Outbreaks of pink wax scale, Ceroplastes rubens Maskell (Hemiptera : Coccidae), on umbrella trees in south-eastern Queensland: Patterns of parasitisation

The degree and distribution of parasitisation in relation to densities of pink wax scale, Ceroplastes rubens Maskell, on umbrella trees, Schefflera actinophylla (Endl.), in south-eastern Queensland were investigated to determine whether scale outbreaks could be attributed, in part, to low levels of parasitisation. Rates of parasitisation were independent of or inversely dependent on host density, and highly variable, especially at low densities. The absence of density dependent parasitisation may occur as a result of: (i) non-aggregation by parasitoids; (ii) aggregation by parasitoids where parasitisation is limited by intrinsic or extrinsic factors; and/or (iii) high rates of hyperparasitisation.

A prospective comparison of two models of cannabis use and psychotic relapse in early psychosis

No abstract

Australia-wide predictions of soil properties using decision trees

This paper describes the construction of Australia-wide soil property predictions from a compiled national soils point database. Those properties considered include pH, organic carbon, total phosphorus, total nitrogen, thickness. texture, and clay content. Many of these soil properties are used directly in environmental process modelling including global climate change models. Models are constructed at the 250-m resolution using decision trees. These relate the soil property to the environment through a suite of environmental predictors at the locations where measurements are observed. These models are then used to extend predictions to the continental extent by applying the rules derived to the exhaustively available environmental predictors. The methodology and performance is described in detail for pH and summarized for other properties. Environmental variables are found to be important predictors, even at the 250-m resolution at which they are available here as they can describe the broad changes in soil property.

The effects of adolescent cannabis use: How should the empirical evidence inform drug policy for young people? : Meeting abstract

Ethics as a subject is now consistently taught in medical schools within Australia. The theoretical Ethical models used, and the associated clinical discussions, vary between schools. Registrars have further theoretical Ethics teaching within Psychiatry Fellowship Training, and ongoing clinical work that is likely to provide exposure to complex and frequent Ethical dilemmas. As Psychiatry Trainees approach subspecialty training in Child and Adolescent Psychiatry they therefore have a rich experience of both theoretical Ethics teaching and clinical exposure to Ethical issues. In this symposium, the difficulties Child and Adolescent Psychiatry Trainees may have in the integration of multiple theoretical Ethical models are discussed. It is suggested that these difficulties make Ethics Teaching for Child and Adolescent Psychiatry Trainees particularly challenging. This is important given the complex Ethical issues often present when working with Children and their Families. The three main Ethical models of Deontology, Virtue Ethics and Consequentialism are described and their usefulness for the Child and Adolescent Psychiatrist examined. Limitations of these models, and “Four Principles” approaches (such as that of Beauchamp and Childress), for Child and Adolescent Psychiatry, are also considered. Clinical cases are included for discussion. Finally, the ways in which these models may be used to enhance Child and Adolescent Psychiatry Training, and subsequent clinical practice as a Child and Adolescent Psychiatrist, are discussed. The integration of different theoretical Ethical models is considered, with implications identified for clinical practice.

Reliability measures for local nodes assessment in classification trees

Most of the modem developments with classification trees are aimed at improving their predictive capacity. This article considers a curiously neglected aspect of classification trees, namely the reliability of predictions that come from a given classification tree. In the sense that a node of a tree represents a point in the predictor space in the limit, the aim of this article is the development of localized assessment of the reliability of prediction rules. A classification tree may be used either to provide a probability forecast, where for each node the membership probabilities for each class constitutes the prediction, or a true classification where each new observation is predictively assigned to a unique class. Correspondingly, two types of reliability measure will be derived-namely, prediction reliability and classification reliability. We use bootstrapping methods as the main tool to construct these measures. We also provide a suite of graphical displays by which they may be easily appreciated. In addition to providing some estimate of the reliability of specific forecasts of each type, these measures can also be used to guide future data collection to improve the effectiveness of the tree model. The motivating example we give has a binary response, namely the presence or absence of a species of Eucalypt, Eucalyptus cloeziana, at a given sampling location in response to a suite of environmental covariates, (although the methods are not restricted to binary response data).

