Flexible high voltage pulsed power supply for plasma applications

Demands for delivering high instantaneous power in a compressed form (pulse shape) have widely increased during recent decades. The flexible shapes with variable pulse specifications offered by pulsed power have made it a practical and effective supply method for an extensive range of applications. In particular, the release of basic subatomic particles (i.e. electron, proton and neutron) in an atom (ionization process) and the synthesizing of molecules to form ions or other molecules are among those reactions that necessitate large amount of instantaneous power. In addition to the decomposition process, there have recently been requests for pulsed power in other areas such as in the combination of molecules (i.e. fusion, material joining), gessoes radiations (i.e. electron beams, laser, and radar), explosions (i.e. concrete recycling), wastewater, exhausted gas, and material surface treatments. These pulses are widely employed in the silent discharge process in all types of materials (including gas, fluid and solid); in some cases, to form the plasma and consequently accelerate the associated process. Due to this fast growing demand for pulsed power in industrial and environmental applications, the exigency of having more efficient and flexible pulse modulators is now receiving greater consideration. Sensitive applications, such as plasma fusion and laser guns also require more precisely produced repetitive pulses with a higher quality. Many research studies are being conducted in different areas that need a flexible pulse modulator to vary pulse features to investigate the influence of these variations on the application. In addition, there is the need to prevent the waste of a considerable amount of energy caused by the arc phenomena that frequently occur after the plasma process. The control over power flow during the supply process is a critical skill that enables the pulse supply to halt the supply process at any stage. Different pulse modulators which utilise different accumulation techniques including Marx Generators (MG), Magnetic Pulse Compressors (MPC), Pulse Forming Networks (PFN) and Multistage Blumlein Lines (MBL) are currently employed to supply a wide range of applications. Gas/Magnetic switching technologies (such as spark gap and hydrogen thyratron) have conventionally been used as switching devices in pulse modulator structures because of their high voltage ratings and considerably low rising times. However, they also suffer from serious drawbacks such as, their low efficiency, reliability and repetition rate, and also their short life span. Being bulky, heavy and expensive are the other disadvantages associated with these devices. Recently developed solid-state switching technology is an appropriate substitution for these switching devices due to the benefits they bring to the pulse supplies. Besides being compact, efficient, reasonable and reliable, and having a long life span, their high frequency switching skill allows repetitive operation of pulsed power supply. The main concerns in using solid-state transistors are the voltage rating and the rising time of available switches that, in some cases, cannot satisfy the application’s requirements. However, there are several power electronics configurations and techniques that make solid-state utilisation feasible for high voltage pulse generation. Therefore, the design and development of novel methods and topologies with higher efficiency and flexibility for pulsed power generators have been considered as the main scope of this research work. This aim is pursued through several innovative proposals that can be classified under the following two principal objectives. • To innovate and develop novel solid-state based topologies for pulsed power generation • To improve available technologies that have the potential to accommodate solid-state technology by revising, reconfiguring and adjusting their structure and control algorithms. The quest to distinguish novel topologies for a proper pulsed power production was begun with a deep and through review of conventional pulse generators and useful power electronics topologies. As a result of this study, it appears that efficiency and flexibility are the most significant demands of plasma applications that have not been met by state-of-the-art methods. Many solid-state based configurations were considered and simulated in order to evaluate their potential to be utilised in the pulsed power area. Parts of this literature review are documented in Chapter 1 of this thesis. Current source topologies demonstrate valuable advantages in supplying the loads with capacitive characteristics such as plasma applications. To investigate the influence of switching transients associated with solid-state devices on rise time of pulses, simulation based studies have been undertaken. A variable current source is considered to pump different current levels to a capacitive load, and it was evident that dissimilar dv/dts are produced at the output. Thereby, transient effects on pulse rising time are denied regarding the evidence acquired from this examination. A detailed report of this study is given in Chapter 6 of this thesis. This study inspired the design of a solid-state based topology that take advantage of both current and voltage sources. A series of switch-resistor-capacitor units at the output splits the produced voltage to lower levels, so it can be shared by the switches. A smart but complicated switching strategy is also designed to discharge the residual energy after each supply cycle. To prevent reverse power flow and to reduce the complexity of the control algorithm in this system, the resistors in common paths of units are substituted with diode rectifiers (switch-diode-capacitor). This modification not only gives the feasibility of stopping the load supply process to the supplier at any stage (and consequently saving energy), but also enables the converter to operate in a two-stroke mode with asymmetrical capacitors. The components’ determination and exchanging energy calculations are accomplished with respect to application specifications and demands. Both topologies were simply modelled and simulation studies have been carried out with the simplified models. Experimental assessments were also executed on implemented hardware and the approaches verified the initial analysis. Reports on details of both converters are thoroughly discussed in Chapters 2 and 3 of the thesis. Conventional MGs have been recently modified to use solid-state transistors (i.e. Insulated gate bipolar transistors) instead of magnetic/gas switching devices. Resistive insulators previously used in their structures are substituted by diode rectifiers to adjust MGs for a proper voltage sharing. However, despite utilizing solid-state technology in MGs configurations, further design and control amendments can still be made to achieve an improved performance with fewer components. Considering a number of charging techniques, resonant phenomenon is adopted in a proposal to charge the capacitors. In addition to charging the capacitors at twice the input voltage, triggering switches at the moment at which the conducted current through switches is zero significantly reduces the switching losses. Another configuration is also introduced in this research for Marx topology based on commutation circuits that use a current source to charge the capacitors. According to this design, diode-capacitor units, each including two Marx stages, are connected in cascade through solid-state devices and aggregate the voltages across the capacitors to produce a high voltage pulse. The polarity of voltage across one capacitor in each unit is reversed in an intermediate mode by connecting the commutation circuit to the capacitor. The insulation of input side from load side is provided in this topology by disconnecting the load from the current source during the supply process. Furthermore, the number of required fast switching devices in both designs is reduced to half of the number used in a conventional MG; they are replaced with slower switches (such as Thyristors) that need simpler driving modules. In addition, the contributing switches in discharging paths are decreased to half; this decrease leads to a reduction in conduction losses. Associated models are simulated, and hardware tests are performed to verify the validity of proposed topologies. Chapters 4, 5 and 7 of the thesis present all relevant analysis and approaches according to these topologies.

