The causes and consequences of corruption

This thesis comprehensively studies the causes and consequences of corruption in both crosscountry and within-country contexts, mainly focusing on China. The thesis commences by extensively investigating the causes of corruption. Using the standard economic approach, this study finds that in China regions with more anti-corruption efforts, higher education attainment, Anglo-American historic influence, higher openness, more access to media, higher relative wages of government employees, and a greater representation of women in legislature are markedly less corrupt; while the social heterogeneity, deregulation and abundance of resources, substantially breed regional corruption. Moreover, fiscal decentralization is discovered to depress corruption significantly. This study also observes a positive relationship between corruption and the economic development in current China that is mainly driven by the transition to a market economy. Focusing on the influence of political institutions on corruption, the thesis then provides evidence that a high level of political interest helps to reduce corruption within a society, while the effect of democracy upon corruption depends on property rights protection and income distribution. With the social economic approach, however, the thesis presents both cross-country and within-country evidence that the social interaction plays an important role in determining corruption. The thesis then continues by comprehensively evaluating the consequences of corruption in China. The study provides evidence that corruption can simultaneously have both positive and negative effects on economic development. And it also observes that corruption considerably increases the income inequality in China. Furthermore this study finds that corruption in China significantly distorts public expenditures. Local corruption is also observed to substantially reduce FDI in Chinese regions. Finally the study documents that corruption substantially aggravates pollution probably through a loosening of the environmental regulation, and that it also modifies the effects of trade openness and FDI on the stringency of environmental policy. Overall, this thesis adds to the current literature by a number of novel findings concerning both the causes and the consequences of corruption.

Evaluation of texture and geometry for dimensional facial expression recognition

Facial expression recognition (FER) algorithms mainly focus on classification into a small discrete set of emotions or representation of emotions using facial action units (AUs). Dimensional representation of emotions as continuous values in an arousal-valence space is relatively less investigated. It is not fully known whether fusion of geometric and texture features will result in better dimensional representation of spontaneous emotions. Moreover, the performance of many previously proposed approaches to dimensional representation has not been evaluated thoroughly on publicly available databases. To address these limitations, this paper presents an evaluation framework for dimensional representation of spontaneous facial expressions using texture and geometric features. SIFT, Gabor and LBP features are extracted around facial fiducial points and fused with FAP distance features. The CFS algorithm is adopted for discriminative texture feature selection. Experimental results evaluated on the publicly accessible NVIE database demonstrate that fusion of texture and geometry does not lead to a much better performance than using texture alone, but does result in a significant performance improvement over geometry alone. LBP features perform the best when fused with geometric features. Distributions of arousal and valence for different emotions obtained via the feature extraction process are compared with those obtained from subjective ground truth values assigned by viewers. Predicted valence is found to have a more similar distribution to ground truth than arousal in terms of covariance or Bhattacharya distance, but it shows a greater distance between the means.

Auditory spatial acuity approximates the resolving power of space-specific neurons

The relationship between neuronal acuity and behavioral performance was assessed in the barn owl (Tyto alba), a nocturnal raptor renowned for its ability to localize sounds and for the topographic representation of auditory space found in the midbrain. We measured discrimination of sound-source separation using a newly developed procedure involving the habituation and recovery of the pupillary dilation response. The smallest discriminable change of source location was found to be about two times finer in azimuth than in elevation. Recordings from neurons in its midbrain space map revealed that their spatial tuning, like the spatial discrimination behavior, was also better in azimuth than in elevation by a factor of about two. Because the PDR behavioral assay is mediated by the same circuitry whether discrimination is assessed in azimuth or in elevation, this difference in vertical and horizontal acuity is likely to reflect a true difference in sensory resolution, without additional confounding effects of differences in motor performance in the two dimensions. Our results, therefore, are consistent with the hypothesis that the acuity of the midbrain space map determines auditory spatial discrimination.

