From science to management : using Bayesian networks to learn about Lyngbya

Toxic blooms of Lyngbya majuscula occur in coastal areas worldwide and have major ecological, health and economic consequences. The exact causes and combinations of factors which lead to these blooms are not clearly understood. Lyngbya experts and stakeholders are a particularly diverse group, including ecologists, scientists, state and local government representatives, community organisations, catchment industry groups and local fishermen. An integrated Bayesian Network approach was developed to better understand and model this complex environmental problem, identify knowledge gaps, prioritise future research and evaluate management options.

Tangled Webs : Using Bayesian Networks in the Fight Against Infection

Bayesian networks (BNs) provide a statistical modelling framework which is ideally suited for modelling the many factors and components of complex problems such as healthcare-acquired infections. The methicillin-resistant Staphylococcus aureus (MRSA) organism is particularly troublesome since it is resistant to standard treatments for Staph infections. Overcrowding and understa�ng are believed to increase infection transmission rates and also to inhibit the effectiveness of disease control measures. Clearly the mechanisms behind MRSA transmission and containment are very complicated and control strategies may only be e�ective when used in combination. BNs are growing in popularity in general and in medical sciences in particular. A recent Current Content search of the number of published BN journal articles showed a fi�ve fold increase in general and a six fold increase in medical and veterinary science from 2000 to 2009. This chapter introduces the reader to Bayesian network (BN) modelling and an iterative modelling approach to build and test the BN created to investigate the possible role of high bed occupancy on transmission of MRSA while simultaneously taking into account other risk factors.

The Good, the Bad and the Efficient : Productivity, efficiency and technical change in the Airline Industry, 2004:2008

This study models the joint production of desirable and undesirable output production (that is, CO2 emissions) of airlines. The Malmquist-Luenberger productivity index is employed to measure productivity growth when undesirable output production is regulated and unregulated. The results show that pollution abatement activities of airlines lowers productivity growth which suggests the traditional approach of measuring productivity growth, which ignores CO2 emissions, overstate "true" productivity growth.

Accelerating the Mathematics Learning of Low Socio-Economic Status Junior Secondary Students : an early report

The Accelerating the Mathematics Learning of Low Socio-Economic Status Junior Secondary Students project aims to address the issues faced by very underperforming mathematics students as they enter high school. Its aim is to accelerate learning of mathematics through a vertical curriculum to enable students to access Year 10 mathematics subjects, thus improving life chances. This paper reports upon the theory underpinning this project and illustrates it with examples of the curriculum that has been designed to achieve acceleration.

Enterprise social networks : a business model perspective

Enterprise Social Networks continue to be adopted by organisations looking to increase collaboration between employees, customers and industry partners. Offering a varied range of features and functionality, this technology can be distinguished by the underlying business models that providers of this software deploy. This study identifies and describes the different business models through an analysis of leading Enterprise Social Networks: Yammer, Chatter, SharePoint, Connections, Jive, Facebook and Twitter. A key contribution of this research is the identification of consumer and corporate models as extreme approaches. These findings align well with research on the adoption of Enterprise Social Networks that has discussed bottom-up and top-down approaches. Of specific interest are hybrid models that wrap a corporate model within a consumer model and may, therefore, provide synergies on both models. From a broader perspective, this can be seen as the merging of the corporate and consumer markets for IT products and services.

Multiscale investigation of microfilament networks disruption in living cells

Actin is the most abundantly distributed protein in living cells which plays critical roles in the cell interior force generation and transmission. The fracture mechanism of microfilament networks, whose principle component is actin, would provide insights which can contribute to the understandings of self-protective characters of cytoskeleton. In this study, molecular simulations are conducted to investigate the molecular mechanisms of disruption of microfilament networks from the viewpoint of biophysics. By employing a coarse-grained (CG) model of actin filament networks, we focused on the ultimate strength and crack growth mode of microfilament networks that have dependency on the crack length. It can be found that, the fracture mechanism of microfilament network has dependency on the structural properties of microfilament networks. The structure flaws marginally change the strength of microfilament networks which would explain the self-protective characters of cytoskeleton.

