Double generalized linear model for tissue culture proportion data: a Bayesian perspective

Joint generalized linear models and double generalized linear models (DGLMs) were designed to model outcomes for which the variability can be explained using factors and/or covariates. When such factors operate, the usual normal regression models, which inherently exhibit constant variance, will under-represent variation in the data and hence may lead to erroneous inferences. For count and proportion data, such noise factors can generate a so-called overdispersion effect, and the use of binomial and Poisson models underestimates the variability and, consequently, incorrectly indicate significant effects. In this manuscript, we propose a DGLM from a Bayesian perspective, focusing on the case of proportion data, where the overdispersion can be modeled using a random effect that depends on some noise factors. The posterior joint density function was sampled using Monte Carlo Markov Chain algorithms, allowing inferences over the model parameters. An application to a data set on apple tissue culture is presented, for which it is shown that the Bayesian approach is quite feasible, even when limited prior information is available, thereby generating valuable insight for the researcher about its experimental results.

Making Fedora easier to implement with Fez: A free open source content model and workflow management front-end to Fedora

The University of Queensland, Australia has developed Fez, a world-leading user-interface and management system for Fedora-based institutional repositories, which bridges the gap between a repository and users. Christiaan Kortekaas, Andrew Bennett and Keith Webster will review this open source software that gives institutions the power to create a comprehensive repository solution without the hassle..

Religious Information Poverty in Australian State Schools

This paper introduces the concept of religious information poverty in Australian state schools from an information science perspective. Information scientists have been theorising about the global information society for some time, along with its increased provision of vital information for the good of the world. Australian state schools see themselves as preparing children for effective participation in the information society, yet Australian children are currently suffering a religious illiteracy that undermines this goal. Some reasons and theories are offered to explain the existence of religious information poverty in state schools, and suggestions for professional stakeholders are offered for its alleviation.

Combining GIS and Expert Opinion to Model Landscapes for a Smallholder Forest Extension Program in Leyte, the Philippines

A Geographic Information System (GIS) was used to model datasets of Leyte Island, the Philippines, to identify land which was suitable for a forest extension program on the island. The datasets were modelled to provide maps of the distance of land from cities and towns, land which was a suitable elevation and slope for smallholder forestry and land of various soil types. An expert group was used to assign numeric site suitabilities to the soil types and maps of site suitability were used to assist the selection of municipalities for the provision of extension assistance to smallholders. Modelling of the datasets was facilitated by recent developments of the ArcGIS® suite of computer programs and derivation of elevation and slope was assisted by the availability of digital elevation models (DEM) produced by the Shuttle Radar Topography (SRTM) mission. The usefulness of GIS software as a decision support tool for small-scale forestry extension programs is discussed.

Project to investigate improving literacy and numeracy outcomes of distance education students in the early years of schooling

The project was commissioned to investigate and analyse the issue of effective support for distance education students in the early years of school to maximise literacy and numeracy outcomes. The scope of this project was limited to students living in rural and remote areas who are undertaking education at home and who are in their early years of schooling. For the purpose of this project, the early years are conceptualised as the first three years of formal compulsory schooling in each of the States and Territories. There were a number of key tasks for the project which included: 1. Examining of the role of home tutors/supervisors This included interviewing personnel from the State and Territory distance education providers as well as the principals, teachers, home tutors and children. 2. Describing literacy and numeracy teaching and learning, and the use of information and communication technologies (ICT) in distance education This aspect of the project involved a critical review and analysis of relevant literature and reports in the last five years, and a consideration of the new initiatives that had been implemented in the States and Territories in the last two years. 3. The development of resources Through examination of the role of home tutors/supervisors, and an examination of literacy and numeracy and the use of technology in distance education, three resources were developed: ● A guide for home tutors/supervisors and schools of distance education about effective intervention and assessment strategies to support students’ learning and to assist the home tutors/supervisors in implementing ICT to support the development of literacy and numeracy in the early years. ● A calendar of activities for literacy and numeracy that would act as a stimulus for integrated and authentic activity for young children. ● An embryonic website of resources for the stakeholders in rural and distance education that might act as a catalyst for future resource building and sharing. In this way the final key task of the project, which was to create a context for a strategic dissemination plan, was realised when a strategy to address effective dissemination of the findings of the project so as to maximise their usefulness for the relevant groups was achieved.