Massively parallel sequencing and analysis of expressed sequence tags in a successful invasive plant

Background Invasive species pose a significant threat to global economies, agriculture and biodiversity. Despite progress towards understanding the ecological factors associated with plant invasions, limited genomic resources have made it difficult to elucidate the evolutionary and genetic factors responsible for invasiveness. This study presents the first expressed sequence tag (EST) collection for Senecio madagascariensis, a globally invasive plant species. Methods We used pyrosequencing of one normalized and two subtractive libraries, derived from one native and one invasive population, to generate an EST collection. ESTs were assembled into contigs, annotated by BLAST comparison with the NCBI non-redundant protein database and assigned gene ontology (GO) terms from the Plant GO Slim ontologies. Key Results Assembly of the 221 746 sequence reads resulted in 12 442 contigs. Over 50 % (6183) of 12 442 contigs showed significant homology to proteins in the NCBI database, representing approx. 4800 independent transcripts. The molecular transducer GO term was significantly over-represented in the native (South African) subtractive library compared with the invasive (Australian) library. Based on NCBI BLAST hits and literature searches, 40 % of the molecular transducer genes identified in the South African subtractive library are likely to be involved in response to biotic stimuli, such as fungal, bacterial and viral pathogens. Conclusions This EST collection is the first representation of the S. madagascariensis transcriptome and provides an important resource for the discovery of candidate genes associated with plant invasiveness. The over-representation of molecular transducer genes associated with defence responses in the native subtractive library provides preliminary support for aspects of the enemy release and evolution of increased competitive ability hypotheses in this successful invasive. This study highlights the contribution of next-generation sequencing to better understanding the molecular mechanisms underlying ecological hypotheses that are important in successful plant invasions.

Quantification of the accuracy of MRI generated 3D models of long bones compared to CT generated 3D models

Orthopaedic fracture fixation implants are increasingly being designed using accurate 3D models of long bones based on computer tomography (CT). Unlike CT, magnetic resonance imaging (MRI) does not involve ionising radiation and is therefore a desirable alternative to CT. This study aims to quantify the accuracy of MRI-based 3D models compared to CT-based 3D models of long bones. The femora of five intact cadaver ovine limbs were scanned using a 1.5T MRI and a CT scanner. Image segmentation of CT and MRI data was performed using a multi-threshold segmentation method. Reference models were generated by digitising the bone surfaces free of soft tissue with a mechanical contact scanner. The MRI- and CT-derived models were validated against the reference models. The results demonstrated that the CT-based models contained an average error of 0.15mm while the MRI-based models contained an average error of 0.23mm. Statistical validation shows that there are no significant differences between 3D models based on CT and MRI data. These results indicate that the geometric accuracy of MRI based 3D models was comparable to that of CT-based models and therefore MRI is a potential alternative to CT for generation of 3D models with high geometric accuracy.

Gender equity in the professoriate : a cohort study of new women professors in Australia

According to statistics and trend data, women continue to be substantially under- represented in the Australian professoriate, and growth in their representation has been slow despite the plethora of equity programs. While not disputing these facts, we propose that examining gender equity by cohort provides a complementary perspective on the status of gender equity in the professoriate. Based on over 500 survey responses, we detected substantial similarities between women and men who were appointed as professors or associate professors between 2005 and 2008. There were similar proportions of women and men appointed via external or internal processes or by invitation. Additionally, similar proportions of women and men professors expressed a marked preference for research over teaching. Furthermore, there were similar distributions between the genders in the age of appointment to the professoriate. However, a notable gender difference was that women were appointed to the professoriate on average 1.9 years later than mens. This later appointment provides one reason for the lower representation of women compared to men in the professoriate. It also raises questions of the typical length of time that women and men remain in the (paid) professoriate and reasons why they might leave it. A further similarity between women and men in this cohort was their identification of motivation and circumstances as key factors in their career orientation. However, substantially more women identified motivation than circumstances and the situation was reversed for men. The open-ended survey responses also provided confirmation that affirmative action initiatives make a difference to women’s careers.

On a Syntactic Characterization of Classification with a Mind Change Bound

Most learning paradigms impose a particular syntax on the class of concepts to be learned; the chosen syntax can dramatically affect whether the class is learnable or not. For classification paradigms, where the task is to determine whether the underlying world does or does not have a particular property, how that property is represented has no implication on the power of a classifier that just outputs 1’s or 0’s. But is it possible to give a canonical syntactic representation of the class of concepts that are classifiable according to the particular criteria of a given paradigm? We provide a positive answer to this question for classification in the limit paradigms in a logical setting, with ordinal mind change bounds as a measure of complexity. The syntactic characterization that emerges enables to derive that if a possibly noncomputable classifier can perform the task assigned to it by the paradigm, then a computable classifier can also perform the same task. The syntactic characterization is strongly related to the difference hierarchy over the class of open sets of some topological space; this space is naturally defined from the class of possible worlds and possible data of the learning paradigm.

