Effective emergency messaging during natural disasters: An application of message compliance theories

Study/Objective This research examines the types of emergency messages used in Australia during the response and early recovery phases of a natural disaster. The aim of the research is to develop theory-driven emergency messages that increase individual behavioural compliance during a disaster. Background There is growing evidence of non-compliant behaviour in Australia, such as refusing to evacuate and travelling through hazardous areas. This can result in personal injury, loss of life, and damage to (or loss of) property. Moreover, non-compliance can place emergency services personnel in life-threatening situations when trying to save non-compliant individuals. Drawing on message compliance research in psychology and sociology, a taxonomy of message types was developed to ascertain how emergency messaging can be improved to produce compliant behaviour. Method A review of message compliance literature was conducted to develop the taxonomy of message types previously found to achieve compliance. Seven categories were identified: direct-rational, manipulation, negative phrasing, positive phrasing, exchange appeals, normative appeals, and appeals to self. A content analysis was then conducted to assess the emergency messages evident in the Australian emergency management context. The existing messages were aligned with the literature to identify opportunities to improve emergency messaging. Results & Conclusion The results suggest there is an opportunity to improve the effectiveness of emergency messaging to increase compliance during the response and early recovery phases of a natural disaster. While some message types cannot legally or ethically be used in emergency communication (e.g. manipulative messaging), there is an opportunity to create more persuasive messages (e.g. appeals to self) that personalise the individual’s perception of risk, triggering them to comply with the message.

Application of higher-order spectra for automated grading of diabetic maculopathy

Diabetic macular edema (DME) is one of the most common causes of visual loss among diabetes mellitus patients. Early detection and successive treatment may improve the visual acuity. DME is mainly graded into non-clinically significant macular edema (NCSME) and clinically significant macular edema according to the location of hard exudates in the macula region. DME can be identified by manual examination of fundus images. It is laborious and resource intensive. Hence, in this work, automated grading of DME is proposed using higher-order spectra (HOS) of Radon transform projections of the fundus images. We have used third-order cumulants and bispectrum magnitude, in this work, as features, and compared their performance. They can capture subtle changes in the fundus image. Spectral regression discriminant analysis (SRDA) reduces feature dimension, and minimum redundancy maximum relevance method is used to rank the significant SRDA components. Ranked features are fed to various supervised classifiers, viz. Naive Bayes, AdaBoost and support vector machine, to discriminate No DME, NCSME and clinically significant macular edema classes. The performance of our system is evaluated using the publicly available MESSIDOR dataset (300 images) and also verified with a local dataset (300 images). Our results show that HOS cumulants and bispectrum magnitude obtained an average accuracy of 95.56 and 94.39 % for MESSIDOR dataset and 95.93 and 93.33 % for local dataset, respectively.

Global environmental emissions estimate: Application of multiple imputation

A new database called the World Resource Table is constructed in this study. Missing values are known to produce complications when constructing global databases. This study provides a solution for applying multiple imputation techniques and estimates the global environmental Kuznets curve (EKC) for CO2, SO2, PM10, and BOD. Policy implications for each type of emission are derived based on the results of the EKC using WRI. Finally, we predicted the future emissions trend and regional share of CO2 emissions. We found that East Asia and South Asia will be increasing their emissions share while other major CO2 emitters will still produce large shares of the total global emissions.

Personas of students accessing a peer-facilitated support for learning program

STIMulate is a support for learning program at the Queensland University of Technology in Brisbane, Australia. The program provides assistance in mathematics, science and information technology for undergraduate students. This paper develops personas - archetypal users - that represent the attitudes and motivations of students that utilise STIMulate (in particular, the IT stream). Seven different personas were developed based on interviews gathered from Peer Learning Facilitators (PLF) who are experienced students that have excelled in relevant subject areas. The personas were then validated by a PLF focus group. Developing the personas enabled us to better understand the characteristics and needs of the students using the STIMulate program, enabling a more critical analysis of the quality of the service provided.

Adapting to concurrent expert evidence in medical litigation

In medical negligence litigation expert evidence has long played a dominant role. The trend towards the use of concurrent expert evidence is now well underway. However, for the lawyers and the doctors involved, the pathway is not yet familiar. Disputes have frequently arisen in the context of pre-hearing expert conclaves, given the adversarial nature of litigation and perhaps fuelled by fears of a less transparent process at this increasingly important stage. This article explains the concurrent expert evidence framework and examines areas of common dispute both in the conclaves and at trial, with a view to providing assistance to legal practitioners working in this area and the medical practitioners called upon to provide expert evidence in such litigation.

