Incentivising private health insurance through the income tax regime : Capitalising on behavioural models

The Australian income tax regime is generally regarded as a mechanism by which the Federal Government raises revenue, with much of the revenue raised used to support public spending programs. A prime example of this type of spending program is health care. However, a government may also decide that the private sector should provide a greater share of the nation's health care. To achieve such a policy it can bring about change through positive regulation, or it can use the taxation regime, via tax expenditures, not to raise revenue but to steer or influence individuals in its desired direction. When used for this purpose, tax expenditures steer taxpayers towards or away from certain behaviour by either imposing costs on, or providing benefits to them. Within the context of the health sector, the Australian Federal Government deploys social steering via the tax system, with the Medicare Levy Surcharge and the 30 percent Private Health Insurance Rebate intended to steer taxpayer behaviour towards the Government’s policy goal of increasing the amount of health provision through the private sector. These steering mechanisms are complemented by the ‘Lifetime Health Cover Initiative’. This article, through the lens of behavioural economics, considers the ways in which these assorted mechanisms might have been expected to operate and whether they encourage individuals to purchase private health insurance.

The development of a naturalistic car following model for assessing managed motorway systems' safety effects

This thesis highlights the limitations of the existing car following models to emulate driver behaviour for safety study purposes. It also compares the capabilities of the mainstream car following models emulating driver behaviour precise parameters such as headways and Time to Collisions. The comparison evaluates the robustness of each car following model for safety metric reproductions. A new car following model, based on the personal space concept and fish school model is proposed to simulate more precise traffic metrics. This new model is capable of reflecting changes in the headway distribution after imposing the speed limit form VSL systems. This research facilitates assessing Intelligent Transportation Systems on motorways, using microscopic simulation.

Causal behavioural profiles : efficient computation, applications, and evaluation

Analysis of behavioural consistency is an important aspect of software engineering. In process and service management, consistency verification of behavioural models has manifold applications. For instance, a business process model used as system specification and a corresponding workflow model used as implementation have to be consistent. Another example would be the analysis to what degree a process log of executed business operations is consistent with the corresponding normative process model. Typically, existing notions of behaviour equivalence, such as bisimulation and trace equivalence, are applied as consistency notions. Still, these notions are exponential in computation and yield a Boolean result. In many cases, however, a quantification of behavioural deviation is needed along with concepts to isolate the source of deviation. In this article, we propose causal behavioural profiles as the basis for a consistency notion. These profiles capture essential behavioural information, such as order, exclusiveness, and causality between pairs of activities of a process model. Consistency based on these profiles is weaker than trace equivalence, but can be computed efficiently for a broad class of models. In this article, we introduce techniques for the computation of causal behavioural profiles using structural decomposition techniques for sound free-choice workflow systems if unstructured net fragments are acyclic or can be traced back to S- or T-nets. We also elaborate on the findings of applying our technique to three industry model collections.

Importance of animal models in schizophrenia research

Objective This review aims to summarize the importance of animal models for research on psychiatric illnesses, particularly schizophrenia. Method and Results Several aspects of animal models are addressed, including animal experimentation ethics and theoretical considerations of different aspects of validity of animal models. A more specific discussion is included on two of the most widely used behavioural models, psychotropic drug-induced locomotor hyperactivity and prepulse inhibition, followed by comments on the difficulty of modelling negative symptoms of schizophrenia. Furthermore, we emphasize the impact of new developments in molecular biology and the generation of genetically modified mice, which have generated the concept of behavioural phenotyping. Conclusions Complex psychiatric illnesses, such as schizophrenia, cannot be exactly reproduced in species such as rats and mice. Nevertheless, by providing new information on the role of neurotransmitter systems and genes in behavioural function, animal 'models' can be an important tool in unravelling mechanisms involved in the symptoms and development of such illnesses, alongside approaches such as post-mortem studies, cognitive and psychophysiological studies, imaging and epidemiology.

