Sampling stored-product insect pests : a comparison of four statistical sampling models for probability of pest detection

Background: Developing sampling strategies to target biological pests such as insects in stored grain is inherently difficult owing to species biology and behavioural characteristics. The design of robust sampling programmes should be based on an underlying statistical distribution that is sufficiently flexible to capture variations in the spatial distribution of the target species. Results: Comparisons are made of the accuracy of four probability-of-detection sampling models - the negative binomial model,1 the Poisson model,1 the double logarithmic model2 and the compound model3 - for detection of insects over a broad range of insect densities. Although the double log and negative binomial models performed well under specific conditions, it is shown that, of the four models examined, the compound model performed the best over a broad range of insect spatial distributions and densities. In particular, this model predicted well the number of samples required when insect density was high and clumped within experimental storages. Conclusions: This paper reinforces the need for effective sampling programs designed to detect insects over a broad range of spatial distributions. The compound model is robust over a broad range of insect densities and leads to substantial improvement in detection probabilities within highly variable systems such as grain storage.

A statistical strategy to select optimal structural health monitoring data in operational modal analysis

Operational modal analysis (OMA) is prevalent in modal identifi cation of civil structures. It asks for response measurements of the underlying structure under ambient loads. A valid OMA method requires the excitation be white noise in time and space. Although there are numerous applications of OMA in the literature, few have investigated the statistical distribution of a measurement and the infl uence of such randomness to modal identifi cation. This research has attempted modifi ed kurtosis to evaluate the statistical distribution of raw measurement data. In addition, a windowing strategy employing this index has been proposed to select quality datasets. In order to demonstrate how the data selection strategy works, the ambient vibration measurements of a laboratory bridge model and a real cable-stayed bridge have been respectively considered. The analysis incorporated with frequency domain decomposition (FDD) as the target OMA approach for modal identifi cation. The modal identifi cation results using the data segments with different randomness have been compared. The discrepancy in FDD spectra of the results indicates that, in order to fulfi l the assumption of an OMA method, special care shall be taken in processing a long vibration measurement data. The proposed data selection strategy is easy-to-apply and verifi ed effective in modal analysis.

Development and use of risk adjusted statistical process control tools for the monitoring and improvement of clinical outcomes in interventional cardiology

This thesis explored the development of statistical methods to support the monitoring and improvement in quality of treatment delivered to patients undergoing coronary angioplasty procedures. To achieve this goal, a suite of outcome measures was identified to characterise performance of the service, statistical tools were developed to monitor the various indicators and measures to strengthen governance processes were implemented and validated. Although this work focused on pursuit of these aims in the context of a an angioplasty service located at a single clinical site, development of the tools and techniques was undertaken mindful of the potential application to other clinical specialties and a wider, potentially national, scope.

Improving the statistical preparation for measuring soil N2O flux by closed chamber

Nitrous oxide emissions from soil are known to be spatially and temporally volatile. Reliable estimation of emissions over a given time and space depends on measuring with sufficient intensity but deciding on the number of measuring stations and the frequency of observation can be vexing. The question of low frequency manual observations providing comparable results to high frequency automated sampling also arises. Data collected from a replicated field experiment was intensively studied with the intention to give some statistically robust guidance on these issues. The experiment had nitrous oxide soil to air flux monitored within 10 m by 2.5 m plots by automated closed chambers under a 3 h average sampling interval and by manual static chambers under a three day average sampling interval over sixty days. Observed trends in flux over time by the static chambers were mostly within the auto chamber bounds of experimental error. Cumulated nitrous oxide emissions as measured by each system were also within error bounds. Under the temporal response pattern in this experiment, no significant loss of information was observed after culling the data to simulate results under various low frequency scenarios. Within the confines of this experiment observations from the manual chambers were not spatially correlated above distances of 1 m. Statistical power was therefore found to improve due to increased replicates per treatment or chambers per replicate. Careful after action review of experimental data can deliver savings for future work.

Young children's statistical reasoning : a tale of two contexts

This thesis explored the knowledge and reasoning of young children in solving novel statistical problems, and the influence of problem context and design on their solutions. It found that young children's statistical competencies are underestimated, and that problem design and context facilitated children's application of a wide range of knowledge and reasoning skills, none of which had been taught. A qualitative design-based research method, informed by the Models and Modeling perspective (Lesh & Doerr, 2003) underpinned the study. Data modelling activities incorporating picture story books were used to contextualise the problems. Children applied real-world understanding to problem solving, including attribute identification, categorisation and classification skills. Intuitive and metarepresentational knowledge together with inductive and probabilistic reasoning was used to make sense of data, and beginning awareness of statistical variation and informal inference was visible.