A network DEA quantity and quality-orientated production model: An application to Australian university research services

The motivation for this analysis is the recently developed Excellence in Research for Australia (ERA) program developed to assess the quality of research in Australia. The objective is to develop an appropriate empirical model that better represents the underlying production of higher education research. In general, past studies on university research performance have used standard DEA models with some quantifiable research outputs. However, these suffer from the twin maladies of an inappropriate production specification and a lack of consideration of the quality of output. By including the qualitative attributes of peer-reviewed journals, we develop a procedure that captures both quality and quantity, and apply it using a network DEA model. Our main finding is that standard DEA models tend to overstate the research efficiency of most Australian universities.

The role of innovation intermediaries in collaborative networks of small and medium-sized enterprises

The major challenge of European Union’s agricultural industry is to ensure sustainable supply of quality food that meets the demands of a rapidly growing population, changing dietary patterns, increased competition for land use, and environmental concerns. Investments in research and innovation, which facilitate integration of external knowledge in food chain operations, are crucial to undertaking such challenges. This paper addresses how SMEs successfully innovate within collaborative networks with the assistance of innovation intermediaries. In particular, we explore the roles of innovation intermediaries in knowledge acquisition, knowledge assimilation, knowledge, transformation, and knowledge exploitation in open innovation initiatives from the wine industry through the theoretical lens of absorptive capacity. Based on two case studies from the wine industry, we identified seven key activities performed by innovation intermediaries that complement SMEs’ ability to successfully leverage external sources of knowledge for innovation purposes. These activities are articulation of knowledge needs and innovation capabilities, facilitation of social interactions, establishment of complementary links, implementation of governance structures, conflict management, enhancement of transparency, and mediation of communication. Our in-depth qualitative study of two innovation intermediaries in the wine industry has several important implications that contribute to research and practice.

Prevalence of alcohol-impaired driving and riding in northern Ghana

Objective The objective of this study was to determine the roadside prevalence of alcohol-impaired driving among drivers and riders in northern Ghana. The study also verifies motorists’ perception on their own alcohol use and knowledge of legal Blood Alcohol Concentration (BAC) limit of Ghana. Method With the assistance of police, the systematic random sampling was used to collect data at roadblocks using a cross-sectional study design. Breathalyzers were used to screen whether motorists had detectable alcohol in their breath and a follow-up breath tests conducted to measure the actual breath alcohol levels among positive participants. Results In all, 9.7% of the 789 participants had detectable alcohol among whom 6% exceeded the legal (BAC) limit of 0.08%. The prevalence of alcohol-impaired driving/riding was highest among cyclists (10% of all cyclists breath tested) followed by truck drivers 9% and motorcyclists (7% of all motorcyclists breath tested). The occurrence of a positive BAC among cyclists was about 8 times higher, (OR=7.73; p<0.001) and 2 times higher, among motorcyclists (OR=2.30; p=0.039) compared with private car drivers. The likelihood for detecting a positive BAC among male motorists/riders was higher than females (OR=1.67; p=0.354). The odds for detecting a positive BAC among weekend motorists/riders was significantly higher than weekdays (OR=2.62; p=0.001). Conclusion Alcohol-impaired driving/riding in Ghana is high by international standards. In order to attenuate the harmful effects of alcohol misuse such as alcohol-impaired driving/riding, there is the need to educate road users about how much alcohol they can consume and stay below the legal limit. The police should also initiate random breath testing to instil the deterrence of detection, certainty of apprehension and punishment, and severity and celerity of punishment among drink-driving motorists and riders.

Modelling collision potentials in Port Anchorages: Application of the Navigational Traffic Conflict Technique (NTCT)

Despite the extent of works done on modelling port water collisions, not much research effort has been devoted to modelling collisions at port anchorages. This paper aims to fill this important gap in literature by applying the Navigation Traffic Conflict Technique (NTCT) for measuring the collision potentials in anchorages and for examining the factors contributing to collisions. Grounding on the principles of the NTCT, a collision potential measurement model and a collision potential prediction model were developed. These models were illustrated by using vessel movement data of the anchorages in Singapore port waters. Results showed that the measured collision potentials are in close agreement with those perceived by harbour pilots. Higher collision potentials were found in anchorages attached to shoreline and international fairways, but not at those attached to confined water. Higher operating speeds, larger numbers of isolated danger marks and day conditions were associated with reduction in the collision potentials.

