Cryptic diversity and evolutionary relationships among Australian closed-forest Melomys (Rodentia: Muridae) and related Australo-Papuan mosaic-tailed rats

This thesis investigates patterns of evolution in a group of native Australo-Papuan rodents. Past climatic change and associated sea level fluctuations, and fragmentation of wet forests in eastern Australia has facilitated rapid radiation, diversification and speciation in this group. This study adds to our understanding of the evolution of Australia’s rainforest fauna and describes the evolutionary relationships of a new genus of Australian rodent.

Evolutionary genetics and human assisted movement of a globally invasive pest (Russian wheat aphid : Diuraphis noxia)

This PhD study has examined the population genetics of the Russian wheat aphid (RWA, Diuraphis noxia), one of the world’s most invasive agricultural pests, throughout its native and introduced global range. Firstly, this study investigated the geographic distribution of genetic diversity within and among RWA populations in western China. Analysis of mitochondrial data from 18 sites provided evidence for the long-term existence and expansion of RWAs in western China. The results refute the hypothesis that RWA is an exotic species only present in China since 1975. The estimated date of RWA expansion throughout western China coincides with the debut of wheat domestication and cultivation practices in western Asia in the Holocene. It is concluded that western China represents the limit of the far eastern native range of this species. Analysis of microsatellite data indicated high contemporary gene flow among northern populations in western China, while clear geographic isolation between northern and southern populations was identified across the Tianshan mountain range and extensive desert regions. Secondly, this study analyzed the worldwide pathway of invasion using both microsatellite and endosymbiont genetic data. Individual RWAs were obtained from native populations in Central Asia and the Middle East and invasive populations in Africa and the Americas. Results indicated two pathways of RWA invasion from 1) Syria in the Middle East to North Africa and 2) Turkey to South Africa, Mexico and then North and South America. Very little clone diversity was identified among invasive populations suggesting that a limited founder event occurred together with predominantly asexual reproduction and rapid population expansion. The most likely explanation for the rapid spread (within two years) from South Africa to the New World is by human movement, probably as a result of the transfer of wheat breeding material. Furthermore, the mitochondrial data revealed the presence of a universal haplotype and it is proposed that this haplotype is representative of a wheat associated super-clone that has gained dominance worldwide as a result of the widespread planting of domesticated wheat. Finally, this study examined salivary gland gene diversity to determine whether a functional basis for RWA invasiveness could be identified. Peroxidase DNA sequence data were obtained for a selection of worldwide RWA samples. Results demonstrated that most native populations were polymorphic while invasive populations were monomorphic, supporting previous conclusions relating to demographic founder effects in invasive populations. Purifying selection most likely explains the existence of a universal allele present in Middle Eastern populations, while balancing selection was evident in East Asian populations. Selection acting on the peroxidase gene may provide an allele-dependent advantage linked to the successful establishment of RWAs on wheat, and ultimately their invasion potential. In conclusion, this study is the most comprehensive molecular genetic investigation of RWA population genetics undertaken to date and provides significant insights into the source and pathway of global invasion and the potential existence of a wheat-adapted genotype that has colonised major wheat growing countries worldwide except for Australia. This research has major biosecurity implications for Australia’s grain industry.

Enhancing critical analysis and problem-solving skills in undergraduate psychology : An evaluation of a collaborative learning and problem-based learning approach

Critical analysis and problem-solving skills are two graduate attributes that are important in ensuring that graduates are well equipped in working across research and practice settings within the discipline of psychology. Despite the importance of these skills, few psychology undergraduate programmes have undertaken any systematic development, implementation, and evaluation of curriculum activities to foster these graduate skills. The current study reports on the development and implementation of a tutorial programme designed to enhance the critical analysis and problem-solving skills of undergraduate psychology students. Underpinned by collaborative learning and problem-based learning, the tutorial programme was administered to 273 third year undergraduate students in psychology. Latent Growth Curve Modelling revealed that students demonstrated a significant linear increase in self-reported critical analysis and problem-solving skills across the tutorial programme. The findings suggest that the development of inquiry-based curriculum offers important opportunities for psychology undergraduates to develop critical analysis and problem-solving skills.

Place psychology: Engaging with notions of 'home'

Psychology of place is theoretical territory shared by a wide range of disciplines. Currently, while environmental psychology addresses such questions as how people interact with and make meaning in places, clinical psychology has paid scant attention to the role of place in mental health. This paper focuses on two concepts from place psychology - place attachment and place identity. Place attachment is here defined as a sense of positively-valanced emotional connection to a familiar place (Morgan 2010). Place identity implies a stronger sense of belonging: the person as part of the place and the place as part of the person (Memmot & Long 2002). Both place attachment and place identity can be seen as relating to notions of ‘home’. My PhD is a work of interdisciplinary practice-based research using creative writing as a methodology to explore how place attachment, place identity and notions of home may support recovery from psychological trauma. A novel provides a site of imaginative encounter between author and reader, in which the two parties collaboratively create place and character through the medium of language. This paper links theory with practice by outlining some choices involved in exploring psychological constructs through narrative fiction.

