Unintended consequences of regulatory reporting requirements for small and medium size construction entities : Australian evidence

The Queensland Building Services Authority (QBSA) regulates the construction industry in Queensland, Australia, with licensing requirements creating differential financial reporting obligations, depending on firm size. Economic theories of regulation and behaviour provide a framework for investigating effects of the financial constraints and financial reporting requirements imposed by QBSA licensing. Data are analysed for all small and medium construction entities operating in Queensland between 2001 and 2006. Findings suggesting that construction licensees are categorizing themselves as smaller to avoid the more onerous and costly financial reporting of higher licensee categories are consistent with US findings from the 2002 Sarbanes-Oxley (SOX) regulation which created incentives for small firms to stay small to avoid the costs of compliance with more onerous financial reporting requirements. Such behaviour can have the undesirable economic consequences of adversely affecting employment, investment, wealth creation and financial stability. Insights and implications from the analysed QBSA processes are important for future policy reform and design, and useful to be considered where similar regulatory approaches are planned.

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.

Variational Bayes and the reduced dependence approximation for the autologistic model on an irregular grid with applications

Discrete Markov random field models provide a natural framework for representing images or spatial datasets. They model the spatial association present while providing a convenient Markovian dependency structure and strong edge-preservation properties. However, parameter estimation for discrete Markov random field models is difficult due to the complex form of the associated normalizing constant for the likelihood function. For large lattices, the reduced dependence approximation to the normalizing constant is based on the concept of performing computationally efficient and feasible forward recursions on smaller sublattices which are then suitably combined to estimate the constant for the whole lattice. We present an efficient computational extension of the forward recursion approach for the autologistic model to lattices that have an irregularly shaped boundary and which may contain regions with no data; these lattices are typical in applications. Consequently, we also extend the reduced dependence approximation to these scenarios enabling us to implement a practical and efficient non-simulation based approach for spatial data analysis within the variational Bayesian framework. The methodology is illustrated through application to simulated data and example images. The supplemental materials include our C++ source code for computing the approximate normalizing constant and simulation studies.

Reduced-Size microstrip patch antenna for Bluetooth applications

A novel reduced-size microstrip rectangular patch antenna for Bluetooth operation is presented in this paper. The proposed antenna operates in the 2400 to 2484 MHz ISM Band. Although an air substrate is introduced, antenna occupies a small volume of 33.3×6.6×0.8 mm3. The gain and the impedance bandwidth of the antenna are predicted using a commercial Finite Element Method software package. The predicted results show good agreement with measured data.

How does the size and shape of local populations in China compare to general anthropometric surveys currently used for product design?

Anthropometry has long been used for a range of ergonomic applications & product design. Although products are often designed for specific cohorts, anthropometric data are typically sourced from large scale surveys representative of the general population. Additionally, few data are available for emerging markets like China and India. This study measured 80 Chinese males that were representative of a specific cohort targeted for the design of a new product. Thirteen anthropometric measurements were recorded and compared to two large databases that represented a general population, a Chinese database and a Western database. Substantial differences were identified between the Chinese males measured in this study and both databases. The subjects were substantially taller, heavier and broader than subjects in the older Chinese database. However, they were still substantially smaller, lighter and thinner than Western males. Data from current Western anthropometric surveys are unlikely to accurately represent the target population for product designers and manufacturers in emerging markets like China.

Influence of field size on pupil diameter under photopic and mesopic light levels

Purpose: We investigated the interaction between adapting field size and luminance on pupil diameter when cones alone (photopic) or rods and cones (mesopic) were active. Method: Circular achromatic targets (1o to 24o diameter) were presented to eight young participants on a rectangular projector screen. The accommodative influence on pupil diameter was minimized using cycloplegia in the fixing right eye and the consensual pupil reflex was measured in the left eye. Target luminance was adjusted for each stimulus such that corneal flux density (product of field area and luminance) was constant at 3600 cd.deg2m-2 (photopic condition) and 1.49 cd.deg2m-2 (mesopic condition). Results: There were no statistically significant effects of adaptive field size on pupil diameter for either condition. Conclusion: If corneal flux density is kept constant, there will be no change in pupil diameter as the size of the stimulus field increases at either mesopic or photopic lighting levels up to at least 24°.