A new registration method based on Log-Euclidean tensor metrics and its application to genetic studies

In structural brain MRI, group differences or changes in brain structures can be detected using Tensor-Based Morphometry (TBM). This method consists of two steps: (1) a non-linear registration step, that aligns all of the images to a common template, and (2) a subsequent statistical analysis. The numerous registration methods that have recently been developed differ in their detection sensitivity when used for TBM, and detection power is paramount in epidemological studies or drug trials. We therefore developed a new fluid registration method that computes the mappings and performs statistics on them in a consistent way, providing a bridge between TBM registration and statistics. We used the Log-Euclidean framework to define a new regularizer that is a fluid extension of the Riemannian elasticity, which assures diffeomorphic transformations. This regularizer constrains the symmetrized Jacobian matrix, also called the deformation tensor. We applied our method to an MRI dataset from 40 fraternal and identical twins, to revealed voxelwise measures of average volumetric differences in brain structure for subjects with different degrees of genetic resemblance.

Automatic clustering of white matter fibers in brain diffusion mri with an application to genetics

To understand factors that affect brain connectivity and integrity, it is beneficial to automatically cluster white matter (WM) fibers into anatomically recognizable tracts. Whole brain tractography, based on diffusion-weighted MRI, generates vast sets of fibers throughout the brain; clustering them into consistent and recognizable bundles can be difficult as there are wide individual variations in the trajectory and shape of WM pathways. Here we introduce a novel automated tract clustering algorithm based on label fusion - a concept from traditional intensity-based segmentation. Streamline tractography generates many incorrect fibers, so our top-down approach extracts tracts consistent with known anatomy, by mapping multiple hand-labeled atlases into a new dataset. We fuse clustering results from different atlases, using a mean distance fusion scheme. We reliably extracted the major tracts from 105-gradient high angular resolution diffusion images (HARDI) of 198 young normal twins. To compute population statistics, we use a pointwise correspondence method to match, compare, and average WM tracts across subjects. We illustrate our method in a genetic study of white matter tract heritability in twins.

MR image-based measurement of rates of change in volumes of brain structures. Part II: Application to a study of Alzheimer's disease and normal aging

We present global and regional rates of brain atrophy measured on serially acquired Tl-weighted brain MR images for a group of Alzheimer's disease (AD) patients and age-matched normal control (NC) subjects using the analysis procedure described in Part I. Three rates of brain atrophy: the rate of atrophy in the cerebrum, the rate of lateral ventricular enlargement and the rate of atrophy in the region of temporal lobes, were evaluated for 14 AD patients and 14 age-matched NC subjects. All three rates showed significant differences between the two groups. However, the greatest separation of the two groups was obtained when the regional rates were combined. This application has demonstrated that rates of brain atrophy, especially in specific regions of the brain, based on MR images can provide sensitive measures for evaluating the progression of AD. These measures will be useful for the evaluation of therapeutic effects of novel therapies for AD.

Application of fragment-based screening to the design of inhibitors of Escherichia coli DsbA

The thiol-disulfide oxidoreductase enzyme DsbA catalyzes the formation of disulfide bonds in the periplasm of Gram-negative bacteria. DsbA substrates include proteins involved in bacterial virulence. In the absence of DsbA, many of these proteins do not fold correctly, which renders the bacteria avirulent. Thus DsbA is a critical mediator of virulence and inhibitors may act as antivirulence agents. Biophysical screening has been employed to identify fragments that bind to DsbA from Escherichia coli. Elaboration of one of these fragments produced compounds that inhibit DsbA activity in vitro. In cell-based assays, the compounds inhibit bacterial motility, but have no effect on growth in liquid culture, which is consistent with selective inhibition of DsbA. Crystal structures of inhibitors bound to DsbA indicate that they bind adjacent to the active site. Together, the data suggest that DsbA may be amenable to the development of novel antibacterial compounds that act by inhibiting bacterial virulence.