Using visuals to explore the contextual aspects of user-product interactions

Experience underlies all kinds of human knowledge and it is dependent on context. People’s experience within a particular context-of-use determines how they interact with products. Methods employed in this research to elicit human experience have included the use of visuals. This paper describes two empirical studies that employed visual representation of concepts as a means to explore the experiential and contextual component of user- product interactions. One study employed visuals that the participants produced during the study. The other employed visuals that the researcher used as prompts during a focus group session. This paper demonstrates that using visuals in design research is valuable for exploring and understanding the contextual aspects of human experience and its influence on people’s concepts of product use.

Towards an understanding of teacher judgement in the context of social moderation

Social moderation involves teachers gathering together to discuss their judgements of the quality of student work and to reach agreement regarding the standard awarded. This qualitative study conducted over a three-year period investigated the social practice of moderation and the influence on teachers’ judgements of students work. An initial survey of teachers’ understandings of moderation and standards, pre-interviews of teachers who participated in the moderation meetings, observations of these meetings with a particular focus on one teacher (focus teachers) comprised the data collection methods. Data analysis involved organising, matching, coding, identifying patterns and themes using a constant comparative method. Socio-cultural theories of learning and assessment underpinned the approach to data analysis and proved helpful in explaining the diverse influences on teachers’ judgements beyond the task criteria, and the progressive development of shared understandings through engaging in professional discussions of students’ work. The study revealed that the process is not clear and linear and is influenced by factors such as the representation of the standards and the knowledge base of the teachers.

Impact of a data warehouse model for improved decision-making process in healthcare

The health system is one sector dealing with a deluge of complex data. Many healthcare organisations struggle to utilise these volumes of health data effectively and efficiently. Also, there are many healthcare organisations, which still have stand-alone systems, not integrated for management of information and decision-making. This shows, there is a need for an effective system to capture, collate and distribute this health data. Therefore, implementing the data warehouse concept in healthcare is potentially one of the solutions to integrate health data. Data warehousing has been used to support business intelligence and decision-making in many other sectors such as the engineering, defence and retail sectors. The research problem that is going to be addressed is, "how can data warehousing assist the decision-making process in healthcare". To address this problem the researcher has narrowed an investigation focusing on a cardiac surgery unit. This research used the cardiac surgery unit at the Prince Charles Hospital (TPCH) as the case study. The cardiac surgery unit at TPCH uses a stand-alone database of patient clinical data, which supports clinical audit, service management and research functions. However, much of the time, the interaction between the cardiac surgery unit information system with other units is minimal. There is a limited and basic two-way interaction with other clinical and administrative databases at TPCH which support decision-making processes. The aims of this research are to investigate what decision-making issues are faced by the healthcare professionals with the current information systems and how decision-making might be improved within this healthcare setting by implementing an aligned data warehouse model or models. As a part of the research the researcher will propose and develop a suitable data warehouse prototype based on the cardiac surgery unit needs and integrating the Intensive Care Unit database, Clinical Costing unit database (Transition II) and Quality and Safety unit database [electronic discharge summary (e-DS)]. The goal is to improve the current decision-making processes. The main objectives of this research are to improve access to integrated clinical and financial data, providing potentially better information for decision-making for both improved from the questionnaire and by referring to the literature, the results indicate a centralised data warehouse model for the cardiac surgery unit at this stage. A centralised data warehouse model addresses current needs and can also be upgraded to an enterprise wide warehouse model or federated data warehouse model as discussed in the many consulted publications. The data warehouse prototype was able to be developed using SAS enterprise data integration studio 4.2 and the data was analysed using SAS enterprise edition 4.3. In the final stage, the data warehouse prototype was evaluated by collecting feedback from the end users. This was achieved by using output created from the data warehouse prototype as examples of the data desired and possible in a data warehouse environment. According to the feedback collected from the end users, implementation of a data warehouse was seen to be a useful tool to inform management options, provide a more complete representation of factors related to a decision scenario and potentially reduce information product development time. However, there are many constraints exist in this research. For example the technical issues such as data incompatibilities, integration of the cardiac surgery database and e-DS database servers and also, Queensland Health information restrictions (Queensland Health information related policies, patient data confidentiality and ethics requirements), limited availability of support from IT technical staff and time restrictions. These factors have influenced the process for the warehouse model development, necessitating an incremental approach. This highlights the presence of many practical barriers to data warehousing and integration at the clinical service level. Limitations included the use of a small convenience sample of survey respondents, and a single site case report study design. As mentioned previously, the proposed data warehouse is a prototype and was developed using only four database repositories. Despite this constraint, the research demonstrates that by implementing a data warehouse at the service level, decision-making is supported and data quality issues related to access and availability can be reduced, providing many benefits. Output reports produced from the data warehouse prototype demonstrated usefulness for the improvement of decision-making in the management of clinical services, and quality and safety monitoring for better clinical care. However, in the future, the centralised model selected can be upgraded to an enterprise wide architecture by integrating with additional hospital units’ databases.

