A new geological model of Cenozoic New Zealand suggests a complex phylogeographic history for New Zealand terrestrial taxa

The new model of North Island Cenozoic palaeogeography developed by Kamp et al. has a range of important implications for the evolution of New Zealand terrestrial taxa over the past 30 Ma. Key aspects include the prolonged isolation of the biota on the North Island landmass from the larger and more diverse greater South Island, and the founding of North Island taxa from the potentially unusual ecosystem of a small island around Northland. The prolonged period of isolation is expected to have generated deep phylogenetic splits within taxa present on both islands, and an important current aim should be to identify such signals in surviving endemics to start building a picture of the historical phylogeography, and inferred ecology of both islands through the Cenozoic. Given the potential differences in founding terrestrial species and climatic conditions, it seems likely that the ecology may have been very diferent between the North and South Islands. New genetic data from the 10 or so species of extinct moa suggest that the radiation of moa was much more recent than previously suggested, and reveals a complex pattern that is inferred to result from the interplay of the Cenozoic biogeography, marine barriers, and glacial cycles.

Assessment of flood-related recharge to alluvial aquifers of an irrigated catchment following extended drought conditions using 3D visualisation and environmental tracers, Lockyer Valley, southeast Queensland, Australia.

The Lockyer Valley in southeast Queensland, Australia, hosts an economically significant alluvial aquifer system which has been impacted by prolonged drought conditions (~1997 to ~ 2009). Throughout this time, the system was under continued groundwater extraction, resulting in severe aquifer depletion. By 2008, much of the aquifer was at <30% of storage but some relief occurred with rains in early 2009. However, between December 2010 and January 2011, most of southeast Queensland experienced unprecedented flooding, which generated significant aquifer recharge. In order to understand the spatial and temporal controls of groundwater recharge in the alluvium, a detailed 3D lithological property model of gravels, sands and clays was developed using GOCAD software. The spatial distribution of recharge throughout the catchment was assessed using hydrograph data from about 400 groundwater observation wells screened at the base of the alluvium. Water levels from these bores were integrated into a catchment-wide 3D geological model using the 3D geological modelling software GOCAD; the model highlights the complexity of recharge mechanisms. To support this analysis, groundwater tracers (e.g. major and minor ions, stable isotopes, 3H and 14C) were used as independent verification. The use of these complementary methods has allowed the identification of zones where alluvial recharge primarily occurs from stream water during episodic flood events. However, the study also demonstrates that in some sections of the alluvium, rainfall recharge and discharge from the underlying basement into the alluvium are the primary recharge mechanisms of the alluvium. This is indicated by the absence of any response to the flood, as well as the observed old radiocarbon ages and distinct basement water chemistry signatures at these locations. Within the 3D geological model, integration of water chemistry and time-series displays of water level surfaces before and after the flood suggests that the spatial variations of the flood response in the alluvium are primarily controlled by the valley morphology and lithological variations within the alluvium. The integration of time-series of groundwater level surfaces in the 3D geological model also enables the quantification of the volumetric change of groundwater stored in the unconfined sections of this alluvial aquifer during drought and following flood events. The 3D representation and analysis of hydraulic and recharge information has considerable advantages over the traditional 2D approach. For example, while many studies focus on singular aspects of catchment dynamics and groundwater-surface water interactions, the 3D approach is capable of integrating multiple types of information (topography, geological, hydraulic, water chemistry and spatial) into a single representation which provides valuable insights into the major factors controlling aquifer processes.

Bending and blurring blended learning boundaries [Extended Abstract]

This presentation presents a blended learning model that provides greater opportunity for learning to be self-managed and personalized.

How to design extended finite state machine test models in Java

This chapter is a tutorial that teaches you how to design extended finite state machine (EFSM) test models for a system that you want to test. EFSM models are more powerful and expressive than simple finite state machine (FSM) models, and are one of the most commonly used styles of models for model-based testing, especially for embedded systems. There are many languages and notations in use for writing EFSM models, but in this tutorial we write our EFSM models in the familiar Java programming language. To generate tests from these EFSM models we use ModelJUnit, which is an open-source tool that supports several stochastic test generation algorithms, and we also show how to write your own model-based testing tool. We show how EFSM models can be used for unit testing and system testing of embedded systems, and for offline testing as well as online testing.