Separation of acoustic emission signals from small size multi-cylinder diesel engine

This paper presents techniques which can lead to diagnosis of faults in a small size multi-cylinder diesel engine. Preliminary analysis of the acoustic emission (AE) signals is outline, including time-frequency analysis and selection of optimum frequency band.The results of applying mean field independent component analysis (MFICA) to separate the AE root mean square (RMS) signals and the effects of changing parameter values are also outlined. The results on separation of RMS signals show thsi technique has the potential of increasing the probability to successfully identify the AE events associated with the various mechanical events within the combustion process of multi-cylinder diesel engines.

Studies on the effect of the size of polycaprolactone microspheres for the dispersion of Salbutamol Sulfate from dry powder inhaler formulations

Purpose: To study the effect of the size of the surface-coated polycaprolactone (PCL) microparticle carriers on the aerosolization and dispersion of Salbutamol Sulfate (SS) from Dry Powder Inhaler (DPI) formulations. Methods: The microparticles were fabricated using an emulsion technique in four different sizes (25, 48, 104 and 150 μm) and later coated with Magnesium stearate (MgSt) and leucine. They were characterized by laser diffraction and SEM. The Fine Particle Fraction (FPF) of SS from powder mixtures was determined by a Twin Stage Impinger (TSI). Results: As the carrier size increased from 25 μm to 150 μm, the FPF of the SS delivered by the coated PCL particles increased approximately four fold. A linear relationship was found between the FPF and Volume mean Diameter (VMD) of the particles over this range. Conclusions: The dispersion behaviour of SS from PCL carriers was dependent on the inherent size of the carriers and the increased FPF of SS with increased carrier size probably reflects the higher mechanical forces produced due to the carrier-carrier collisions or collisions between the carrier particles and the internal walls of the inhaler during aerosolization.

Computationally efficient methods for solving time-variable-order time-space fractional reaction-diffusion equation

Fractional differential equations are becoming more widely accepted as a powerful tool in modelling anomalous diffusion, which is exhibited by various materials and processes. Recently, researchers have suggested that rather than using constant order fractional operators, some processes are more accurately modelled using fractional orders that vary with time and/or space. In this paper we develop computationally efficient techniques for solving time-variable-order time-space fractional reaction-diffusion equations (tsfrde) using the finite difference scheme. We adopt the Coimbra variable order time fractional operator and variable order fractional Laplacian operator in space where both orders are functions of time. Because the fractional operator is nonlocal, it is challenging to efficiently deal with its long range dependence when using classical numerical techniques to solve such equations. The novelty of our method is that the numerical solution of the time-variable-order tsfrde is written in terms of a matrix function vector product at each time step. This product is approximated efficiently by the Lanczos method, which is a powerful iterative technique for approximating the action of a matrix function by projecting onto a Krylov subspace. Furthermore an adaptive preconditioner is constructed that dramatically reduces the size of the required Krylov subspaces and hence the overall computational cost. Numerical examples, including the variable-order fractional Fisher equation, are presented to demonstrate the accuracy and efficiency of the approach.

Sequential fusion of decisions with favorable dependence for controlled verification errors

Statistical dependence between classifier decisions is often shown to improve performance over statistically independent decisions. Though the solution for favourable dependence between two classifier decisions has been derived, the theoretical analysis for the general case of 'n' client and impostor decision fusion has not been presented before. This paper presents the expressions developed for favourable dependence of multi-instance and multi-sample fusion schemes that employ 'AND' and 'OR' rules. The expressions are experimentally evaluated by considering the proposed architecture for text-dependent speaker verification using HMM based digit dependent speaker models. The improvement in fusion performance is found to be higher when digit combinations with favourable client and impostor decisions are used for speaker verification. The total error rate of 20% for fusion of independent decisions is reduced to 2.1% for fusion of decisions that are favourable for both client and impostors. The expressions developed here are also applicable to other biometric modalities, such as finger prints and handwriting samples, for reliable identity verification.