Multifractal characterisation and analysis of complex networks

Complex networks have been studied extensively due to their relevance to many real-world systems such as the world-wide web, the internet, biological and social systems. During the past two decades, studies of such networks in different fields have produced many significant results concerning their structures, topological properties, and dynamics. Three well-known properties of complex networks are scale-free degree distribution, small-world effect and self-similarity. The search for additional meaningful properties and the relationships among these properties is an active area of current research. This thesis investigates a newer aspect of complex networks, namely their multifractality, which is an extension of the concept of selfsimilarity. The first part of the thesis aims to confirm that the study of properties of complex networks can be expanded to a wider field including more complex weighted networks. Those real networks that have been shown to possess the self-similarity property in the existing literature are all unweighted networks. We use the proteinprotein interaction (PPI) networks as a key example to show that their weighted networks inherit the self-similarity from the original unweighted networks. Firstly, we confirm that the random sequential box-covering algorithm is an effective tool to compute the fractal dimension of complex networks. This is demonstrated on the Homo sapiens and E. coli PPI networks as well as their skeletons. Our results verify that the fractal dimension of the skeleton is smaller than that of the original network due to the shortest distance between nodes is larger in the skeleton, hence for a fixed box-size more boxes will be needed to cover the skeleton. Then we adopt the iterative scoring method to generate weighted PPI networks of five species, namely Homo sapiens, E. coli, yeast, C. elegans and Arabidopsis Thaliana. By using the random sequential box-covering algorithm, we calculate the fractal dimensions for both the original unweighted PPI networks and the generated weighted networks. The results show that self-similarity is still present in generated weighted PPI networks. This implication will be useful for our treatment of the networks in the third part of the thesis. The second part of the thesis aims to explore the multifractal behavior of different complex networks. Fractals such as the Cantor set, the Koch curve and the Sierspinski gasket are homogeneous since these fractals consist of a geometrical figure which repeats on an ever-reduced scale. Fractal analysis is a useful method for their study. However, real-world fractals are not homogeneous; there is rarely an identical motif repeated on all scales. Their singularity may vary on different subsets; implying that these objects are multifractal. Multifractal analysis is a useful way to systematically characterize the spatial heterogeneity of both theoretical and experimental fractal patterns. However, the tools for multifractal analysis of objects in Euclidean space are not suitable for complex networks. In this thesis, we propose a new box covering algorithm for multifractal analysis of complex networks. This algorithm is demonstrated in the computation of the generalized fractal dimensions of some theoretical networks, namely scale-free networks, small-world networks, random networks, and a kind of real networks, namely PPI networks of different species. Our main finding is the existence of multifractality in scale-free networks and PPI networks, while the multifractal behaviour is not confirmed for small-world networks and random networks. As another application, we generate gene interactions networks for patients and healthy people using the correlation coefficients between microarrays of different genes. Our results confirm the existence of multifractality in gene interactions networks. This multifractal analysis then provides a potentially useful tool for gene clustering and identification. The third part of the thesis aims to investigate the topological properties of networks constructed from time series. Characterizing complicated dynamics from time series is a fundamental problem of continuing interest in a wide variety of fields. Recent works indicate that complex network theory can be a powerful tool to analyse time series. Many existing methods for transforming time series into complex networks share a common feature: they define the connectivity of a complex network by the mutual proximity of different parts (e.g., individual states, state vectors, or cycles) of a single trajectory. In this thesis, we propose a new method to construct networks of time series: we define nodes by vectors of a certain length in the time series, and weight of edges between any two nodes by the Euclidean distance between the corresponding two vectors. We apply this method to build networks for fractional Brownian motions, whose long-range dependence is characterised by their Hurst exponent. We verify the validity of this method by showing that time series with stronger correlation, hence larger Hurst exponent, tend to have smaller fractal dimension, hence smoother sample paths. We then construct networks via the technique of horizontal visibility graph (HVG), which has been widely used recently. We confirm a known linear relationship between the Hurst exponent of fractional Brownian motion and the fractal dimension of the corresponding HVG network. In the first application, we apply our newly developed box-covering algorithm to calculate the generalized fractal dimensions of the HVG networks of fractional Brownian motions as well as those for binomial cascades and five bacterial genomes. The results confirm the monoscaling of fractional Brownian motion and the multifractality of the rest. As an additional application, we discuss the resilience of networks constructed from time series via two different approaches: visibility graph and horizontal visibility graph. Our finding is that the degree distribution of VG networks of fractional Brownian motions is scale-free (i.e., having a power law) meaning that one needs to destroy a large percentage of nodes before the network collapses into isolated parts; while for HVG networks of fractional Brownian motions, the degree distribution has exponential tails, implying that HVG networks would not survive the same kind of attack.