Abeta oligomer toxicity inhibitor protects memory in models of synaptic toxicity

BACKGROUND AND PURPOSE:

Amyloid-ß (Aß) aggregation into synaptotoxic, prefibrillar oligomers is a major pathogenic event underlying the neuropathology of Alzheimer's disease (AD). The pharmacological and neuroprotective properties of a novel Aß aggregation inhibitor, SEN1269, were investigated on aggregation and cell viability and in test systems relevant to synaptic function and memory, using both synthetic Aß(1-42) and cell-derived Aß oligomers.
EXPERIMENTAL APPROACH:

Surface plasmon resonance studies measured binding of SEN1269 to Aß(1-42) . Thioflavin-T fluorescence and MTT assays were used to measure its ability to block Aß(1-42) -induced aggregation and reduction in cell viability. In vitro and in vivo long-term potentiation (LTP) experiments measured the effect of SEN1269 on deficits induced by synthetic Aß(1-42) and cell-derived Aß oligomers. Following i.c.v. administration of the latter, a complex (alternating-lever cyclic ratio) schedule of operant responding measured effects on memory in freely moving rats.
KEY RESULTS:

SEN1269 demonstrated direct binding to monomeric Aß(1-42) , produced a concentration-related blockade of Aß(1-42) aggregation and protected neuronal cell lines exposed to Aß(1-42) . In vitro, SEN1269 alleviated deficits in hippocampal LTP induced by Aß(1-42) and cell-derived Aß oligomers. In vivo, SEN1269 reduced the deficits in LTP and memory induced by i.c.v. administration of cell-derived Aß oligomers.
CONCLUSIONS AND IMPLICATIONS:

SEN1269 protected cells exposed to Aß(1-42) , displayed central activity with respect to reducing Aß-induced neurotoxicity and was neuroprotective in electrophysiological and behavioural models of memory relevant to Aß-induced neurodegeneration. It represents a promising lead for designing inhibitors of Aß-mediated synaptic toxicity as potential neuroprotective agents for treating AD.

Models of human behaviour in social-ecological systems

Environmental change research often relies on simplistic, static models of human behaviour in social-ecological systems. This limits understanding of how social-ecological change occurs. Integrative, process-based behavioural models, which include feedbacks between action, and social and ecological system structures and dynamics, can inform dynamic policy assessment in which decision making is internalised in the model. These models focus on dynamics rather than states. They stimulate new questions and foster interdisciplinarity between and within the natural and social sciences.

Simulation models of obesity : a review of the literature and implications for research and policy

Simulation models (SMs) combine information from a variety of sources to provide a useful tool for examining how the effects of obesity unfold over time and impact population health. SMs can aid in the understanding of the complex interaction of the drivers of diet and activity and their relation to health outcomes. As emphasized in a recently released report of the Institute or Medicine, SMs can be especially useful for considering the potential impact of an array of policies that will be required to tackle the obesity problem. The purpose of this paper is to present an overview of existing SMs for obesity. First, a background section introduces the different types of models, explains how models are constructed, shows the utility of SMs and discusses their strengths and weaknesses. Using these typologies, we then briefly review extant obesity SMs. We categorize these models according to their focus: health and economic outcomes, trends in obesity as a function of past trends, physiologically based behavioural models, environmental contributors to obesity and policy interventions. Finally, we suggest directions for future research.