Integrating JERS-1 imaging radar and elevation models for mapping tropical rainforest communities in far North Queensland, Australia

The Wet Tropics World Heritage Area in Far North Queens- land, Australia consists predominantly of tropical rainforest and wet sclerophyll forest in areas of variable relief. Previous maps of vegetation communities in the area were produced by a labor-intensive combination of field survey and air-photo interpretation. Thus,. the aim of this work was to develop a new vegetation mapping method based on imaging radar that incorporates topographical corrections, which could be repeated frequently, and which would reduce the need for detailed field assessments and associated costs. The method employed G topographic correction and mapping procedure that was developed to enable vegetation structural classes to be mapped from satellite imaging radar. Eight JERS-1 scenes covering the Wet Tropics area for 1996 were acquired from NASDA under the auspices of the Global Rainforest Mapping Project. JERS scenes were geometrically corrected for topographic distortion using an 80 m DEM and a combination of polynomial warping and radar viewing geometry modeling. An image mosaic was created to cover the Wet Tropics region, and a new technique for image smoothing was applied to the JERS texture bonds and DEM before a Maximum Likelihood classification was applied to identify major land-cover and vegetation communities. Despite these efforts, dominant vegetation community classes could only be classified to low levels of accuracy (57.5 percent) which were partly explained by the significantly larger pixel size of the DEM in comparison to the JERS image (12.5 m). In addition, the spatial and floristic detail contained in the classes of the original validation maps were much finer than the JERS classification product was able to distinguish. In comparison to field and aerial photo-based approaches for mapping the vegetation of the Wet Tropics, appropriately corrected SAR data provides a more regional scale, all-weather mapping technique for broader vegetation classes. Further work is required to establish an appropriate combination of imaging radar with elevation data and other environmental surrogates to accurately map vegetation communities across the entire Wet Tropics.

Application and evaluation of classification trees for screening unwanted plants

Risk assessment systems for introduced species are being developed and applied globally, but methods for rigorously evaluating them are still in their infancy. We explore classification and regression tree models as an alternative to the current Australian Weed Risk Assessment system, and demonstrate how the performance of screening tests for unwanted alien species may be quantitatively compared using receiver operating characteristic (ROC) curve analysis. The optimal classification tree model for predicting weediness included just four out of a possible 44 attributes of introduced plants examined, namely: (i) intentional human dispersal of propagules; (ii) evidence of naturalization beyond native range; (iii) evidence of being a weed elsewhere; and (iv) a high level of domestication. Intentional human dispersal of propagules in combination with evidence of naturalization beyond a plants native range led to the strongest prediction of weediness. A high level of domestication in combination with no evidence of naturalization mitigated the likelihood of an introduced plant becoming a weed resulting from intentional human dispersal of propagules. Unlikely intentional human dispersal of propagules combined with no evidence of being a weed elsewhere led to the lowest predicted probability of weediness. The failure to include intrinsic plant attributes in the model suggests that either these attributes are not useful general predictors of weediness, or data and analysis were inadequate to elucidate the underlying relationship(s). This concurs with the historical pessimism that we will ever be able to accurately predict invasive plants. Given the apparent importance of propagule pressure (the number of individuals of an species released), future attempts at evaluating screening model performance for identifying unwanted plants need to account for propagule pressure when collating and/or analysing datasets. The classification tree had a cross-validated sensitivity of 93.6% and specificity of 36.7%. Based on the area under the ROC curve, the performance of the classification tree in correctly classifying plants as weeds or non-weeds was slightly inferior (Area under ROC curve = 0.83 +/- 0.021 (+/- SE)) to that of the current risk assessment system in use (Area under ROC curve = 0.89 +/- 0.018 (+/- SE)), although requires many fewer questions to be answered.

Evaluation of different models to describe egg and pupal development of Xyleborus fornicatus Eichh. (Coleoptera: Scolytidae), the shot-hole borer of tea in Sri Lanka

Abstract Development data of eggs and pupae of Xyleborus fornicatus Eichh. (Coleoptera: Scolytidae), the shot-hole borer of tea in Sri Lanka, at constant temperatures were used to evaluate a linear and seven nonlinear models for insect development. Model evaluation was based on fit to data (residual sum of squares and coefficient of determination or coefficient of nonlinear regression), number of measurable parameters, the biological value of the fitted coefficients and accuracy in the estimation of thresholds. Of the nonlinear models, the Lactin model fitted experimental data well and along with the linear model, can be used to describe the temperature-dependent development of this species.