Application of clustering technique to generating capacity state model for reliability evaluation

Capacity probability models of generating units are commonly used in many power system reliability studies, at hierarchical level one (HLI). Analytical modelling of a generating system with many units or generating units with many derated states in a system, can result in an extensive number of states in the capacity model. Limitations on available memory and computational time of present computer facilities can pose difficulties for assessment of such systems in many studies. A cluster procedure using the nearest centroid sorting method was used for IEEE-RTS load model. The application proved to be very effective in producing a highly similar model with substantially fewer states. This paper presents an extended application of the clustering method to include capacity probability representation. A series of sensitivity studies are illustrated using IEEE-RTS generating system and load models. The loss of load and energy expectations (LOLE, LOEE), are used as indicators to evaluate the application

Asset health prediction using the explicit hazard model

The ability to estimate the asset reliability and the probability of failure is critical to reducing maintenance costs, operation downtime, and safety hazards. Predicting the survival time and the probability of failure in future time is an indispensable requirement in prognostics and asset health management. In traditional reliability models, the lifetime of an asset is estimated using failure event data, alone; however, statistically sufficient failure event data are often difficult to attain in real-life situations due to poor data management, effective preventive maintenance, and the small population of identical assets in use. Condition indicators and operating environment indicators are two types of covariate data that are normally obtained in addition to failure event and suspended data. These data contain significant information about the state and health of an asset. Condition indicators reflect the level of degradation of assets while operating environment indicators accelerate or decelerate the lifetime of assets. When these data are available, an alternative approach to the traditional reliability analysis is the modelling of condition indicators and operating environment indicators and their failure-generating mechanisms using a covariate-based hazard model. The literature review indicates that a number of covariate-based hazard models have been developed. All of these existing covariate-based hazard models were developed based on the principle theory of the Proportional Hazard Model (PHM). However, most of these models have not attracted much attention in the field of machinery prognostics. Moreover, due to the prominence of PHM, attempts at developing alternative models, to some extent, have been stifled, although a number of alternative models to PHM have been suggested. The existing covariate-based hazard models neglect to fully utilise three types of asset health information (including failure event data (i.e. observed and/or suspended), condition data, and operating environment data) into a model to have more effective hazard and reliability predictions. In addition, current research shows that condition indicators and operating environment indicators have different characteristics and they are non-homogeneous covariate data. Condition indicators act as response variables (or dependent variables) whereas operating environment indicators act as explanatory variables (or independent variables). However, these non-homogenous covariate data were modelled in the same way for hazard prediction in the existing covariate-based hazard models. The related and yet more imperative question is how both of these indicators should be effectively modelled and integrated into the covariate-based hazard model. This work presents a new approach for addressing the aforementioned challenges. The new covariate-based hazard model, which termed as Explicit Hazard Model (EHM), explicitly and effectively incorporates all three available asset health information into the modelling of hazard and reliability predictions and also drives the relationship between actual asset health and condition measurements as well as operating environment measurements. The theoretical development of the model and its parameter estimation method are demonstrated in this work. EHM assumes that the baseline hazard is a function of the both time and condition indicators. Condition indicators provide information about the health condition of an asset; therefore they update and reform the baseline hazard of EHM according to the health state of asset at given time t. Some examples of condition indicators are the vibration of rotating machinery, the level of metal particles in engine oil analysis, and wear in a component, to name but a few. Operating environment indicators in this model are failure accelerators and/or decelerators that are included in the covariate function of EHM and may increase or decrease the value of the hazard from the baseline hazard. These indicators caused by the environment in which an asset operates, and that have not been explicitly identified by the condition indicators (e.g. Loads, environmental stresses, and other dynamically changing environment factors). While the effects of operating environment indicators could be nought in EHM; condition indicators could emerge because these indicators are observed and measured as long as an asset is operational and survived. EHM has several advantages over the existing covariate-based hazard models. One is this model utilises three different sources of asset health data (i.e. population characteristics, condition indicators, and operating environment indicators) to effectively predict hazard and reliability. Another is that EHM explicitly investigates the relationship between condition and operating environment indicators associated with the hazard of an asset. Furthermore, the proportionality assumption, which most of the covariate-based hazard models suffer from it, does not exist in EHM. According to the sample size of failure/suspension times, EHM is extended into two forms: semi-parametric and non-parametric. The semi-parametric EHM assumes a specified lifetime distribution (i.e. Weibull distribution) in the form of the baseline hazard. However, for more industry applications, due to sparse failure event data of assets, the analysis of such data often involves complex distributional shapes about which little is known. Therefore, to avoid the restrictive assumption of the semi-parametric EHM about assuming a specified lifetime distribution for failure event histories, the non-parametric EHM, which is a distribution free model, has been developed. The development of EHM into two forms is another merit of the model. A case study was conducted using laboratory experiment data to validate the practicality of the both semi-parametric and non-parametric EHMs. The performance of the newly-developed models is appraised using the comparison amongst the estimated results of these models and the other existing covariate-based hazard models. The comparison results demonstrated that both the semi-parametric and non-parametric EHMs outperform the existing covariate-based hazard models. Future research directions regarding to the new parameter estimation method in the case of time-dependent effects of covariates and missing data, application of EHM in both repairable and non-repairable systems using field data, and a decision support model in which linked to the estimated reliability results, are also identified.

