Dinuclear Ru-Cu complexes : electronic characterisation and application to dye-sensitised solar cells

Dye-sensitised solar cells have emerged as an important developing technology for low-cost solar energy conversion and a crucial element of these is the dye, responsible for light harvesting and control of interfacial electron-transfer processes.[1] A number of examples of dye exist in the literature which link a ruthenium polypyridyl complex to another platinum group metal complex such as Ru (II), Os (II), Re (I) or Rh (III) via a bridging ligand.[2-6] These systems are often referred to as heterosupramolecular triads when adsorbed on the surface of TiO2 as the semiconductor becomes an active component in the system. A number of problems can arise with these types of sensitisers, for example if a flexible linker, e.g. bis-pyridylethane, is used to couple the two complexes it can be hard to control the orientation of the whole dye. This may lead to the resultant dye cation hole being closer to the surface than desired, and hence the long-lived charge-separated state is not achieved. In addition the size of these dyes may be much larger than that of a mononuclear complex and can lead to poor pore filling on the TiO2 and lower dye coverage, leading to a lower efficiency cell.[7] Despite these issues, efficient charge-separation has been achieved with polynuclear complexes and a long-lived state on the millisecond timescale has been observed for a trinuclear ruthenium complex.[8]

Some novel techniques of parameter estimation for the dynamical models in biological systems

Inverse problems based on using experimental data to estimate unknown parameters of a system often arise in biological and chaotic systems. In this paper, we consider parameter estimation in systems biology involving linear and non-linear complex dynamical models, including the Michaelis–Menten enzyme kinetic system, a dynamical model of competence induction in Bacillus subtilis bacteria and a model of feedback bypass in B. subtilis bacteria. We propose some novel techniques for inverse problems. Firstly, we establish an approximation of a non-linear differential algebraic equation that corresponds to the given biological systems. Secondly, we use the Picard contraction mapping, collage methods and numerical integration techniques to convert the parameter estimation into a minimization problem of the parameters. We propose two optimization techniques: a grid approximation method and a modified hybrid Nelder–Mead simplex search and particle swarm optimization (MH-NMSS-PSO) for non-linear parameter estimation. The two techniques are used for parameter estimation in a model of competence induction in B. subtilis bacteria with noisy data. The MH-NMSS-PSO scheme is applied to a dynamical model of competence induction in B. subtilis bacteria based on experimental data and the model for feedback bypass. Numerical results demonstrate the effectiveness of our approach.

Floods, earthquakes and insurance coverage : issues, problems and solutions

The recent floods in Queensland and elsewhere in Australia as well as the recent earthquakes in New Zealand have again given rise to very significant uninsured losses. This article looks at the issue of cover protection against catastrophes such as floods and earthquakes affecting home buildings and contents insurance and the standard cover provisions of the Insurance Contracts Act 1984 (Cth). It points also to the possibility of a national scheme to cover natural disasters including floods.

Exchange design patterns for electronic intermediairies

Intermediaries have introduced electronic services with varying success. One of the problems an intermediary faces is deciding what kind of exchange service it should offer to its customers and suppliers. For example, should it only provide a catalogue or should it also enable customers to order products? Developing the right exchange design is a complex undertaking because of the many design options on the one hand and the interests of multiple actors to be considered on the other. This is far more difficult than simple prescriptions like ‘creating a win-win situation’ suggest. We address this problem by developing design patterns for the exchanges between customers, intermediary, and suppliers related to role, linkage, transparency, and ovelty choices. For developing these design patterns, we studied four distinct electronic intermediaries and dentified exchange design choices that require trade-offs relating to the interests of customers, intermediary, and suppliers. The exchange design patterns contribute to the development of design theory for electronic intermediaries by filling a gap between basic business models and detailed business process designs.

