Anti-metabolic effects of Galanthus nivalis agglutinin and wheat germ agglutinin on nymphal stages of the common brown leafhopper using a novel artificial diet system

The common brown leafhopper, Orosius orientalis (Matsumura) (Homoptera: Cicadellidae), previously described as Orosius argentatus (Evans), is an important vector of several viruses and phytoplasmas worldwide. In Australia, phytoplasmas vectored by O. orientalis cause a range of economically important diseases, including legume little leaf (Hutton & Grylls, 1956), tomato big bud (Osmelak, 1986), lucerne witches broom (Helson, 1951), potato purple top wilt (Harding & Teakle, 1985), and Australian lucerne yellows (Pilkington et al., 2004). Orosius orientalis also transmits Tobacco yellow dwarf virus (TYDV; genus Mastrevirus, family Geminiviridae) to beans, causing bean summer death disease (Ballantyne, 1968), and to tobacco, causing tobacco yellow dwarf disease (Hill, 1937, 1941). TYDV has only been recorded in Australia to date. Both diseases result in significant production and quality losses (Ballantyne, 1968; Thomas, 1979; Moran & Rodoni, 1999). Although direct damage caused by leafhopper feeding has been observed, it is relatively minor compared to the losses resulting from disease (P Tr E bicki, unpubl.).

Collaboration using BIM : results of cooperative research centre for construction innovation projects

This paper discusses the issues with sharing information between different disciplines in collaborative projects. The focus is on the information itself rather than the wider issues of collaboration. A range of projects carried out by the Cooperative Research Centre for Construction Innovation (CRC CI) in Australia is used to illustrate the issues.

Towards continuous surveillance of fruit flies using sensor networks and machine vision

In Australia, the Queensland fruit fly (B. tryoni), is the most destructive insect pest of horticulture, attacking nearly all fruit and vegetable crops. This project has researched and prototyped a system for monitoring fruit flies so that authorities can be alerted when a fly enters a crop in a more efficient manner than is currently used. This paper presents the idea of our sensor platform design as well as the fruit fly detection and recognition algorithm by using machine vision techniques. Our experiments showed that the designed trap and sensor platform is capable to capture quality fly images, the invasive flies can be successfully detected and the average precision of the Queensland fruit fly recognition is 80% from our experiment.

High-level concept annotation using ontology and probabilistic inference

Image annotation is a significant step towards semantic based image retrieval. Ontology is a popular approach for semantic representation and has been intensively studied for multimedia analysis. However, relations among concepts are seldom used to extract higher-level semantics. Moreover, the ontology inference is often crisp. This paper aims to enable sophisticated semantic querying of images, and thus contributes to 1) an ontology framework to contain both visual and contextual knowledge, and 2) a probabilistic inference approach to reason the high-level concepts based on different sources of information. The experiment on a natural scene database from LabelMe database shows encouraging results.

Using the imagination : consumer evoking and thematizing of the fantastic imaginary

This article explores the process by which consumers evoke and thematize the fantastic imaginary when playing a fantasy-based trading card game. Interviews with 15 informants, all players of Magic: The Gathering, serve as data. The result is a new framework that reveals how the fantastic imaginary is evoked and thematized. A typology of thematizing strategies employed by consumers is also presented. Implications are discussed in relation to consumer research, imagination theory, literary theory of the evoked fantastic imaginary, and the imaginary in play.