Introducing standardized protocols for anthropological measurement of virtual subadult crania using computed tomography

Objectives This study introduces and assesses the precision of a standardized protocol for anthropometric measurement of the juvenile cranium using three-dimensional surface rendered models, for implementation in forensic investigation or paleodemographic research. Materials and methods A subset of multi-slice computed tomography (MSCT) DICOM datasets (n=10) of modern Australian subadults (birth—10 years) was accessed from the “Skeletal Biology and Forensic Anthropology Virtual Osteological Database” (n>1200), obtained from retrospective clinical scans taken at Brisbane children hospitals (2009–2013). The capabilities of Geomagic Design X™ form the basis of this study; introducing standardized protocols using triangle surface mesh models to (i) ascertain linear dimensions using reference plane networks and (ii) calculate the area of complex regions of interest on the cranium. Results The protocols described in this paper demonstrate high levels of repeatability between five observers of varying anatomical expertise and software experience. Intra- and inter-observer error was indiscernible with total technical error of measurement (TEM) values ≤0.56 mm, constituting <0.33% relative error (rTEM) for linear measurements; and a TEM value of ≤12.89 mm2, equating to <1.18% (rTEM) of the total area of the anterior fontanelle and contiguous sutures. Conclusions Exploiting the advances of MSCT in routine clinical assessment, this paper assesses the application of this virtual approach to acquire highly reproducible morphometric data in a non-invasive manner for human identification and population studies in growth and development. The protocols and precision testing presented are imperative for the advancement of “virtual anthropology” into routine Australian medico-legal death investigation.

Cooperative education through a large scale industry-school partnership

In most of the advanced economies, students are losing interest in careers especially in en¬gineering and related industries. Hence, western economies are confronting a critical skilled labour shortage in areas of technology, science and engineering. Decisions about career pathways are made as early as the primary years of schooling and hence cooperation be¬tween industry and schools to attract students to the professions is crucial. The aim of this paper is to document how the organisational and institutional elements of one industry-school partnerships initiative — The Gateway Schools Program — contribute to productive knowledge sharing and networking. In particular this paper focuses on an initiative of an Australian State government in response to a perceived crisis around the skills shortage in an economy transitioning from a localised to a global knowledge production economy. The Gateway Schools initiative signals the first sustained attempt in Australia to incorporate schools into production networks through strategic partnerships linking them to partner organisations at the industry level. We provide case examples of how four schools opera¬tionalise the partnerships with the minerals and energy industries and how these partner¬ships as knowledge assets impact the delivery of curriculum and capacity building among teachers. Our ultimate goal is to define those characteristics of successful partnerships that do contribute to enhanced interest and engagement by students in those careers that are currently experiencing critical shortages.

Technical efficiency of mainstream airlines and low-cost carriers : New evidence using bootstrap data envelopment analysis truncated regression

Between 2001 and 2005, the US airline industry faced financial turmoil while the European airline industry entered a period of substantive deregulation. Consequently, this opened up opportunities for low-cost carriers to become more competitive in the market. To assess airline performance and identify the sources of efficiency in the immediate aftermath of these events, we employ a bootstrap data envelopment analysis truncated regression approach. The results suggest that at the time the mainstream airlines needed to significantly reorganize and rescale their operations to remain competitive. In the second-stage analysis, the results indicate that private ownership, status as a low-cost carrier, and improvements in weight load contributed to better organizational efficiency.

Climate change and IMO technical and operational measures for reduction of emissions of greenhouse gas from ships

According to a study conducted by the International Maritime organisation (IMO) shipping sector is responsible for 3.3% of the global Greenhouse Gas (GHG) emissions. The 1997 Kyoto Protocol calls upon states to pursue limitation or reduction of emissions of GHG from marine bunker fuels working through the IMO. In 2011, 14 years after the adoption of the Kyoto Protocol, the Marine Environment Protection Committee (MEPC) of the IMO has adopted mandatory energy efficiency measures for international shipping which can be treated as the first ever mandatory global GHG reduction instrument for an international industry. The MEPC approved an amendment of Annex VI of the 1973 International Convention for the Prevention of Pollution from Ships (MARPOL 73/78) to introduce a mandatory Energy Efficiency Design Index (EEDI) for new ships and the Ship Energy Efficiency Management Plan (SEEMP) for all ships. Considering the growth projections of human population and world trade the technical and operational measures may not be able to reduce the amount of GHG emissions from international shipping in a satisfactory level. Therefore, the IMO is considering to introduce market-based mechanisms that may serve two purposes including providing a fiscal incentive for the maritime industry to invest in more energy efficient manner and off-setting of growing ship emissions. Some leading developing countries already voiced their serious reservations on the newly adopted IMO regulations stating that by imposing the same obligation on all countries, irrespective of their economic status, this amendment has rejected the Principle of Common but Differentiated Responsibility (the CBDR Principle), which has always been the cornerstone of international climate change law discourses. They also claimed that negotiation for a market based mechanism should not be continued without a clear commitment from the developed counters for promotion of technical co-operation and transfer of technology relating to the improvement of energy efficiency of ships. Against this backdrop, this article explores the challenges for the developing counters in the implementation of already adopted technical and operational measures.