Using complex network metrics to predict the persistence of metapopulations with asymmetric connectivity patterns

Almost all metapopulation modelling assumes that connectivity between patches is only a function of distance, and is therefore symmetric. However, connectivity will not depend only on the distance between the patches, as some paths are easy to traverse, while others are difficult. When colonising organisms interact with the heterogeneous landscape between patches, connectivity patterns will invariably be asymmetric. There have been few attempts to theoretically assess the effects of asymmetric connectivity patterns on the dynamics of metapopulations. In this paper, we use the framework of complex networks to investigate whether metapopulation dynamics can be determined by directly analysing the asymmetric connectivity patterns that link the patches. Our analyses focus on “patch occupancy” metapopulation models, which only consider whether a patch is occupied or not. We propose three easily calculated network metrics: the “asymmetry” and “average path strength” of the connectivity pattern, and the “centrality” of each patch. Together, these metrics can be used to predict the length of time a metapopulation is expected to persist, and the relative contribution of each patch to a metapopulation’s viability. Our results clearly demonstrate the negative effect that asymmetry has on metapopulation persistence. Complex network analyses represent a useful new tool for understanding the dynamics of species existing in fragmented landscapes, particularly those existing in large metapopulations.

Coupling hybrid-game strategies with particle swarm optimisation for multi-objective high lift systems design optimisation

This paper investigates the High Lift System (HLS) application of complex aerodynamic design problem using Particle Swarm Optimisation (PSO) coupled to Game strategies. Two types of optimization methods are used; the first method is a standard PSO based on Pareto dominance and the second method hybridises PSO with a well-known Nash Game strategies named Hybrid-PSO. These optimization techniques are coupled to a pre/post processor GiD providing unstructured meshes during the optimisation procedure and a transonic analysis software PUMI. The computational efficiency and quality design obtained by PSO and Hybrid-PSO are compared. The numerical results for the multi-objective HLS design optimisation clearly shows the benefits of hybridising a PSO with the Nash game and makes promising the above methodology for solving other more complex multi-physics optimisation problems in Aeronautics.

Using participatory action research in a community-based initiative addressing complex mental health needs

Objective: This paper describes the first phase of a larger project that utilizes participatory action research to examine complex mental health needs across an extensive group of stakeholders in the community. Method: Within an objective qualitative analysis of focus group discussions the social ecological model is utilized to explore how integrative activities can be informed, planned and implemented across multiple elements and levels of a system. Seventy-one primary care workers, managers, policy-makers, consumers and carers from across the southern metropolitan and Gippsland regions of Victoria, Australia took part in seven focus groups. All groups responded to an identical set of focusing questions. Results: Participants produced an explanatory model describing the service system, as it relates to people with complex needs, across the levels of social ecological analysis. Qualitative themes analysis identified four priority areas to be addressed in order to improve the system's capacity for working with complexity. These included: (i) system fragmentation; (ii) integrative case management practices; (iii) community attitudes; and (iv) money and resources. Conclusions: The emergent themes provide clues as to how complexity is constructed and interpreted across the system of involved agencies and interest groups. The implications these findings have for the development and evaluation of this community capacity-building project were examined from the perspective of constructing interventions that address both top-down and bottom-up processes.

Development of a performance model for international construction joint venture : a system dynamics approach

The uncertain and dynamic nature of International Construction Joint Venture (ICJV) performance is evolved with many critical factors which lead to make partner relationships more complex in respect of making decisions to maintain a cohesive environment. Addressing to the fact, a generic system dynamics performance model for ICJV is developed by integrating a number variables as to get an overall impact on performance of ICJV and to make effective decisions based on that. In order to formulate and validate the model both structurally and behaviourally, both qualitative and quantitative data are gathered by conducting intensive interviews from two ICJVs in Thailand. After conducting intensive simulations of model, three major problems are identified related to negative value gap, low productivity in construction and high rate of ineffective information sharing of both ICJVs. Several policies are suggested and integrated application of these policies provides a maximum improvement to performance of the ICJV.

Year 7 students’ approaches to understanding and solving NAPLAN numeracy problems

This study investigated how the interpretation of mathematical problems by Year 7 students impacted on their ability to demonstrate what they can do in NAPLAN numeracy testing. In the study, mathematics is viewed as a culturally and socially determined system of signs and signifiers that establish the meaning, origins and importance of mathematics. The study hypothesises that students are unable to succeed in NAPLAN numeracy tests because they cannot interpret the questions, even though they may be able to perform the necessary calculations. To investigate this, the study applied contemporary theories of literacy to the context of mathematical problem solving. A case study design with multiple methods was used. The study used a correlation design to explore the connections between NAPLAN literacy and numeracy outcomes of 198 Year 7 students in a Queensland school. Additionally, qualitative methods provided a rich description of the effect of the various forms of NAPLAN numeracy questions on the success of ten Year 7 students in the same school. The study argues that there is a quantitative link between reading and numeracy. It illustrates that interpretation (literacy) errors are the most common error type in the selected NAPLAN questions, made by students of all abilities. In contrast, conceptual (mathematical) errors are less frequent amongst more capable students. This has important implications in preparing students for NAPLAN numeracy tests. The study concluded by recommending that increased focus on the literacies of mathematics would be effective in improving NAPLAN results.