Using Trauma Injury Severity Score (TRISS) variables to predict length of hospital stay following trauma in New Zealand

Aim – To develop and assess the predictive capabilities of a statistical model that relates routinely collected Trauma Injury Severity Score (TRISS) variables to length of hospital stay (LOS) in survivors of traumatic injury. Method – Retrospective cohort study of adults who sustained a serious traumatic injury, and who survived until discharge from Auckland City, Middlemore, Waikato, or North Shore Hospitals between 2002 and 2006. Cubic-root transformed LOS was analysed using two-level mixed-effects regression models. Results – 1498 eligible patients were identified, 1446 (97%) injured from a blunt mechanism and 52 (3%) from a penetrating mechanism. For blunt mechanism trauma, 1096 (76%) were male, average age was 37 years (range: 15-94 years), and LOS and TRISS score information was available for 1362 patients. Spearman’s correlation and the median absolute prediction error between LOS and the original TRISS model was ρ=0.31 and 10.8 days, respectively, and between LOS and the final multivariable two-level mixed-effects regression model was ρ=0.38 and 6.0 days, respectively. Insufficient data were available for the analysis of penetrating mechanism models. Conclusions – Neither the original TRISS model nor the refined model has sufficient ability to accurately or reliably predict LOS. Additional predictor variables for LOS and other indicators for morbidity need to be considered.

Using a longitudinal model to estimate the effect of methicillin-resistant staphylococcus aureus infection on length of stay in an intensive care unit

Healthcare-associated methicillin-resistant Staphylococcus aureus(MRSA) infection may cause increased hospital stay or, sometimes, death. Quantifying this effect is complicated because it is a time-dependent exposure: infection may prolong hospital stay, while longer stays increase the risk of infection. We overcome these problems by using a multinomial longitudinal model for estimating the daily probability of death and discharge. We then extend the basic model to estimate how the effect of MRSA infection varies over time, and to quantify the number of excess ICU days due to infection. We find that infection decreases the relative risk of discharge (relative risk ratio = 0.68, 95% credible interval: 0.54, 0.82), but is only indirectly associated with increased mortality. An infection on the first day of admission resulted in a mean extra stay of 0.3 days (95% CI: 0.1, 0.5) for a patient with an APACHE II score of 10, and 1.2 days (95% CI: 0.5, 2.0) for a patient with an APACHE II score of 30. The decrease in the relative risk of discharge remained fairly constant with day of MRSA infection, but was slightly stronger closer to the start of infection. These results confirm the importance of MRSA infection in increasing ICU stay, but suggest that previous work may have systematically overestimated the effect size.

Computational approach to localization using global energy minimization

Damage localization induced by strain softening can be predicted by the direct minimization of a global energy function. This article concerns the computational strategy for implementing this principle for softening materials such as concrete. Instead of using heuristic global optimization techniques, our strategies are a hybrid of local optimization methods with a path-finding approach to ensure a global optimum. With admissible nodal displacements being independent variables, it is easy to deal with the geometric (mesh) constraint conditions. The direct search optimization methods recover the localized solutions for a range of softening lattice models which are representative of quasi-brittle structures

Enforcing P3P policies using a digital rights management system

The protection of privacy has gained considerable attention recently. In response to this, new privacy protection systems are being introduced. SITDRM is one such system that protects private data through the enforcement of licenses provided by consumers. Prior to supplying data, data owners are expected to construct a detailed license for the potential data users. A license specifies whom, under what conditions, may have what type of access to the protected data. The specification of a license by a data owner binds the enterprise data handling to the consumer’s privacy preferences. However, licenses are very detailed, may reveal the internal structure of the enterprise and need to be kept synchronous with the enterprise privacy policy. To deal with this, we employ the Platform for Privacy Preferences Language (P3P) to communicate enterprise privacy policies to consumers and enable them to easily construct data licenses. A P3P policy is more abstract than a license, allows data owners to specify the purposes for which data are being collected and directly reflects the privacy policy of an enterprise.

Using self-referencing to explain the effectiveness of ethnic minority models in advertising

Advertising research has generally not gone beyond offering support for a positive effect where ethnic models in advertising are viewed by consumers of the same ethnicity. This study offers an explanation behind this phenomenon that can be useful to marketers using self-reference theory. Our experiment reveals a strong self-referencing effect for ethnic minority individuals. Specifically, Asian subjects (the ethnic minority group) self-referenced ads with Asian models more than white subjects (the ethnic majority group). However, this result was not evident for white subjects. Implications for academics and advertisers are discussed.