A novel SNP in COMT is associated with alcohol dependence but not opiate or nicotine dependence: a case control study

Background It is well established that COMT is a strong candidate gene for substance use disorder and schizophrenia. Recently we identified two SNPs in COMT (rs4680 and rs165774) that are associated with schizophrenia in an Australian cohort. Individuals with schizophrenia were more than twice as likely to carry the GG genotype compared to the AA genotype for both the rs165774 and rs4680 SNPs. Association of both rs4680 and rs165774 with substance dependence, a common comorbidity of schizophrenia has not been investigated. Methods To determine whether COMT is important in substance dependence, rs165774 and rs4680 were genotyped and haplotyped in patients with nicotine, alcohol and opiate dependence. Results The rs165774 SNP was associated with alcohol dependence. However, it was not associated with nicotine or opiate dependence. Individuals with alcohol dependence were more than twice as likely to carry the GG or AG genotypes compared to the AA genotype, indicating a dominant mode of inheritance. The rs4680 SNP showed a weak association with alcohol dependence at the allele level that did not reach significance at the genotype level but it was not associated with nicotine or opiate dependence. Analysis of rs165774/rs4680 haplotypes also revealed association with alcohol dependence with the G/G haplotype being almost 1.5 times more common in alcohol-dependent cases. Conclusions Our study provides further support for the importance of the COMT in alcohol dependence in addition to schizophrenia. It is possible that the rs165774 SNP, in combination with rs4680, results in a common molecular variant of COMT that contributes to schizophrenia and alcohol dependence susceptibility. This is potentially important for future studies of comorbidity. As our participant numbers are limited our observations should be viewed with caution until they are independently replicated.

Measuring the apparent size of the Moon with a digital camera

The Moon appears to be much larger closer to the horizon than when higher in the sky. This is called the ‘Moon Illusion’ since the observed size of the Moon is not actually larger when the Moon is just above the horizon. This article describes a technique for verifying that the observed size of the Moon in not larger on the horizon. The technique can be easily performed in a high school teaching environment. Moreover, the technique demonstrates the surprising fact that the observed size of the Moon is actually smaller on the horizon due to atmospheric refraction. For the purposes of this paper, several images of the moon were taken with the Moon close to the horizon and close to the zenith. Images were processed using a free program called ImageJ. The Moon was found to be 5.73 ±0.04% smaller in area on the horizon then at the zenith.

A DRD2 and ANKK1 haplotype is associated with nicotine dependence

To test the importance of the dopamine D2 receptor (DRD2) region in nicotine dependence, 150 smokers and 228 controls were genotyped for the DRD2 C957T, -141delC and ANKK1 TaqIA polymorphisms (rs6277, rs1799732 and rs1800497, respectively). The -141delC SNP did not show any association but both the C957T and TaqIA SNPs showed association at the allele, genotype, haplotype and combined genotype levels. The 957C/TaqI A1 haplotype was more than 3.5 times as likely to be associated with nicotine dependence compared with the 957T/TaqI A1 haplotype (P = 0.003). Analysis of the combined genotypes of both SNPs revealed that individuals who were homozygous for the 957C-allele (CC) and had either one or two copies of the TaqI A1-allele were 3.3 times as likely to have nicotine dependence compared to all other genotype combinations (P = 0.0003) and that these genotypes accounted for approximately 13% of the susceptibility to nicotine addiction in our population. Our findings suggest that the DRD2 C957T polymorphism and the ANKK1 TaqIA polymorphism are key contributors to the genetic susceptibility to nicotine dependence.