Employee adjustment to large-scale organisational change

The present study was designed to test the utility of a stress-coping model of employee adjustment to organisational change. Specifically, it was proposed that employee adjustment to this type of work stress would be influenced by the characteristics of the change situation, employees' appraisals of the situation, their coping strategies, and the extent of their personal resources. Data were collected from 140 middle managers and supervisors involved in a large-scale public sector integration. The results of the research provided some support for the proposed model: high levels of psychological distress were related to a reliance on informal sources of information, high appraised stress, low appraised certainty, and the use of avoidant rather than problem-focused strategies, whereas poor social functioning was associated with low self-esteem, high levels or disruption across the period of change, a reliance on informal sources of information, and the use of avoidant coping strategies. There was no evidence that coping strategies mediated the effects of the event characteristics, situational appraisals, and personal resources on adjustment; however, there was some evidence linking these variables to coping strategies, in particular, problem-focused coping. There was also some evidence to indicate that the experience of organisational change was different for managers and supervisors: levels of threat were higher for the managers than the supervisors, but there was no difference between the groups of employees in terms of adjustment.

Structural analysis and molecular model of a self-incompatibility RNase from wild tomato

Self-incompatibility RNases (S-RNases) are an allelic series of style glycoproteins associated with rejection of self-pollen in solanaceous plants. The nucleotide sequences of S-RNase alleles from several genera have been determined, but the structure of the gene products has only been described for those from Nicotiana alata. We report on the N-glycan structures and the disulfide bonding of the S-3-RNase from wild tomato (Lycopersicon peruvianum) and use this and other information to construct a model of this molecule. The S-3-RNase has a single N-glycosylation site (Asn-28) to which one of three N-glycans is attached. S-3-RNase has seven Cys residues; six are involved in disulfide linkages (Cys-16-Cys-21, Cys-46-Cys-91, and Cys-166-Cys-177), and one has a free thiol group (Cys-150). The disulfide-bonding pattern is consistent with that observed in RNase Rh, a related RNase for which radiographic-crystallographic information is available. A molecular model of the S-3-RNase shows that four of the most variable regions of the S-RNases are clustered on one surface of the molecule. This is discussed in the context of recent experiments that set out to determine the regions of the S-RNase important for recognition during the self-incompatibility response.

An experimental study of the effects of work stress, work control, and task information on adjustment

The present study was designed to examine the main and interactive effects of task demands, work control, and task information on levels of adjustment. Task demands, work control, and task information were manipulated in an experimental setting where participants completed a letter-sorting activity (N = 128). Indicators of adjustment included measures of positive mood, participants' perceptions of task performance, and task satisfaction. Results of the present study provided some support for the main effects of objective task demands, work control, and task information on levels of adjustment. At the subjective level of analysis, there was some evidence to suggest that work control and task information interacted in their effects on levels of adjustment. There was minimal support for the proposal that work control and task information would buffer the negative effects of task demands on adjustment. There was, however, some evidence to suggest that the stress-buffering role of subjective work control was more marked at high, rather than low, levels of subjective task information.

Likelihood-based estimation of the regression model with scrambled responses

A significant problem in the collection of responses to potentially sensitive questions, such as relating to illegal, immoral or embarrassing activities, is non-sampling error due to refusal to respond or false responses. Eichhorn & Hayre (1983) suggested the use of scrambled responses to reduce this form of bias. This paper considers a linear regression model in which the dependent variable is unobserved but for which the sum or product with a scrambling random variable of known distribution, is known. The performance of two likelihood-based estimators is investigated, namely of a Bayesian estimator achieved through a Markov chain Monte Carlo (MCMC) sampling scheme, and a classical maximum-likelihood estimator. These two estimators and an estimator suggested by Singh, Joarder & King (1996) are compared. Monte Carlo results show that the Bayesian estimator outperforms the classical estimators in almost all cases, and the relative performance of the Bayesian estimator improves as the responses become more scrambled.

On modifications to the long-term survival mixture model in the presence of competing risks

A mixture model for long-term survivors has been adopted in various fields such as biostatistics and criminology where some individuals may never experience the type of failure under study. It is directly applicable in situations where the only information available from follow-up on individuals who will never experience this type of failure is in the form of censored observations. In this paper, we consider a modification to the model so that it still applies in the case where during the follow-up period it becomes known that an individual will never experience failure from the cause of interest. Unless a model allows for this additional information, a consistent survival analysis will not be obtained. A partial maximum likelihood (ML) approach is proposed that preserves the simplicity of the long-term survival mixture model and provides consistent estimators of the quantities of interest. Some simulation experiments are performed to assess the efficiency of the partial ML approach relative to the full ML approach for survival in the presence of competing risks.