QoS-aware web service composition using genetic algorithms

Web service technology is increasingly being used to build various e-Applications, in domains such as e-Business and e-Science. Characteristic benefits of web service technology are its inter-operability, decoupling and just-in-time integration. Using web service technology, an e-Application can be implemented by web service composition — by composing existing individual web services in accordance with the business process of the application. This means the application is provided to customers in the form of a value-added composite web service. An important and challenging issue of web service composition, is how to meet Quality-of-Service (QoS) requirements. This includes customer focused elements such as response time, price, throughput and reliability as well as how to best provide QoS results for the composites. This in turn best fulfils customers’ expectations and achieves their satisfaction. Fulfilling these QoS requirements or addressing the QoS-aware web service composition problem is the focus of this project. From a computational point of view, QoS-aware web service composition can be transformed into diverse optimisation problems. These problems are characterised as complex, large-scale, highly constrained and multi-objective problems. We therefore use genetic algorithms (GAs) to address QoS-based service composition problems. More precisely, this study addresses three important subproblems of QoS-aware web service composition; QoS-based web service selection for a composite web service accommodating constraints on inter-service dependence and conflict, QoS-based resource allocation and scheduling for multiple composite services on hybrid clouds, and performance-driven composite service partitioning for decentralised execution. Based on operations research theory, we model the three problems as a constrained optimisation problem, a resource allocation and scheduling problem, and a graph partitioning problem, respectively. Then, we present novel GAs to address these problems. We also conduct experiments to evaluate the performance of the new GAs. Finally, verification experiments are performed to show the correctness of the GAs. The major outcomes from the first problem are three novel GAs: a penaltybased GA, a min-conflict hill-climbing repairing GA, and a hybrid GA. These GAs adopt different constraint handling strategies to handle constraints on interservice dependence and conflict. This is an important factor that has been largely ignored by existing algorithms that might lead to the generation of infeasible composite services. Experimental results demonstrate the effectiveness of our GAs for handling the QoS-based web service selection problem with constraints on inter-service dependence and conflict, as well as their better scalability than the existing integer programming-based method for large scale web service selection problems. The major outcomes from the second problem has resulted in two GAs; a random-key GA and a cooperative coevolutionary GA (CCGA). Experiments demonstrate the good scalability of the two algorithms. In particular, the CCGA scales well as the number of composite services involved in a problem increases, while no other algorithms demonstrate this ability. The findings from the third problem result in a novel GA for composite service partitioning for decentralised execution. Compared with existing heuristic algorithms, the new GA is more suitable for a large-scale composite web service program partitioning problems. In addition, the GA outperforms existing heuristic algorithms, generating a better deployment topology for a composite web service for decentralised execution. These effective and scalable GAs can be integrated into QoS-based management tools to facilitate the delivery of feasible, reliable and high quality composite web services.

The contribution of leadership attributes to large scale, complex project success

Mismanagement of large-scale, complex projects has resulted in spectacular failures, cost overruns, time blowouts, and stakeholder dissatisfaction. We focus discussion on the interaction of key management and leadership attributes which facilitate leaders’ adaptive behaviors. These behaviors should in turn influence adaptive team member behavior, stakeholder engagement and successful project outcomes, outputs and impacts. An understanding of this type of management will benefit from a perspective based in managerial and organizational cognition. The research question we explore is whether successful leaders of large-scale complex projects have an internal process leading to a display of administrative, adaptive, and enabling behaviors that foster adaptive processes and enabling behaviors within their teams and with external stakeholders. At the core of the model we propose interactions of key attributes, namely cognitive flexibility, affect, and emotional intelligence. The result of these cognitive-affective attribute interactions is leadership leading to enhanced likelihood of complex project success.