Extending and validating the is-impact model in Saudi Arabia : accounting for computer network quality

Organizations from every industry sector seek to enhance their business performance and competitiveness through the deployment of contemporary information systems (IS), such as Enterprise Systems (ERP). Investments in ERP are complex and costly, attracting scrutiny and pressure to justify their cost. Thus, IS researchers highlight the need for systematic evaluation of information system success, or impact, which has resulted in the introduction of varied models for evaluating information systems. One of these systematic measurement approaches is the IS-Impact Model introduced by a team of researchers at Queensland University of technology (QUT) (Gable, Sedera, & Chan, 2008). The IS-Impact Model is conceptualized as a formative, multidimensional index that consists of four dimensions. Gable et al. (2008) define IS-Impact as "a measure at a point in time, of the stream of net benefits from the IS, to date and anticipated, as perceived by all key-user-groups" (p.381). The IT Evaluation Research Program (ITE-Program) at QUT has grown the IS-Impact Research Track with the central goal of conducting further studies to enhance and extend the IS-Impact Model. The overall goal of the IS-Impact research track at QUT is "to develop the most widely employed model for benchmarking information systems in organizations for the joint benefit of both research and practice" (Gable, 2009). In order to achieve that, the IS-Impact research track advocates programmatic research having the principles of tenacity, holism, and generalizability through extension research strategies. This study was conducted within the IS-Impact Research Track, to further generalize the IS-Impact Model by extending it to the Saudi Arabian context. According to Hofsted (2012), the national culture of Saudi Arabia is significantly different from the Australian national culture making the Saudi Arabian culture an interesting context for testing the external validity of the IS-Impact Model. The study re-visits the IS-Impact Model from the ground up. Rather than assume the existing instrument is valid in the new context, or simply assess its validity through quantitative data collection, the study takes a qualitative, inductive approach to re-assessing the necessity and completeness of existing dimensions and measures. This is done in two phases: Exploratory Phase and Confirmatory Phase. The exploratory phase addresses the first research question of the study "Is the IS-Impact Model complete and able to capture the impact of information systems in Saudi Arabian Organization?". The content analysis, used to analyze the Identification Survey data, indicated that 2 of the 37 measures of the IS-Impact Model are not applicable for the Saudi Arabian Context. Moreover, no new measures or dimensions were identified, evidencing the completeness and content validity of the IS-Impact Model. In addition, the Identification Survey data suggested several concepts related to IS-Impact, the most prominent of which was "Computer Network Quality" (CNQ). The literature supported the existence of a theoretical link between IS-Impact and CNQ (CNQ is viewed as an antecedent of IS-Impact). With the primary goal of validating the IS-Impact model within its extended nomological network, CNQ was introduced to the research model. The Confirmatory Phase addresses the second research question of the study "Is the Extended IS-Impact Model Valid as a Hierarchical Multidimensional Formative Measurement Model?". The objective of the Confirmatory Phase was to test the validity of IS-Impact Model and CNQ Model. To achieve that, IS-Impact, CNQ, and IS-Satisfaction were operationalized in a survey instrument, and then the research model was assessed by employing the Partial Least Squares (PLS) approach. The CNQ model was validated as a formative model. Similarly, the IS-Impact Model was validated as a hierarchical multidimensional formative construct. However, the analysis indicated that one of the IS-Impact Model indicators was insignificant and can be removed from the model. Thus, the resulting Extended IS-Impact Model consists of 4 dimensions and 34 measures. Finally, the structural model was also assessed against two aspects: explanatory and predictive power. The analysis revealed that the path coefficient between CNQ and IS-Impact is significant with t-value= (4.826) and relatively strong with â = (0.426) with CNQ explaining 18% of the variance in IS-Impact. These results supported the hypothesis that CNQ is antecedent of IS-Impact. The study demonstrates that the quality of Computer Network affects the quality of the Enterprise System (ERP) and consequently the impacts of the system. Therefore, practitioners should pay attention to the Computer Network quality. Similarly, the path coefficient between IS-Impact and IS-Satisfaction was significant t-value = (17.79) and strong â = (0.744), with IS-Impact alone explaining 55% of the variance in Satisfaction, consistent with results of the original IS-Impact study (Gable et al., 2008). The research contributions include: (a) supporting the completeness and validity of IS-Impact Model as a Hierarchical Multi-dimensional Formative Measurement Model in the Saudi Arabian context, (b) operationalizing Computer Network Quality as conceptualized in the ITU-T Recommendation E.800 (ITU-T, 1993), (c) validating CNQ as a formative measurement model and as an antecedent of IS Impact, and (d) conceptualizing and validating IS-Satisfaction as a reflective measurement model and as an immediate consequence of IS Impact. The CNQ model provides a framework to perceptually measure Computer Network Quality from multiple perspectives. The CNQ model features an easy-to-understand, easy-to-use, and economical survey instrument.