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.

Revealing common attributes of organizational identities using performance measurement systems

Identity is unique, multiple and dynamic. This paper explores common attributes of organisational identities, and examines the role of performance management systems (PMSs) on revealing identity attributes. One of the influential PMSs, the balanced scorecard, is used to illustrate the arguments. A case study of a public-sector organisation suggests that PMSs now place a value on the intangible aspects of organisational life as well as the financial, periodically revealing distinctiveness, relativity, visibility, fluidity and manageability of public-sector identities that sustain their viability. This paper contributes to a multi-disciplinary approach and its practical application, demonstrating an alternative pathway to identity-making using PMSs.

Reduced variance in monozygous twins for multiple MR parameters : implications for disease studies and the genetic basis of brain structure

Twin studies offer the opportunity to determine the relative contribution of genes versus environment in traits of interest. Here, we investigate the extent to which variance in brain structure is reduced in monozygous twins with identical genetic make-up. We investigate whether using twins as compared to a control population reduces variability in a number of common magnetic resonance (MR) structural measures, and we investigate the location of areas under major genetic influences. This is fundamental to understanding the benefit of using twins in studies where structure is the phenotype of interest. Twenty-three pairs of healthy MZ twins were compared to matched control pairs. Volume, T2 and diffusion MR imaging were performed as well as spectroscopy (MRS). Images were compared using (i) global measures of standard deviation and effect size, (ii) voxel-based analysis of similarity and (iii) intra-pair correlation. Global measures indicated a consistent increase in structural similarity in twins. The voxel-based and correlation analyses indicated a widespread pattern of increased similarity in twin pairs, particularly in frontal and temporal regions. The areas of increased similarity were most widespread for the diffusion trace and least widespread for T2. MRS showed consistent reduction in metabolite variation that was significant in the temporal lobe N-acetylaspartate (NAA). This study has shown the distribution and magnitude of reduced variability in brain volume, diffusion, T2 and metabolites in twins. The data suggest that evaluation of twins discordant for disease is indeed a valid way to attribute genetic or environmental influences to observed abnormalities in patients since evidence is provided for the underlying assumption of decreased variability in twins.