Reconceptualizing statistical learning in the early years

This chapter argues for the need to restructure children’s statistical experiences from the beginning years of formal schooling. The ability to understand and apply statistical reasoning is paramount across all walks of life, as seen in the variety of graphs, tables, diagrams, and other data representations requiring interpretation. Young children are immersed in our data-driven society, with early access to computer technology and daily exposure to the mass media. With the rate of data proliferation have come increased calls for advancing children’s statistical reasoning abilities, commencing with the earliest years of schooling (e.g., Langrall et al. 2008; Lehrer and Schauble 2005; Shaughnessy 2010; Whitin and Whitin 2011). Several articles (e.g., Franklin and Garfield 2006; Langrall et al. 2008) and policy documents (e.g., National Council of Teachers ofMathematics 2006) have highlighted the need for a renewed focus on this component of early mathematics learning, with children working mathematically and scientifically in dealing with realworld data. One approach to this component in the beginning school years is through data modelling (English 2010; Lehrer and Romberg 1996; Lehrer and Schauble 2000, 2007)...

National survey of viruses in pastures of subterranean clover. II. Statistical methodology for large scale quantitative ELISA

Statistical methodology was applied to a survey of time-course incidence of four viruses (alfalfa mosaic virus, clover yellow vein virus, subterranean clover mottle virus and subterranean clover red leaf virus) in improved pastures in southern regions of Australia. -from Authors

Building indicators in media assistance; four ways evaluation reports present “change”

The international aid and development community has supported programs that aim to build the capacity of media professionals or contribute to an enabling environment throughout the past 20 years. However, two decades on from the first modern media assistance programs, the sector is still struggling to identify, measure and understand the changes effected by their programs. There are questions raised as to whether it is even feasible to identify impacts on society and governance. This paper draws on some preliminary findings from a comparative thematic analysis of 47 evaluation documents of media assistance programs. The aim of this analysis is to identify trends in impact evaluation practice in the media assistance field, as well as the strengths and weaknesses of different evaluation approaches. This paper presents four types of social change claims commonly presented in reports; hypothetical changes, introduction of new opportunities, concrete examples of immediate impacts, and analysis of ongoing social and political changes. Although these types may appear as a spectrum from weak to strong, the interactions are perhaps more accurately understood using metaphors such as building blocks. This paper explores these types in more detail and suggests that a robust set of impacts-types could be useful in developing more grounded theories of change and indicators.

Phytophotodermatitis : case reports of children presenting with blistering after preparing lime juice

Letter to the Editor We read with interest the case report entitled ‘‘Contact with fig tree sap: An unusual cause of burn injury’’ by Mandalia et al. [1] and would like to report our similar experience with phytophotodermatitis caused by lime juice. Phototoxic dermatitis is understandably easily confused with a burn, particularly when a patient presents with large blisters of unknown mechanism. At the Royal Children’s Hospital Burns Centre, this injury was treated in the same manner as a burn and is described here...

Controlled Monte Carlo data generation for statistical damage identification employing Mahalanobis squared distance

The use of Mahalanobis squared distance–based novelty detection in statistical damage identification has become increasingly popular in recent years. The merit of the Mahalanobis squared distance–based method is that it is simple and requires low computational effort to enable the use of a higher dimensional damage-sensitive feature, which is generally more sensitive to structural changes. Mahalanobis squared distance–based damage identification is also believed to be one of the most suitable methods for modern sensing systems such as wireless sensors. Although possessing such advantages, this method is rather strict with the input requirement as it assumes the training data to be multivariate normal, which is not always available particularly at an early monitoring stage. As a consequence, it may result in an ill-conditioned training model with erroneous novelty detection and damage identification outcomes. To date, there appears to be no study on how to systematically cope with such practical issues especially in the context of a statistical damage identification problem. To address this need, this article proposes a controlled data generation scheme, which is based upon the Monte Carlo simulation methodology with the addition of several controlling and evaluation tools to assess the condition of output data. By evaluating the convergence of the data condition indices, the proposed scheme is able to determine the optimal setups for the data generation process and subsequently avoid unnecessarily excessive data. The efficacy of this scheme is demonstrated via applications to a benchmark structure data in the field.