A commentary on the current and future status of educational and developmental psychology in Australia

Educational and developmental psychology faces a number of current and future challenges and opportunities in Australia. In this commentary we consider the identity of educational and developmental psychology in terms of the features that distinguish it from other specialisations, and address issues related to training, specialist endorsement, supervision and rebating under the Australian government's Medicare system. The current status of training in Australia is considered through a review of the four university programs in educational and developmental psychology currently offered, and the employment destinations of their graduates. Although the need for traditional services in settings such as schools, hospitals, disability and community organisations will undoubtedly continue, the role of educational and developmental psychologists is being influenced and to some extent redefined by advances in technology, medicine, genetics, and neuroscience. We review some of these advances and conclude with recommendations for training and professional development that will enable Australian educational and developmental psychologists to meet the challenges ahead.

The linking of plate tectonics and evolutionary divergence

It is exciting to be living at a time when the big questions in biology can be investigated using modern genetics and computing [1]. Bauzà-Ribot et al.[2] take on one of the fundamental drivers of biodiversity, the effect of continental drift in the formation of the world’s biota 3 and 4, employing next-generation sequencing of whole mitochondrial genomes and modern Bayesian relaxed molecular clock analysis. Bauzà-Ribot et al.[2] conclude that vicariance via plate tectonics best explains the genetic divergence between subterranean metacrangonyctid amphipods currently found on islands separated by the Atlantic Ocean. This finding is a big deal in biogeography, and science generally [3], as many other presumed biotic tectonic divergences have been explained as probably due to more recent transoceanic dispersal events [4]. However, molecular clocks can be problematic 5 and 6 and we have identified three issues with the analyses of Bauzà-Ribot et al.[2] that cast serious doubt on their results and conclusions. When we reanalyzed their mitochondrial data and attempted to account for problems with calibration 5 and 6, modeling rates across branches 5 and 7 and substitution saturation [5], we inferred a much younger date for their key node. This implies either a later trans-Atlantic dispersal of these crustaceans, or more likely a series of later invasions of freshwaters from a common marine ancestor, but either way probably not ancient tectonic plate movements.

Pragmatism and precision : psychology in the service of civil litigation

While forensic psychology is commonly associated with the criminal and family law domains, its ambit to offer skills and knowledge at the legal interface also makes it particularly suited to the civil law domain. At this time, civil law is arguably the least represented legislative area in terms of psychological research and professional commentary. However, it is also a broad area, with its very breadth providing scope for research consideration, as urged by Greene. The purposes of this article are (1) to review the broad role of the psychologist in the conduct of civil litigation matters in Australia, (2) to assist the novice to the area by indicating a non-exhaustive list of potentially ambiguous terms and concepts common to the conduct of professional practice, and; (3) to highlight, as an example, one area of practice not only where legal direction demands professional pragmatism but also where opportunity arises for psychological research to vitally address a major social issue.

Towards a model for student selection in clinical psychology

Background Selection of candidates for clinical psychology programmes is arguably the most important decision made in determining the clinical psychology workforce. However, there are few models to inform the development of selection tools to support selection procedures. The study, using a factor analytic structure, has operationalised the model predicting applicants' capabilities. Method Eighty-eight clinical applicants for entry into a postgraduate clinical psychology programme were assessed on a series of tasks measuring eight capabilities: guided reflection, communication skills, ethical decision making, writing, conceptual reasoning, empathy, and awareness of mind and self-observation. Results Factor analysis revealed three capabilities: labelled “awareness” accounting for 35.71% of variance; “reflection” accounting for 20.56%; and “reasoning” accounting for 18.24% of variance. Fourth year grade point average (GPA) did not correlate with performance on any of the selection capabilities other than a weak correlation with performance on the ethics capability. Conclusions Eight selection capabilities are identified for the selection of candidates independent of GPA. While the model is tentative, it is hoped that the findings will stimulate the development and validation of assessment procedures with good predictive validity which will benefit the training of clinical psychologists and, ultimately, effective service delivery.

Composite SaaS resource management in cloud computing using evolutionary computation