Understanding IT business value creation and evaluation in least developed economies

Information Technology (IT) is an important resource that can facilitate growth and development in both the developed and developing economies. The forces of globalisation increase the digital divide between the developed and developing economies is increasing. The least developed economies (LDEs) are the most vulnerable within this environment. Intense competition for IT resources means that LDEs need a deeper understanding of how to source and evaluate their IT-related efforts. This effort puts LDEs in a better position to source funding from various stakeholders and promote localized investment in IT. This study presents a complementary approach to securing better IT-related business value in organizations in the LDEs. It further evaluates how IT and the complementaries need to managed within the LDEs. Analysis of data collected from five LDEs show that organizations that invest in IT and related complementaries are able to better their business processes. The data also suggest that improved business processes lead to overall business processes improvements. The above is only possible if organizations adopt IT and make related changes in the complementary resources within the established culture and localizing the required changes.

Structural damage identification with noise polluted Frequency Response Functions (FRFs)

Damage detection in structures has become increasingly important in recent years. While a number of damage detection and localization methods have been proposed, very few attempts have been made to explore the structure damage with noise polluted data which is unavoidable effect in real world. The measurement data are contaminated by noise because of test environment as well as electronic devices and this noise tend to give error results with structural damage identification methods. Therefore it is important to investigate a method which can perform better with noise polluted data. This paper introduces a new damage index using principal component analysis (PCA) for damage detection of building structures being able to accept noise polluted frequency response functions (FRFs) as input. The FRF data are obtained from the function datagen of MATLAB program which is available on the web site of the IASC-ASCE (International Association for Structural Control– American Society of Civil Engineers) Structural Health Monitoring (SHM) Task Group. The proposed method involves a five-stage process: calculation of FRFs, calculation of damage index values using proposed algorithm, development of the artificial neural networks and introducing damage indices as input parameters and damage detection of the structure. This paper briefly describes the methodology and the results obtained in detecting damage in all six cases of the benchmark study with different noise levels. The proposed method is applied to a benchmark problem sponsored by the IASC-ASCE Task Group on Structural Health Monitoring, which was developed in order to facilitate the comparison of various damage identification methods. The illustrated results show that the PCA-based algorithm is effective for structural health monitoring with noise polluted FRFs which is of common occurrence when dealing with industrial structures.

A hybrid shifting bottleneck procedure algorithm for the parallel-machine job-shop scheduling problem

In practice, parallel-machine job-shop scheduling (PMJSS) is very useful in the development of standard modelling approaches and generic solution techniques for many real-world scheduling problems. In this paper, based on the analysis of structural properties in an extended disjunctive graph model, a hybrid shifting bottleneck procedure (HSBP) algorithm combined with Tabu Search metaheuristic algorithm is developed to deal with the PMJSS problem. The original-version SBP algorithm for the job-shop scheduling (JSS) has been significantly improved to solve the PMJSS problem with four novelties: i) a topological-sequence algorithm is proposed to decompose the PMJSS problem into a set of single-machine scheduling (SMS) and/or parallel-machine scheduling (PMS) subproblems; ii) a modified Carlier algorithm based on the proposed lemmas and the proofs is developed to solve the SMS subproblem; iii) the Jackson rule is extended to solve the PMS subproblem; iv) a Tabu Search metaheuristic algorithm is embedded under the framework of SBP to optimise the JSS and PMJSS cases. The computational experiments show that the proposed HSBP is very efficient in solving the JSS and PMJSS problems.

A fast tabu search algorithm for the group shop scheduling problem

Three types of shop scheduling problems, the flow shop, the job shop and the open shop scheduling problems, have been widely studied in the literature. However, very few articles address the group shop scheduling problem introduced in 1997, which is a general formulation that covers the three above mentioned shop scheduling problems and the mixed shop scheduling problem. In this paper, we apply tabu search to the group shop scheduling problem and evaluate the performance of the algorithm on a set of benchmark problems. The computational results show that our tabu search algorithm is typically more efficient and faster than the other methods proposed in the literature. Furthermore, the proposed tabu search method has found some new best solutions of the benchmark instances.

A comparison of the psychological, social, and legal factors contributing to speeding and drink driving behaviour