Projecting Computational Sense of Self: A Study of Transition in a Chronic Illness Online Community

We report on analysis of discussions in an online community of people with chronic illness using socio-cognitively motivated, automatically produced semantic spaces. The analysis aims to further the emerging theory of "transition" (how people can learn to incorporate the consequences of illness into their lives). An automatically derived representation of sense of self for individuals is created in the semantic space by the analysis of the email utterances of the community members. The movement over time of the sense of self is visualised, via projection, with respect to axes of "ordinariness" and "extra-ordinariness". Qualitative evaluation shows that the visualisation is paralleled by the transitions of people during the course of their illness. The research aims to progress tools for analysis of textual data to promote greater use of tacit knowledge as found in online virtual communities. We hope it also encourages further interest in representation of sense-of-self.

A subject-specific model of human buttocks and thighs in a seated posture

Finite element analyses of the human body in seated postures requires digital models capable of providing accurate and precise prediction of the tissue-level response of the body in the seated posture. To achieve such models, the human anatomy must be represented with high fidelity. This information can readily be defined using medical imaging techniques such as Magnetic Resonance Imaging (MRI) or Computed Tomography (CT). Current practices for constructing digital human models, based on the magnetic resonance (MR) images, in a lying down (supine) posture have reduced the error in the geometric representation of human anatomy relative to reconstructions based on data from cadaveric studies. Nonetheless, the significant differences between seated and supine postures in segment orientation, soft-tissue deformation and soft tissue strain create a need for data obtained in postures more similar to the application posture. In this study, we present a novel method for creating digital human models based on seated MR data. An adult-male volunteer was scanned in a simulated driving posture using a FONAR 0.6T upright MRI scanner with a T1 scanning protocol. To compensate for unavoidable image distortion near the edges of the study, images of the same anatomical structures were obtained in transverse and sagittal planes. Combinations of transverse and sagittal images were used to reconstruct the major anatomical features from the buttocks through the knees, including bone, muscle and fat tissue perimeters, using Solidworks® software. For each MR image, B-splines were created as contours for the anatomical structures of interest, and LOFT commands were used to interpolate between the generated Bsplines. The reconstruction of the pelvis, from MR data, was enhanced by the use of a template model generated in previous work CT images. A non-rigid registration algorithm was used to fit the pelvis template into the MR data. Additionally, MR image processing was conducted to both the left and the right sides of the model due to the intended asymmetric posture of the volunteer during the MR measurements. The presented subject-specific, three-dimensional model of the buttocks and thighs will add value to optimisation cycles in automotive seat development when used in simulating human interaction with automotive seats.

The contribution of seat components to seat hardness and the interface between human occupant and a driver seat

Effective digital human model (DHM) simulation of automotive driver packaging ergonomics, safety and comfort depends on accurate modelling of occupant posture, which is strongly related to the mechanical interaction between human body soft tissue and flexible seat components. This paper comprises: a study investigating the component mechanical behaviour of a spring-suspended, production level seat when indented by SAE J826 type, human thigh-buttock representing hard shell; a model of seated human buttock shape for improved indenter design using a multivariate representation of Australian population thigh-buttock anthropometry; and a finite-element study simulating the deflection of human buttock and thigh soft tissue when seated, based on seated MRI. The results of the three studies provide a description of the mechanical properties of the driver-seat interface, and allow validation of future dynamic simulations, involving multi-body and finite-element (FE) DHM in virtual ergonomic studies.

Tests and Models of Non-compositional Concepts

The question of under what conditions conceptual representation is compositional remains debatable within cognitive science. This paper proposes a well developed mathematical apparatus for a probabilistic representation of concepts, drawing upon methods developed in quantum theory to propose a formal test that can determine whether a specific conceptual combination is compositional, or not. This test examines a joint probability distribution modeling the combination, asking whether or not it is factorizable. Empirical studies indicate that some combinations should be considered non-compositionally.