RWMODEL II: Computer simulation of the Rescorla-Wagner model of Pavlovian conditioning

RWMODEL II simulates the Rescorla-Wagner model of Pavlovian conditioning. It is written in Delphi and runs under Windows 3.1 and Windows 95. The program was designed for novice and expert users and can be employed in teaching, as well as in research. It is user friendly and requires a minimal level of computer literacy but is sufficiently flexible to permit a wide range of simulations. It allows the display of empirical data, against which predictions from the model can be validated.

A model of specification-based testing of interactive systems

In this paper we present a model of specification-based testing of interactive systems. This model provides the basis for a framework to guide such testing. Interactive systems are traditionally decomposed into a functionality component and a user interface component; this distinction is termed dialogue separation and is the underlying basis for conceptual and architectural models of such systems. Correctness involves both proper behaviour of the user interface and proper computation by the underlying functionality. Specification-based testing is one method used to increase confidence in correctness, but it has had limited application to interactive system development to date.

A comparative mental health literacy survey of psychiatrists and other mental health professionals in Singapore

Objective: The objectives of this study are, first, to replicate and extend an Australian approach to assessing mental health literacy by studying a sample of Singapore mental health professionals, and to focus on differences between judgements made by the psychiatrists in comparison with the other mental health professionals. Second, to compare the psychiatrists' judgements with those of Australian psychiatrists. Method: The Australian questionnaire, assessing responses in relation to vignettes of major depression and to schizophrenia was extended by adding a third vignette of mania, and by the addition of several region-specific response options. Nearly 500 questionnaires were distributed to representative staff (psychiatrists, nurses and allied health) of a large psychiatric institution in Singapore, with a response rate of 81%. Psychiatrists' judgements were compared with all other hospital staff, and with Australian psychiatrists' judgements. Results: The two principal contrast groups (Singapore psychiatrists and other Singapore mental health professionals) differed slightly in terms of diagnostic accuracy. The psychiatrists differed in favouring a more professionally focused model of intervention, while both professional groups viewed traditional healers and their practices as distinctly unhelpful. Direct comparison of psychiatrist ratings generated in Singapore and in Australia revealed quite similar response profiles. Conclusions: In addition to generating data of some intrinsic importance, comparison with Australian survey data allows the potential impact of regional and cultural differences, as well as of varying psychiatric practices, to be identified. Responses identified more similarities than differences in the judgements of the psychiatrists from the two countries.

A context noise model of episodic word recognition

Item noise models of recognition assert that interference at retrieval is generated by the words from the study list. Context noise models of recognition assert that interference at retrieval is generated by the contexts in which the test word has appeared. The authors introduce the bind cue decide model of episodic memory, a Bayesian context noise model, and demonstrate how it can account for data from the item noise and dual-processing approaches to recognition memory. From the item noise perspective, list strength and list length effects, the mirror effect for word frequency and concreteness, and the effects of the similarity of other words in a list are considered. From the dual-processing perspective, process dissociation data on the effects of length, temporal separation of lists, strength, and diagnosticity of context are examined. The authors conclude that the context noise approach to recognition is a viable alternative to existing approaches.

An agent-based approach to modelling driver route choice behaviour under the influence of real-time information

This paper presents an agent-based approach to modelling individual driver behaviour under the influence of real-time traffic information. The driver behaviour models developed in this study are based on a behavioural survey of drivers which was conducted on a congested commuting corridor in Brisbane, Australia. Commuters' responses to travel information were analysed and a number of discrete choice models were developed to determine the factors influencing drivers' behaviour and their propensity to change route and adjust travel patterns. Based on the results obtained from the behavioural survey, the agent behaviour parameters which define driver characteristics, knowledge and preferences were identified and their values determined. A case study implementing a simple agent-based route choice decision model within a microscopic traffic simulation tool is also presented. Driver-vehicle units (DVUs) were modelled as autonomous software components that can each be assigned a set of goals to achieve and a database of knowledge comprising certain beliefs, intentions and preferences concerning the driving task. Each DVU provided route choice decision-making capabilities, based on perception of its environment, that were similar to the described intentions of the driver it represented. The case study clearly demonstrated the feasibility of the approach and the potential to develop more complex driver behavioural dynamics based on the belief-desire-intention agent architecture. (C) 2002 Elsevier Science Ltd. All rights reserved.