Characterising anomalous events using change point correlation on unsolicited network traffic

Monitoring unused or dark IP addresses offers opportunities to extract useful information about both on-going and new attack patterns. In recent years, different techniques have been used to analyze such traffic including sequential analysis where a change in traffic behavior, for example change in mean, is used as an indication of malicious activity. Change points themselves say little about detected change; further data processing is necessary for the extraction of useful information and to identify the exact cause of the detected change which is limited due to the size and nature of observed traffic. In this paper, we address the problem of analyzing a large volume of such traffic by correlating change points identified in different traffic parameters. The significance of the proposed technique is two-fold. Firstly, automatic extraction of information related to change points by correlating change points detected across multiple traffic parameters. Secondly, validation of the detected change point by the simultaneous presence of another change point in a different parameter. Using a real network trace collected from unused IP addresses, we demonstrate that the proposed technique enables us to not only validate the change point but also extract useful information about the causes of change points.

Estimating total cross sections from neutron-nucleus collisions using a simple functional form

Total cross sections for neutron scattering from nuclei, with energies ranging from 10 to 600 MeV and from many nuclei spanning the mass range 6Li to 238U, have been analyzed using a simple, three-parameter, functional form. The calculated cross sections are compared with results obtained by using microscopic (g-folding) optical potentials as well as with experimental data. The functional form reproduces those total cross sections very well. When allowance is made for Ramsauer-like effects in the scattering, the parameters of the functional form required vary smoothly with energy and target mass. They too can be represented by functions of energy and mass.

Crowd Counting Using Multiple Local Features

In public venues, crowd size is a key indicator of crowd safety and stability. Crowding levels can be detected using holistic image features, however this requires a large amount of training data to capture the wide variations in crowd distribution. If a crowd counting algorithm is to be deployed across a large number of cameras, such a large and burdensome training requirement is far from ideal. In this paper we propose an approach that uses local features to count the number of people in each foreground blob segment, so that the total crowd estimate is the sum of the group sizes. This results in an approach that is scalable to crowd volumes not seen in the training data, and can be trained on a very small data set. As a local approach is used, the proposed algorithm can easily be used to estimate crowd density throughout different regions of the scene and be used in a multi-camera environment. A unique localised approach to ground truth annotation reduces the required training data is also presented, as a localised approach to crowd counting has different training requirements to a holistic one. Testing on a large pedestrian database compares the proposed technique to existing holistic techniques and demonstrates improved accuracy, and superior performance when test conditions are unseen in the training set, or a minimal training set is used.

Long-term outcomes of seriously injured children : a study using the Child Health Questionnaire

Objective: To assess the health-related quality of life (HRQoL) in children 1-2 years after they had sustained an injury. Methods: Parents of all children who were identified by the Queensland Trauma Registry during their admission to either of the two paediatric specialty hospitals in Brisbane, Australia, for the treatment of an injury, were invited to participate in this study. Parents who consented to participation received a copy of the Child Health Questionnaire (CHQ) that required them to provide information regarding their child’s HRQoL following injury. The CHQ scores for the study respondents were compared with those of the Australian norms. This study was approved by the relevant ethics committees. Results: Two hundred and forty-one completed questionnaires were returned. The majority of cases were male (65%) and there was even representation across all age groups. The majority of injuries were considered to be minor (81%) and were predominantly the result of falls and cycling accidents causing mainly fractures and intracranial injury. On the majority of subscales of the CHQ, study participants recorded scores that were statistically significantly below those of the Australian norms. None of the relevant variables collected by the Queensland Trauma Registry were found to predict scores on the CHQ in this study (for those children hospitalized for >24 h). Conclusion: Injured children are worse off than their Australian counterparts in terms of HRQoL even up to 2 years following an injury. Further research needs to be undertaken to identify factors that predict lower HRQoL in order to reduce the burden of injury on children and their families.