IMO technical and operational measures for reduction of emissions of greenhouse gas from ships : perspectives of Asian countries

International shipping is responsible for about 2.7% of the global emissions of CO2. In the absence of proper action, emissions from the maritime sector may grow by 150% to 250% by 2050, in comparison with the level of emissions in 2007. Against this backdrop, the International Maritime Organisation has introduced a mandatory Energy Efficiency Design Index (EEDI) for new ships and the Ship Energy Efficiency Management Plan (SEEMP) for all ships. Some Asian countries have voiced serious reservations about the newly adopted IMO regulations. They have suggested that imposing the same obligations on all countries, irrespective of their economic status, is a serious departure from the Principle of Common but Differentiated Responsibility, which has always been the cornerstone of international climate change law discourse. Against this backdrop, this article presents a brief overview of the technical and operational measures from the perspective of Asian countries.

Portfolio selection using artificial intelligence

The application of artificial intelligence in finance is relatively new area of research. This project employed artificial neural networks (ANNs) that use both fundamental and technical inputs to predict future prices of widely held Australian stocks and use these predicted prices for stock portfolio selection over a long investment horizon. The research involved the creation and testing of a large number of possible network configurations and draws conclusions about ANN architectures and their overall suitability for the purpose of stock portfolio selection.

Predicting voltage unbalance impacts of plug-in electric vehicles penetration in residential low-voltage distribution networks

Plug-in electric vehicles will soon be connected to residential distribution networks in high quantities and will add to already overburdened residential feeders. However, as battery technology improves, plug-in electric vehicles will also be able to support networks as small distributed generation units by transferring the energy stored in their battery into the grid. Even though the increase in the plug-in electric vehicle connection is gradual, their connection points and charging/discharging levels are random. Therefore, such single-phase bidirectional power flows can have an adverse effect on the voltage unbalance of a three-phase distribution network. In this article, a voltage unbalance sensitivity analysis based on charging/discharging levels and the connection point of plug-in electric vehicles in a residential low-voltage distribution network is presented. Due to the many uncertainties in plug-in electric vehicle ratings and connection points and the network load, a Monte Carlo-based stochastic analysis is developed to predict voltage unbalance in the network in the presence of plug-in electric vehicles. A failure index is introduced to demonstrate the probability of non-standard voltage unbalance in the network due to plug-in electric vehicles.

Sampling designs on stream networks using the pseudo-Bayesian approach

Monitoring stream networks through time provides important ecological information. The sampling design problem is to choose locations where measurements are taken so as to maximise information gathered about physicochemical and biological variables on the stream network. This paper uses a pseudo-Bayesian approach, averaging a utility function over a prior distribution, in finding a design which maximizes the average utility. We use models for correlations of observations on the stream network that are based on stream network distances and described by moving average error models. Utility functions used reflect the needs of the experimenter, such as prediction of location values or estimation of parameters. We propose an algorithmic approach to design with the mean utility of a design estimated using Monte Carlo techniques and an exchange algorithm to search for optimal sampling designs. In particular we focus on the problem of finding an optimal design from a set of fixed designs and finding an optimal subset of a given set of sampling locations. As there are many different variables to measure, such as chemical, physical and biological measurements at each location, designs are derived from models based on different types of response variables: continuous, counts and proportions. We apply the methodology to a synthetic example and the Lake Eacham stream network on the Atherton Tablelands in Queensland, Australia. We show that the optimal designs depend very much on the choice of utility function, varying from space filling to clustered designs and mixtures of these, but given the utility function, designs are relatively robust to the type of response variable.