Early adolescents’ helping behaviours when a friend is injured in a fight : the role of an extended Theory of Planned Behavior

This paper examines the role of first aid training in increasing adolescent helping behaviours when taught in a school-based injury prevention program, Skills for Preventing Injury in Youth (SPIY). The research involved the development and application of an extended Theory of Planned Behaviour (TPB), including “behavioural willingness in a fight situation,” “first aid knowledge” and “perceptions of injury seriousness”, to predict the relationship between participation in SPIY and helping behaviours when a friend is injured in a fight. From 35 Queensland high schools, 2500 Year 9 students (mean age = 13.5, 40% male) completed surveys measuring their attitudes, perceived behavioural control, subjective norms and behavioural intention, from the TPB, and added measures of behavioural willingness in a fight situation, perceptions of injury seriousness and first aid knowledge, to predict helping behaviours when a friend is injured in a fight. It is expected that the TPB will significantly contribute to understanding the relationship between participation in SPIY and helping behaviours when a friend is injured in a fight. Further analyses will determine whether the extension of the model significantly increases the variance explained in helping behaviours. The findings of this research will provide insight into the critical factors that may increase adolescent bystanders’ actions in injury situations.

A microscopic simulation model to estimate Bus Rapid Transit (BRT) station service capacity with mixed stopping and non-stopping bus operation

Bus Rapid Transit (BRT) station is the interface between passenger and service. The station is crucial to line operation as it is typically the only location where buses can pass each other. Congestion may occur here when buses maneuvering into and out of the platform lane interfere with bus flow, or when a queue of buses forms upstream of the platform lane blocking the passing lane. However, some systems include operation where express buses pass the critical station, resulting in a proportion of non stopping buses. It is important to understand the operation of the critical busway station under this type of operation, as it affects busway line capacity. This study uses micro simulation to treat the BRT station operation and to analyze the relationship between station Limit state bus capacity (B_ls), Total Bus Capacity (B_ttl). First, the simulation model is developed for Limit state scenario and then a mathematical model is defined, calibrated for a specified range of controlled scenarios of mean and coefficient of variation of dwell time. Thereafter, the proposed B_ls model is extended to consider non stopping buses and B_ttlmodel is defined. The proposed models provides better understanding to the BRT line capacity and is useful for transit authorities for designing better BRT operation.

Numerical solution of an optimal control model of dendritic cell treatment of a growing tumour

A new optimal control model of the interactions between a growing tumour and the host immune system along with an immunotherapy treatment strategy is presented. The model is based on an ordinary differential equation model of interactions between the growing tu- mour and the natural killer, cytotoxic T lymphocyte and dendritic cells of the host immune system, extended through the addition of a control function representing the application of a dendritic cell treat- ment to the system. The numerical solution of this model, obtained from a multi species Runge–Kutta forward-backward sweep scheme, is described. We investigate the effects of varying the maximum al- lowed amount of dendritic cell vaccine administered to the system and find that control of the tumour cell population is best effected via a high initial vaccine level, followed by reduced treatment and finally cessation of treatment. We also found that increasing the strength of the dendritic cell vaccine causes an increase in the number of natural killer cells and lymphocytes, which in turn reduces the growth of the tumour.