Behavioural analysis of mouse mutants with altered neuronal and glial genes

Im ersten Teil dieser Doktorarbeit beabsichtigte meine Arbeit, die funktionelle Beteiligung des CB1 Rezeptors, einer Hauptkomponente des neuronalen Endocannabinoid-Systems (ECS), an der Ausbildung von verschiedenen Verhaltensphänotypen mit Hilfe von konditionalen Mausmutanten, denen der CB1 Rezeptor auf verschiedenen neuronalen Unterpopulationen fehlt, aufzuschlüsseln und zu untersuchen. Verschiedene Verhaltensmodelle wurden hierzu getestet. Dabei lag der Fokus dieser Arbeit auf der CB1f/f;D1-Cre Mauslinie, welche der CB1 Rezeptor auf den D1 Rezeptor exprimierenden Neuronen des Striatums fehlt. Ich konnte zeigen, dass der Verlust des CB1 Rezeptors auf diesen Neuronen keinen Einfluss auf basale neurologische Funktionen, Gewicht, Bewegung, Exploration, Sozialverhalten, Angst und Stressbewältigung der Tiere hat, jedoch eine Beteiligung an der Entwicklung von Suchtverhalten gegeben ist. Bei Betrachtung des Kokain-induzierten Suchtverhaltens zeigten die konditionalen Mausmutanten eine reduzierte Suchtanfälligkeit sowohl im Vergleich zu Tieren mit einem totalen CB1 Rezeptor Verlust in allen Körperzellen, als auch zu genetisch unveränderten Kontrollmäusen beider Linien.rnDes Weiteren zeigen die Ergebnisse dieser Studie eine große, aber gegensätzliche Beteiligung des ECS bei der Regulation von Exploration in Abhängigkeit des Verlustes des CB1 Rezeptors auf GABAergen Neuronen des Vorderhirns und kortikalen glutamatergen Neuronen, jedoch nicht auf striatalen Neuronen alleine. Zusätzlich war ich in der Lage, die Wichtigkeit des genetischen Hintergrunds von Mauslinien nicht nur auf die Ausbildung von spezifischen Verhaltensphänotypen, sondern auch auf die Genexpression zu zeigen.rnIn dem zweiten Teil dieser Arbeit, in dem ich mich auf die Funktion von Gliazellen konzentrierte, wurden ebenfalls Mausmutanten in verschiedenen Verhaltensmodellen getestet. Ein genetisches Auslöschen des NG2 Glykoproteins in Gliazellen sorgt in den Knock-out Mäusen für ein schlechteres Hörvermögen und ein reduziertes Depressionsverhalten im Vergleich zu ihren Wildtyp-Kontrollmäusen. Interessanterweise zeigten diese Tiere auch eine reduzierte Empfänglichkeit bei chemisch induzierten epileptischen Krämpfen, was eine Rolle des NG2 Glykoproteins bei der Kontrolle der glutamatergen Homöostase vorschlägt, die wahrscheinlich durch Strukturänderungen der Neuron-Glia-Synapse verursacht wird. rn

Confusion with diffusion? Unravelling is diffusion and innovation literature with a focus on SMEs

The aim of this paper is to contribute to the understanding of various models used in research for the adoption and diffusion of information technology in small and medium-sized enterprises (SMEs). Starting with Rogers' diffusion theory and behavioural models, technology adoption models used in IS research are discussed. Empirical research has shown that the reasons why firms choose to adopt or not adopt technology is dependent on a number of factors. These factors can be categorised as owner/manager characteristics, firm characteristics and other characteristics. The existing models explaining IS diffusion and adoption by SMEs overlap and complement each other. This paper reviews the existing literature and proposes a comprehensive model which includes the whole array of variables from earlier models.

Efficient methods for empirical tests of behavioral economics theories in laboratory and field experiments

In the quest for a descriptive theory of decision-making, the rational actor model in economics imposes rather unrealistic expectations and abilities on human decision makers. The further we move from idealized scenarios, such as perfectly competitive markets, and ambitiously extend the reach of the theory to describe everyday decision making situations, the less sense these assumptions make. Behavioural economics has instead proposed models based on assumptions that are more psychologically realistic, with the aim of gaining more precision and descriptive power. Increased psychological realism, however, comes at the cost of a greater number of parameters and model complexity. Now there are a plethora of models, based on different assumptions, applicable in differing contextual settings, and selecting the right model to use tends to be an ad-hoc process. In this thesis, we develop optimal experimental design methods and evaluate different behavioral theories against evidence from lab and field experiments.

We look at evidence from controlled laboratory experiments. Subjects are presented with choices between monetary gambles or lotteries. Different decision-making theories evaluate the choices differently and would make distinct predictions about the subjects' choices. Theories whose predictions are inconsistent with the actual choices can be systematically eliminated. Behavioural theories can have multiple parameters requiring complex experimental designs with a very large number of possible choice tests. This imposes computational and economic constraints on using classical experimental design methods. We develop a methodology of adaptive tests: Bayesian Rapid Optimal Adaptive Designs (BROAD) that sequentially chooses the "most informative" test at each stage, and based on the response updates its posterior beliefs over the theories, which informs the next most informative test to run. BROAD utilizes the Equivalent Class Edge Cutting (EC²) criteria to select tests. We prove that the EC² criteria is adaptively submodular, which allows us to prove theoretical guarantees against the Bayes-optimal testing sequence even in the presence of noisy responses. In simulated ground-truth experiments, we find that the EC² criteria recovers the true hypotheses with significantly fewer tests than more widely used criteria such as Information Gain and Generalized Binary Search. We show, theoretically as well as experimentally, that surprisingly these popular criteria can perform poorly in the presence of noise, or subject errors. Furthermore, we use the adaptive submodular property of EC² to implement an accelerated greedy version of BROAD which leads to orders of magnitude speedup over other methods.