Within Australia, motor vehicle injury is the leading cause of hospital admissions and fatalities. Road crash data reveals that among the factors contributing to crashes in Queensland, speed and alcohol continue to be overrepresented. While alcohol is the number one contributing factor to fatal crashes, speeding also contributes to a high proportion of crashes. Research indicates that risky driving is an important contributor to road crashes. However, it has been debated whether all risky driving behaviours are similar enough to be explained by the same combination of factors. Further, road safety authorities have traditionally relied upon deterrence based countermeasures to reduce the incidence of illegal driving behaviours such as speeding and drink driving. However, more recent research has focussed on social factors to explain illegal driving behaviours. The purpose of this research was to examine and compare the psychological, legal, and social factors contributing to two illegal driving behaviours: exceeding the posted speed limit and driving when over the legal blood alcohol concentration (BAC) for the drivers licence type. Complementary theoretical perspectives were chosen to comprehensively examine these two behaviours including Akers’ social learning theory, Stafford and Warr’s expanded deterrence theory, and personality perspectives encompassing alcohol misuse, sensation seeking, and Type-A behaviour pattern. The program of research consisted of two phases: a preliminary pilot study, and the main quantitative phase. The preliminary pilot study was undertaken to inform the development of the quantitative study and to ensure the clarity of the theoretical constructs operationalised in this research. Semi-structured interviews were conducted with 11 Queensland drivers recruited from Queensland Transport Licensing Centres and Queensland University of Technology (QUT). These interviews demonstrated that the majority of participants had engaged in at least one of the behaviours, or knew of someone who had. It was also found among these drivers that the social environment in which both behaviours operated, including family and friends, and the social rewards and punishments associated with the behaviours, are important in their decision making. The main quantitative phase of the research involved a cross-sectional survey of 547 Queensland licensed drivers. The aim of this study was to determine the relationship between speeding and drink driving and whether there were any similarities or differences in the factors that contribute to a driver’s decision to engage in one or the other. A comparison of the participants self-reported speeding and self-reported drink driving behaviour demonstrated that there was a weak positive association between these two behaviours. Further, participants reported engaging in more frequent speeding at both low (i.e., up to 10 kilometres per hour) and high (i.e., 10 kilometres per hour or more) levels, than engaging in drink driving behaviour. It was noted that those who indicated they drove when they may be over the legal limit for their licence type, more frequently exceeded the posted speed limit by 10 kilometres per hour or more than those who complied with the regulatory limits for drink driving. A series of regression analyses were conducted to investigate the factors that predict self-reported speeding, self-reported drink driving, and the preparedness to engage in both behaviours. In relation to self-reported speeding (n = 465), it was found that among the sociodemographic and person-related factors, younger drivers and those who score high on measures of sensation seeking were more likely to report exceeding the posted speed limit. In addition, among the legal and psychosocial factors it was observed that direct exposure to punishment (i.e., being detected by police), direct punishment avoidance (i.e., engaging in an illegal driving behaviour and not being detected by police), personal definitions (i.e., personal orientation or attitudes toward the behaviour), both the normative and behavioural dimensions of differential association (i.e., refers to both the orientation or attitude of their friends and family, as well as the behaviour of these individuals), and anticipated punishments were significant predictors of self-reported speeding. It was interesting to note that associating with significant others who held unfavourable definitions towards speeding (the normative dimension of differential association) and anticipating punishments from others were both significant predictors of a reduction in self-reported speeding. In relation to self-reported drink driving (n = 462), a logistic regression analysis indicated that there were a number of significant predictors which increased the likelihood of whether participants had driven in the last six months when they thought they may have been over the legal alcohol limit. These included: experiences of direct punishment avoidance; having a family member convicted of drink driving; higher levels of Type-A behaviour pattern; greater alcohol misuse (as measured by the AUDIT); and the normative dimension of differential association (i.e., associating with others who held favourable attitudes to drink driving). A final logistic regression analysis examined the predictors of whether the participants reported engaging in both drink driving and speeding versus those who reported engaging in only speeding (the more common of the two behaviours) (n = 465). It was found that experiences of punishment avoidance for speeding decreased the likelihood of engaging in both speeding and drink driving; whereas in the case of drink driving, direct punishment avoidance increased the likelihood of engaging in both behaviours. It was also noted that holding favourable personal definitions toward speeding and drink driving, as well as higher levels of on Type-A behaviour pattern, and greater alcohol misuse significantly increased the likelihood of engaging in both speeding and drink driving. This research has demonstrated that the compliance with the regulatory limits was much higher for drink driving than it was for speeding. It is acknowledged that while speed limits are a fundamental component of speed management practices in Australia, the countermeasures applied to both speeding and drink driving do not appear to elicit the same level of compliance across the driving population. Further, the findings suggest that while the principles underpinning the current regime of deterrence based countermeasures are sound, current enforcement practices are insufficient to force compliance among the driving population, particularly in the case of speeding. Future research should further examine the degree of overlap between speeding and drink driving behaviour and whether punishment avoidance experiences for a specific illegal driving behaviour serve to undermine the deterrent effect of countermeasures aimed at reducing the incidence of another illegal driving behaviour. Furthermore, future work should seek to understand the factors which predict engaging in speeding and drink driving behaviours at the same time. Speeding has shown itself to be a pervasive and persistent behaviour, hence it would be useful to examine why road safety authorities have been successful in convincing the majority of drivers of the dangers of drink driving, but not those associated with speeding. In conclusion, the challenge for road safety practitioners will be to convince drivers that speeding and drink driving are equally risky behaviours, with the ultimate goal to reduce the prevalence of both behaviours.