Cloud computing is an emerging computing paradigm in which IT resources are provided over the Internet as a service to users. One such service offered through the Cloud is Software as a Service or SaaS. SaaS can be delivered in a composite form, consisting of a set of application and data components that work together to deliver higher-level functional software. SaaS is receiving substantial attention today from both software providers and users. It is also predicted to has positive future markets by analyst firms. This raises new challenges for SaaS providers managing SaaS, especially in large-scale data centres like Cloud. One of the challenges is providing management of Cloud resources for SaaS which guarantees maintaining SaaS performance while optimising resources use. Extensive research on the resource optimisation of Cloud service has not yet addressed the challenges of managing resources for composite SaaS. This research addresses this gap by focusing on three new problems of composite SaaS: placement, clustering and scalability. The overall aim is to develop efficient and scalable mechanisms that facilitate the delivery of high performance composite SaaS for users while optimising the resources used. All three problems are characterised as highly constrained, large-scaled and complex combinatorial optimisation problems. Therefore, evolutionary algorithms are adopted as the main technique in solving these problems. The first research problem refers to how a composite SaaS is placed onto Cloud servers to optimise its performance while satisfying the SaaS resource and response time constraints. Existing research on this problem often ignores the dependencies between components and considers placement of a homogenous type of component only. A precise problem formulation of composite SaaS placement problem is presented. A classical genetic algorithm and two versions of cooperative co-evolutionary algorithms are designed to now manage the placement of heterogeneous types of SaaS components together with their dependencies, requirements and constraints. Experimental results demonstrate the efficiency and scalability of these new algorithms. In the second problem, SaaS components are assumed to be already running on Cloud virtual machines (VMs). However, due to the environment of a Cloud, the current placement may need to be modified. Existing techniques focused mostly at the infrastructure level instead of the application level. This research addressed the problem at the application level by clustering suitable components to VMs to optimise the resource used and to maintain the SaaS performance. Two versions of grouping genetic algorithms (GGAs) are designed to cater for the structural group of a composite SaaS. The first GGA used a repair-based method while the second used a penalty-based method to handle the problem constraints. The experimental results confirmed that the GGAs always produced a better reconfiguration placement plan compared with a common heuristic for clustering problems. The third research problem deals with the replication or deletion of SaaS instances in coping with the SaaS workload. To determine a scaling plan that can minimise the resource used and maintain the SaaS performance is a critical task. Additionally, the problem consists of constraints and interdependency between components, making solutions even more difficult to find. A hybrid genetic algorithm (HGA) was developed to solve this problem by exploring the problem search space through its genetic operators and fitness function to determine the SaaS scaling plan. The HGA also uses the problem's domain knowledge to ensure that the solutions meet the problem's constraints and achieve its objectives. The experimental results demonstrated that the HGA constantly outperform a heuristic algorithm by achieving a low-cost scaling and placement plan. This research has identified three significant new problems for composite SaaS in Cloud. Various types of evolutionary algorithms have also been developed in addressing the problems where these contribute to the evolutionary computation field. The algorithms provide solutions for efficient resource management of composite SaaS in Cloud that resulted to a low total cost of ownership for users while guaranteeing the SaaS performance.

Representations for evolutionary design modelling

This research looked at using the metaphor of biological evolution as a way of solving architectural design problems. Drawing from fields such as language grammars, algorithms and cellular biology, this thesis looked at ways of encoding design information for processing. The aim of this work is to help in the building of software that support the architectural design process and allow designers to examine more variations.

An efficient hybrid evolutionary optimization algorithm based on PSO and SA for clustering

The K-means algorithm is one of the most popular techniques in clustering. Nevertheless, the performance of the K-means algorithm depends highly on initial cluster centers and converges to local minima. This paper proposes a hybrid evolutionary programming based clustering algorithm, called PSO-SA, by combining particle swarm optimization (PSO) and simulated annealing (SA). The basic idea is to search around the global solution by SA and to increase the information exchange among particles using a mutation operator to escape local optima. Three datasets, Iris, Wisconsin Breast Cancer, and Ripley’s Glass, have been considered to show the effectiveness of the proposed clustering algorithm in providing optimal clusters. The simulation results show that the PSO-SA clustering algorithm not only has a better response but also converges more quickly than the K-means, PSO, and SA algorithms.

An efficient hybrid evolutionary optimization algorithm for daily volt/var control at distribution system including DGs

This paper presents a new hybrid evolutionary algorithm based on Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) for daily Volt/Var control in distribution system including Distributed Generators (DGs). Due to the small X/R ratio and radial configuration of distribution systems, DGs have much impact on this problem. Since DGs are independent power producers or private ownership, a price based methodology is proposed as a proper signal to encourage owners of DGs in active power generation. Generally, the daily Volt/Var control is a nonlinear optimization problem. Therefore, an efficient hybrid evolutionary method based on Particle Swarm Optimization and Ant Colony Optimization (ACO), called HPSO, is proposed to determine the active power values of DGs, reactive power values of capacitors and tap positions of transformers for the next day. The feasibility of the proposed algorithm is demonstrated and compared with methods based on the original PSO, ACO and GA algorithms on IEEE 34-bus distribution feeder.

A novel hybrid evolutionary algorithm based on ACO and SA for distribution feeder reconfiguration with regard to DGs

This paper presents an efficient hybrid evolutionary optimization algorithm based on combining Ant Colony Optimization (ACO) and Simulated Annealing (SA), called ACO-SA, for distribution feeder reconfiguration (DFR) considering Distributed Generators (DGs). Due to private ownership of DGs, a cost based compensation method is used to encourage DGs in active and reactive power generation. The objective function is summation of electrical energy generated by DGs and substation bus (main bus) in the next day. The approach is tested on a real distribution feeder. The simulation results show that the proposed evolutionary optimization algorithm is robust and suitable for solving DFR problem.