We use BROAD to perform two experiments. First, we compare the main classes of theories for decision-making under risk, namely: expected value, prospect theory, constant relative risk aversion (CRRA) and moments models. Subjects are given an initial endowment, and sequentially presented choices between two lotteries, with the possibility of losses. The lotteries are selected using BROAD, and 57 subjects from Caltech and UCLA are incentivized by randomly realizing one of the lotteries chosen. Aggregate posterior probabilities over the theories show limited evidence in favour of CRRA and moments' models. Classifying the subjects into types showed that most subjects are described by prospect theory, followed by expected value. Adaptive experimental design raises the possibility that subjects could engage in strategic manipulation, i.e. subjects could mask their true preferences and choose differently in order to obtain more favourable tests in later rounds thereby increasing their payoffs. We pay close attention to this problem; strategic manipulation is ruled out since it is infeasible in practice, and also since we do not find any signatures of it in our data.

In the second experiment, we compare the main theories of time preference: exponential discounting, hyperbolic discounting, "present bias" models: quasi-hyperbolic (α, β) discounting and fixed cost discounting, and generalized-hyperbolic discounting. 40 subjects from UCLA were given choices between 2 options: a smaller but more immediate payoff versus a larger but later payoff. We found very limited evidence for present bias models and hyperbolic discounting, and most subjects were classified as generalized hyperbolic discounting types, followed by exponential discounting.

In these models the passage of time is linear. We instead consider a psychological model where the perception of time is subjective. We prove that when the biological (subjective) time is positively dependent, it gives rise to hyperbolic discounting and temporal choice inconsistency.

We also test the predictions of behavioral theories in the "wild". We pay attention to prospect theory, which emerged as the dominant theory in our lab experiments of risky choice. Loss aversion and reference dependence predicts that consumers will behave in a uniquely distinct way than the standard rational model predicts. Specifically, loss aversion predicts that when an item is being offered at a discount, the demand for it will be greater than that explained by its price elasticity. Even more importantly, when the item is no longer discounted, demand for its close substitute would increase excessively. We tested this prediction using a discrete choice model with loss-averse utility function on data from a large eCommerce retailer. Not only did we identify loss aversion, but we also found that the effect decreased with consumers' experience. We outline the policy implications that consumer loss aversion entails, and strategies for competitive pricing.

In future work, BROAD can be widely applicable for testing different behavioural models, e.g. in social preference and game theory, and in different contextual settings. Additional measurements beyond choice data, including biological measurements such as skin conductance, can be used to more rapidly eliminate hypothesis and speed up model comparison. Discrete choice models also provide a framework for testing behavioural models with field data, and encourage combined lab-field experiments.