FPGA implementation of an evolutionary algorithm for autonomous unmanned aerial vehicle on-board path planning

In this paper, a hardware-based path planning architecture for unmanned aerial vehicle (UAV) adaptation is proposed. The architecture aims to provide UAVs with higher autonomy using an application specific evolutionary algorithm (EA) implemented entirely on a field programmable gate array (FPGA) chip. The physical attributes of an FPGA chip, being compact in size and low in power consumption, compliments it to be an ideal platform for UAV applications. The design, which is implemented entirely in hardware, consists of EA modules, population storage resources, and three-dimensional terrain information necessary to the path planning process, subject to constraints accounted for separately via UAV, environment and mission profiles. The architecture has been successfully synthesised for a target Xilinx Virtex-4 FPGA platform with 32% logic slices utilisation. Results obtained from case studies for a small UAV helicopter with environment derived from LIDAR (Light Detection and Ranging) data verify the effectiveness of the proposed FPGA-based path planner, and demonstrate convergence at rates above the typical 10 Hz update frequency of an autopilot system.

Importance of soil ecology in vegetation rehabilitation on a North Stradbroke Island sand mine

Sibelco Australia Limited (SAL), a mineral sand mining operation on North Stradbroke Island, undertakes progressive rehabilitation of mined areas. Initial investigations have found that some areas at SAL’s Yarraman Mine have failed to redevelop towards approved criteria. This study, undertaken in 2010, examined ground cover rehabilitation of different aged plots at the Yarraman Mine to determine if there was a relationship between key soil and vegetation attributes. Vegetation and soil data were collected from five plots rehabilitated in 2003, 2006, 2008, 2009 and 2010, and one unmined plot. Cluster (PATN) analysis revealed that vegetation species composition, species richness and ground cover differed between plots. Principal component analysis (PCA) extracted ten soil attributes that were then correlated with vegetation data. The attributes extracted by PCA, in order of most common variance, were: water content, pH, terrolas depth, elevation, slope angle, leaf litter depth, total organic carbon, and counts of macrofauna, fungi and bacteria. All extracted attributes differed between plots, and all except bacteria correlated with at least one vegetation attribute. Water content and pH correlated most strongly with vegetation cover suggesting an increase in soil moisture and a reduction in pH are required in order to improve vegetation rehabilitation at Yarraman Mine. Further study is recommended to confirm these results using controlled experiments and to test potential solutions, such as organic amendments.

Acceptability of cognitive-behaviour therapy via the Internet for cessation of benzodiazepine use

Introduction and Aims: Long-term use of benzodiazepines remains common, and conveys significant risk. Providing psychological intervention in association with gradual dose reduction increases cessation rates above dose reduction alone, but appropriate psychological support is difficult to obtain. This study was undertaken to assess the outcomes of an uncontrolled case series of an internet-based cognitive-behaviour therapy (I-CBT) for benzodiazepine cessation. Design and Method: Users of benzodiazepines for > 3 months who wanted to reduce or cease benzodiazepines participated in the trial. They completed online assessments and accessed 13 newsletters on managing withdrawal symptoms and developing alternate ways to cope with life events. Therapist assistance was provided by email. Follow-up was at 3 and 6 months and feedback was obtained via comments and emails. Results: Program ratings and emailed comments of the program were positive. Thirty-two people registered for the program and 14 (44%) completed a 6-month follow-up. Of these, 8 (57%) reduced weekly intake by at least half, including 5 (36%) who ceased use. Shorter duration of use and birth outside Australia predicted greater percentage reductions at 3 months, while being partnered and in paid employment predicted reductions at 6 months. Discussion and Conclusion: While results were encouraging, controlled research is required to confirm the efficacy of the program, and engagement of both users and prescribers needs further attention.