A rigorous foundation for pattern based design models

This paper presents a way to describe design patterns rigorously based on role concepts. Rigorous pattern descriptions are a key aspect for patterns to be used as rules for model evolution in the MDA context, for example. We formalize the role concepts commonly used in defining design patterns as a role metamodel using Object-Z. Given this role metamodel, individual design patterns are specified generically as a formal pattern role model using Object-Z. We also formalize the properties that must be captured in a class model when a design pattern is deployed. These properties are defined generically in terms of role bindings from a pattern role model to a class model. Our work provides a precise but abstract approach for pattern definition and also provides a precise basis for checking the validity of pattern usage in designs.

Verifying abstract information flow properties in fault tolerant security devices

The verification of information flow properties of security devices is difficult because it involves the analysis of schematic diagrams, artwork, embedded software, etc. In addition, a typical security device has many modes, partial information flow, and needs to be fault tolerant. We propose a new approach to the verification of such devices based upon checking abstract information flow properties expressed as graphs. This approach has been implemented in software, and successfully used to find possible paths of information flow through security devices.

Abstract specification in Object-Z and CSP

A number of integrations of the state-based specification language Object-Z and the process algebra CSP have been proposed in recent years. In developing such integrations, a number of semantic decisions have to be made. In particular, what happens when an operation's precondition is not satisfied? Is the operation blocked, i.e., prevented from occurring, or can it occur with an undefined result? Also, are outputs from operations angelic, satisfying the environment's constraints on them, or are they demonic and not influenced by the environment at all? In this paper we discuss the differences between the models, and show that by adopting a blocking model of preconditions together with an angelic model of outputs one can specify systems at higher levels of abstraction.

Formal verification of ASM designs using the MDG tool

In this paper, we present a formal hardware verification framework linking ASM with MDG. ASM (Abstract State Machine) is a state based language for describing transition systems. MDG (Multiway Decision Graphs) provides symbolic representation of transition systems with support of abstract sorts and functions. We implemented a transformation tool that automatically generates MDG models from ASM specifications, then formal verification techniques provided by the MDG tool, such as model checking or equivalence checking, can be applied on the generated models. We support this work with a case study of an Island Tunnel Controller, which behavior and structure were specified in ASM then using our ASM-MDG tool successfully verified within the MDG tool.

Interfacing ASM with the MDG tool

In this paper we describe an approach to interface Abstract State Machines (ASM) with Multiway Decision Graphs (MDG) to enable tool support for the formal verification of ASM descriptions. ASM is a specification method for software and hardware providing a powerful means of modeling various kinds of systems. MDGs are decision diagrams based on abstract representation of data and axe used primarily for modeling hardware systems. The notions of ASM and MDG axe hence closely related to each other, making it appealing to link these two concepts. The proposed interface between ASM and MDG uses two steps: first, the ASM model is transformed into a flat, simple transition system as an intermediate model. Second, this intermediate model is transformed into the syntax of the input language of the MDG tool, MDG-HDL. We have successfully applied this transformation scheme on a case study, the Island Tunnel Controller, where we automatically generated the corresponding MDG-HDL models from ASM specifications.

Defining a role for the subthalamic nucleus within operative theoretical models of subcortical participation in language

Objective:To investigate the effects of bilateral, surgically induced functional inhibition of the subthalamic nucleus (STN) on general language, high level linguistic abilities, and semantic processing skills in a group of patients with Parkinson’s disease. Methods:Comprehensive linguistic profiles were obtained up to one month before and three months after bilateral implantation of electrodes in the STN during active deep brain stimulation (DBS) in five subjects with Parkinson’s disease (mean age, 63.2 years). Equivalent linguistic profiles were generated over a three month period for a non-surgical control cohort of 16 subjects with Parkinson’s disease (NSPD) (mean age, 64.4 years). Education and disease duration were similar in the two groups. Initial assessment and three month follow up performance profiles were compared within subjects by paired t tests. Reliability change indices (RCI), representing clinically significant alterations in performance over time, were calculated for each of the assessment scores achieved by the five STN-DBS cases and the 16 NSPD controls, relative to performance variability within a group of 16 non-neurologically impaired adults (mean age, 61.9 years). Proportions of reliable change were then compared between the STN-DBS and NSPD groups. Results:Paired comparisons within the STN-DBS group showed prolonged postoperative semantic processing reaction times for a range of word types coded for meanings and meaning relatedness. Case by case analyses of reliable change across language assessments and groups revealed differences in proportions of change over time within the STN-DBS and NSPD groups in the domains of high level linguistics and semantic processing. Specifically, when compared with the NSPD group, the STN-DBS group showed a proportionally significant (p