Novel roles for the GABAB receptor in anxiety and cocaine addiction

The GABAB receptor has been postulated as a possible drug target in the treatment of anxiety disorders and cocaine addiction. Indeed, a wealth of preclinical data is emerging that has shown that mice lacking functional GABAB receptors display a highly anxious behaviour across a range of behavioural models of anxiety. Additionally, novel compounds that act by altering the allosteric conformation of the GABAB receptor to a more active state; the GABAB receptor positive modulators, have been repeatedly demonstrated to have anxiolytic effects in animals. In addition to being a putative anxiolytic drug target, the GABAB receptor has been identified as a novel target for antiaddictive therapies. Indeed GABAB receptor positive modulators have been demonstrated to have anti-addictive properties across a broad variety of behavioural paradigms. Despite these findings, several gaps in our knowledge of the role played by the GABAB receptor in both anxiety and drug abuse disorder exist. The aim of this thesis was to use preclinical animal models in an effort to further probe the role played by the GABAB receptor in anxiety and addiction. Our studies initially examined the role played by the GABAB receptor in the neurodevelopmental processes underpinning of anxiety. Our studies demonstrated that treating mouse pups in early life with the GABAB receptor agonist baclofen produced an anxious phenotype in adult life, whereas treatment with the GABAB receptor antagonist CGP52432 produced no effects on adult behaviour. Further to this, we examined whether the anxious behaviour induced by early life blockade of the serotonin reuptake transporter was dependant on alterations in GABAB receptor function. Our studies however revealed no effect of early life selective serotonin reuptake inhibitor treatment on adult life baclofen sensitivity. The next issue addressed in this thesis is the characterization of the effects of a GABAB receptor positive modulator and a GABAB receptor antagonist in a behavioural model of conditioned fear behaviour. These novel classes of GABAB receptor ligands have been considerably less well characterized in this facet of preclinical anxiety behaviour than in terms of innate anxiety behaviour. Our study however revealed that the GABAB receptor positive modulator GS39783 and the GABAB receptor antagonist CGP52432 were without effect on the acquisition, expression or extinction of conditioned fear in our model. The next element of this thesis dealt with the characterization of a novel mouse model, the GABAB(2)- S892A mouse. This mouse has been engineered to express a form of the GABAB(2) receptor subunit wherein the function determining serine phosphorylation site cannot be phosphorylated. We initially tested this mouse in terms of its GABAB receptor function in adult life, followed by testing it in a battery of tests of unconditioned and learned anxiety behaviour. We also examined the behavioural and molecular responses of the GABAB(2)-S892A mouse to cocaine. All of our studies appear to show that the GABAB(2)-S892A mouse is indistinguishable from wildtype controls. The final aim of the thesis was to investigate the behavioural and molecular sensitivity of the GABAB(1) subunit isoform null mice, the GABAB(1a) -/- and GABAB(1b) -/- mice to cocaine. Our studies revealed that these mice display differing behavioural responses to cocaine, with the GABAB(1a) -/- mouse displaying a hypersensitivity to the acute locomotor effects of cocaine, while the GABAB(1b) -/- displayed blunted locomotor sensitisation to cocaine.

Self-adaptability and man-in-the-loop: a dilemma in autonomic computing systems

This paper addresses some controversial issues relating to two main questions. Firstly, we discuss 'man-in-the loop' issues in SAACS. Some people advocate this must always be so that man's decisions can override autonomic components. In this case, the system has two subsystems - man and machine. Can we, however, have a fully autonomic machine - with no man in sight; even for short periods of time? What kinds of systems require man to always be in the loop? What is the optimum balance in self-to-human control? How do we determine the optimum? How far can we go in describing self-behaviour? How does a SAACS system handle unexpected behaviour? Secondly, what are the challenges/obstacles in testing SAACS in the context of self/human dilemma? Are there any lesson to be learned from other programmes e.g. Star-wars, aviation and space explorations? What role human factors and behavioural models play whilst in interacting with SAACS?.

Multi-physics modelling for the fabrication, packaging and reliability of micro-systems components

The latest advances in multi-physics modelling both using high fidelity techniques and reduced order and behavioural models will be discussed. Particular focus will be given to the application and validation of these techniques for modelling the fabrication, packaging and subsequent reliability of micro-systems based components. The paper will discuss results from a number of research projects with particular emphasis on the techniques being developed in a major UK Goverment funded project - 3D-MINTEGRATION (www.3d-mintegration.com).

Polynomial Model for High-Order and Multi-Carrier Passive Intermodulation Products

Passive intermodulation (PIM) often limits the performance of communication systems, particularly in the presence of multiple carriers. Since the origins of the apparently multiple physical sources of nonlinearity causing PIM in distributed circuits are not fully understood, the behavioural models are frequently employed to describe the process of PIM generation. In this paper, a memoryless nonlinear polynomial model, capable of predicting high-order multi-carrier intermodulation products, is deduced from the third-order two-tone PIM measurements on a microstrip transmission line with distributed nonlinearity. The analytical model of passive distributed nonlinearity is implemented in Keysight Technology’s ADS simulator to evaluate the adjacent band power ratio for three-tone signals. The obtained results suggest that the costly multi-carrier test setups can possibly be replaced by a simulation tool based on the properly retrieved nonlinear polynomial model.