Optimal coordination of overcurrent relays in distribution systems with distributed generators based on differential evolution algorithm

Distributed generators (DGs) are defined as generators that are connected to a distribution network. The direction of the power flow and short-circuit current in a network could be changed compared with one without DGs. The conventional protective relay scheme does not meet the requirement in this emerging situation. As the number and capacity of DGs in the distribution network increase, the problem of coordinating protective relays becomes more challenging. Given this background, the protective relay coordination problem in distribution systems is investigated, with directional overcurrent relays taken as an example, and formulated as a mixed integer nonlinear programming problem. A mathematical model describing this problem is first developed, and the well-developed differential evolution algorithm is then used to solve it. Finally, a sample system is used to demonstrate the feasiblity and efficiency of the developed method.

Exploring the contested role of mandatory reporting laws in the identification of severe child abuse and neglect

Significant numbers of children are severely abused and neglected by parents and caregivers. Infants and very young children are the most vulnerable and are unable to seek help. To identify these situations and enable child protection and the provision of appropriate assistance, many jurisdictions have enacted ‘mandatory reporting laws’ requiring designated professionals such as doctors, nurses, police and teachers to report suspected cases of severe child abuse and neglect. Other jurisdictions have not adopted this legislative approach, at least partly motivated by a concern that the laws produce dramatic increases in unwarranted reports, which, it is argued, lead to investigations which infringe on people’s privacy, cause trauma to innocent parents and families, and divert scarce government resources from deserving cases. The primary purpose of this paper is to explore the extent to which opposition to mandatory reporting laws is valid based on the claim that the laws produce ‘overreporting’. The first part of this paper revisits the original mandatory reporting laws, discusses their development into various current forms, explains their relationship with policy and common law reporting obligations, and situates them in the context of their place in modern child protection systems. This part of the paper shows that in general, contemporary reporting laws have expanded far beyond their original conceptualisation, but that there is also now a deeper understanding of the nature, incidence, timing and effects of different types of severe maltreatment, an awareness that the real incidence of maltreatment is far higher than that officially recorded, and that there is strong evidence showing the majority of identified cases of severe maltreatment are the result of reports by mandated reporters. The second part of this paper discusses the apparent effect of mandatory reporting laws on ‘overreporting’ by referring to Australian government data about reporting patterns and outcomes, with a particular focus on New South Wales. It will be seen that raw descriptive data about report numbers and outcomes appear to show that reporting laws produce both desirable consequences (identification of severe cases) and problematic consequences (increased numbers of unsubstantiated reports). Yet, to explore the extent to which the data supports the overreporting claim, and because numbers of unsubstantiated reports alone cannot demonstrate overreporting, this part of the paper asks further questions of the data. Who makes reports, about which maltreatment types, and what are the outcomes of those reports? What is the nature of these reports; for example, to what extent are multiple numbers of reports made about the same child? What meaning can be attached to an ‘unsubstantiated’ report, and can such reports be used to show flaws in reporting effectiveness and problems in reporting laws? It will be suggested that available evidence from Australia is not sufficiently detailed or strong to demonstrate the overreporting claim. However, it is also apparent that, whether adopting an approach based on public health and or other principles, much better evidence about reporting needs to be collected and analyzed. As well, more nuanced research needs to be conducted to identify what can reasonably be said to constitute ‘overreports’, and efforts must be made to minimize unsatisfactory reporting practice, informed by the relevant jurisdiction’s context and aims. It is also concluded that, depending on the jurisdiction, the available data may provide useful indicators of positive, negative and unanticipated effects of specific components of the laws, and of the strengths, weaknesses and needs of the child protection system.

A sequential Monte Carlo algorithm to incorporate model uncertainty in Bayesian sequential design

Here we present a sequential Monte Carlo (SMC) algorithm that can be used for any one-at-a-time Bayesian sequential design problem in the presence of model uncertainty where discrete data are encountered. Our focus is on adaptive design for model discrimination but the methodology is applicable if one has a different design objective such as parameter estimation or prediction. An SMC algorithm is run in parallel for each model and the algorithm relies on a convenient estimator of the evidence of each model which is essentially a function of importance sampling weights. Other methods for this task such as quadrature, often used in design, suffer from the curse of dimensionality. Approximating posterior model probabilities in this way allows us to use model discrimination utility functions derived from information theory that were previously difficult to compute except for conjugate models. A major benefit of the algorithm is that it requires very little problem specific tuning. We demonstrate the methodology on three applications, including discriminating between models for decline in motor neuron numbers in patients suffering from neurological diseases such as Motor Neuron disease.