Impact of cognitive behaviour therapy via mail for cessation of benzodiazepine use : a series of case reports

Benzodiazepines are widely prescribed to manage sleep disorders, anxiety and muscular tension. While providing short-term relief, continued use induces tolerance and withdrawal, and in older users, increases the risk of falls. However, long-term prescription remains common, and effective interventions are not widely available. This study developed a self-managed cognitive behaviour therapy package for cessation of benzodiazepine use delivered to participants via mail (M-CBT) and trialled its effectiveness as an adjunct to a general practitioner (GP)-managed dose reduction schedule. In the pilot trial, participants were randomly assigned to GP management with immediate or delayed M-CBT. Significant recruitment and engagement problems were experienced, and only three participants were allocated to each condition. After immediate M-CBT, two participants ceased use, while none receiving delayed treatment reduced daily intake by more than 50%. Across the sample, doses at 12 months remained significantly lower than baseline, and qualitative feedback from participants was positive. While M-CBT may have promise, improved engagement of GPs and participants is needed for this approach to substantially impact on community-wide benzodiazepine use.

The 2013 creative industries statistical analysis for Western Australia

The Department of Culture and the Arts undertook the first mapping of Perth’s creative industries in 2007 in partnership with the City of Perth and the Departments of Industry and Resources and the Premier and Cabinet. The 2013 Creative Industries Statistical Analysis for Western Australia report has updated the mapping with the 2011 Census employment data to provide invaluable information for the State’s creative industries, their peak associations and potential investors. The report maps sector employment numbers and growth between the 2006 and 2011 Census in the areas of music, visual and performing arts, film, TV and radio, advertising and marketing, software and digital content, publishing, and architecture and design, which includes designer fashion.

An evaluation of medication review reports across different settings

Background There is a growing body of evidence which supports that a pharmacist conducted medication review increases the health outcomes for patients. A pharmacist integrated into a primary care medical centre may offer many potential advantages in conducting medication reviews in this setting however research describing this is presently limited. Objective To compare medication review reports conducted by pharmacists practicing externally to a medical centre to those medication review reports conducted by an integrated practice pharmacist. The secondary objective was to compare medication review reports conducted by pharmacists in the patient’s home to those conducted in the medical centre. Setting A primary care medical centre, Brisbane, Australia Method A retrospective analysis of pharmacist conducted medication reviews prior to and after the integration of a pharmacist into a medical centre. Main outcome measures Types of drug related problems identified by the Pharma cists, recommended intervention for drug related problems made by the pharmacist, and the extent of implementation of pharmacist recommendations by the general practitioner. Results The primary drug related problem reported in the practice pharmacist phase was Additional therapy required as compared to Precautions in the external pharmacist phase. The practice pharmacist most frequently recommended to add drug with Additional monitoring recommended most often in the external pharmacists. During the practice pharmacist phase 71 % of recommendations were implemented and was significantly higher than the external pharmacist phase with 53 % of recommendations implemented (p\0.0001). Two of the 23 drug related problem domains differed significantly when comparing medication reviews conducted in the patient’s home to those conducted in the medical centre.

Teachers' motivations for working in rural schools

This paper reports on the analysis of qualitative and quantitative data concerning Australian teachers’ motivations for taking up, remaining in, or leaving teaching positions in rural and regional schools. The data were collected from teachers (n = 2940) as part of the SiMERR National Survey, though the results of the qualitative data analysis were not published with the survey report in 2006. The teachers’ comments provide additional insight into their career decisions, complementing the quantitative findings. Content and frequency analyses of the teachers’ comments reveal individual and collective priorities which together with the statistical evidence can be used to inform policies aimed at addressing the staffing needs of rural schools.

Statistical modelling of district-level residential electricity use in NSW, Australia

Electricity network investment and asset management require accurate estimation of future demand in energy consumption within specified service areas. For this purpose, simple models are typically developed to predict future trends in electricity consumption using various methods and assumptions. This paper presents a statistical model to predict electricity consumption in the residential sector at the Census Collection District (CCD) level over the state of New South Wales, Australia, based on spatial building and household characteristics. Residential household demographic and building data from the Australian Bureau of Statistics (ABS) and actual electricity consumption data from electricity companies are merged for 74 % of the 12,000 CCDs in the state. Eighty percent of the merged dataset is randomly set aside to establish the model using regression analysis, and the remaining 20 % is used to independently test the accuracy of model prediction against actual consumption. In 90 % of the cases, the predicted consumption is shown to be within 5 kWh per dwelling per day from actual values, with an overall state accuracy of -1.15 %. Given a future scenario with a shift in climate zone and a growth in population, the model is used to identify the geographical or service areas that are most likely to have increased electricity consumption. Such geographical representation can be of great benefit when assessing alternatives to the centralised generation of energy; having such a model gives a quantifiable method to selecting the 'most' appropriate system when a review or upgrade of the network infrastructure is required.