Improving the design of online applications for social benefit through a behaviour change model

Community support agencies routinely employ a web presence to provide information on their services. While this online information provision helps to increase an agency’s reach, this paper argues that it can be further extended by mapping relationships between services and by facilitating two-way communication and collaboration with local communities. We argue that emergent technologies, such as locative media and networking tools, can assist in harnessing this social capital. However, new applications must be designed in ways that both persuade and support community members to contribute information and support others in need. An analysis of the online presence of community service agencies and social benefit applications is presented against Fogg’s Behaviour Model. From this evaluation, design principles are proposed for developing new locative, collaborative online applications for social benefit.

The role of desire in understanding intentions to drink responsibly : an application of the model of goal-directed behaviour

This study models young people's moderate drinking decision-making using the Model of Goal-Directed Behaviour (MGB), thus presenting insights into young people's desires and intentions to drink responsibly. Testing the applicability of the MGB to quantitatively analyse responsible drinking, the explanatory sphere of the MGB is extended. An online survey resulted in 1522 completed questionnaires from respondents aged between 18 and 25 years. Collected data were analysed with structural equation modelling (SEM) using SPSS AMOS21 (IBM, New York, NY, USA) software. The key finding of this study is that an individual's desire to drink moderately is the most important predictor of young people's responsible drinking intentions. Our use of MGB provides further evidence that there is a strong distinction between consumer desires and intentions.

Development and application of a predictive model of freshwater fish assemblage composition to evaluate river health in eastern Australia

Multivariate predictive models are widely used tools for assessment of aquatic ecosystem health and models have been successfully developed for the prediction and assessment of aquatic macroinvertebrates, diatoms, local stream habitat features and fish. We evaluated the ability of a modelling method based on the River InVertebrate Prediction and Classification System (RIVPACS) to accurately predict freshwater fish assemblage composition and assess aquatic ecosystem health in rivers and streams of south-eastern Queensland, Australia. The predictive model was developed, validated and tested in a region of comparatively high environmental variability due to the unpredictable nature of rainfall and river discharge. The model was concluded to provide sufficiently accurate and precise predictions of species composition and was sensitive enough to distinguish test sites impacted by several common types of human disturbance (particularly impacts associated with catchment land use and associated local riparian, in-stream habitat and water quality degradation). The total number of fish species available for prediction was low in comparison to similar applications of multivariate predictive models based on other indicator groups, yet the accuracy and precision of our model was comparable to outcomes from such studies. In addition, our model developed for sites sampled on one occasion and in one season only (winter), was able to accurately predict fish assemblage composition at sites sampled during other seasons and years, provided that they were not subject to unusually extreme environmental conditions (e.g. extended periods of low flow that restricted fish movement or resulted in habitat desiccation and local fish extinctions).

Cohabitation, marriage, and divorce in a model of match quality

The objective of this research is to further our understanding of how and why individuals enter and leave coresidential relationships. We develop and estimate an economic model of nonmarital cohabitation, marriage, and divorce that is consistent with current data on the formation and dissolution of relationships. Jovanovic's (Journal of Political Economy 87 (1979), 972-90) theoretical matching model is extended to help explain household formation and dissolution behavior. Implications of the model reveal what factors influence the decision to start a relationship, what form this relationship will take, and the relative stability of the various types of unions. The structural parameters of the model are estimated using longitudinal data from a sample of female high school seniors from the United States. New numerical methods are developed to reduce computational costs associated with estimation. The empirical results have interesting interpretations given the structural model. They show that a significant cause of cohabitation is the need to learn about potential partners and to hedge against future bad shocks. The estimated parameters are used to conduct several comparative dynamic experiments. For example, we show that policy experiments changing the cost of divorce have little effect on relationship choices.

Mechanical model and superelastic properties of carbon microcoils with circular cross-section

Here we report on an unconventional Ni-P alloy-catalyzed, high-throughput, highly reproducible chemical vapor deposition of ultralong carbon microcoils using acetylene precursor in the temperature range 700-750 °C. Scanning electron microscopy analysis reveals that the carbon microcoils have a unique double-helix structure and a uniform circular cross-section. It is shown that double-helix carbon microcoils have outstanding superelastic properties. The microcoils can be extended up to 10-20 times of their original coil length, and quickly recover the original state after releasing the force. A mechanical model of the carbon coils with a large spring index is developed to describe their extension and contraction. Given the initial coil parameters, this mechanical model can successfully account for the geometric nonlinearity of the spring constants for carbon micro- and nanocoils, and is found in a good agreement with the experimental data in the whole stretching process.