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The Satin Bowerbird Optimisation (SBO) was inspired by the Satin Bowerbirds living in Australia's rainforests and other mesic habitats. Like other meta-heuristic algorithms, the main problem faced by the SBO is that it has been empirically demonstrated to become easily trapped into local optimal solutions, creating low precision and slow convergence speeds. To overcome these deficiencies, we propose herein the Adaptive Chaotic Satin Bowerbird Optimisation algorithm (AC-SBO). Within the AC-SBO algorithm, a chaotic map is introduced to modify the search process, with which to enhance global convergence speeds, and to obtain better performance. We introduced the chaos theory into the SBO optimisation process, in order to replace the main parameter's greatest step size ( α), which assists in controlling the balance between both exploration and exploitation. The search accuracy and performance of the AC-SBO algorithm were verified on ten classical benchmark functions. In addition, in the experimental CEC2014 results showed that for almost all functions, the AC-SBO technique proved superior to the other comparative algorithms optimisations. The Wilcoxon rank-sum statistical test was performed in order to judge the significance of the results, and further demonstrated the improved performance of the proposed AC-SBO algorithm. [ABSTRACT FROM AUTHOR]

There is a growing concern around the dependency of news organisations on platforms like Facebook for audience traffic. However, scholars are still working out the extent of this dependency and how it manifests in practice. In this article, we draw on interviews with Australian news professionals and industry fieldwork to provide a nuanced account of this phenomenon. We find that news media organisations have recently started to diversify their distribution strategies and the business models associated with them in response to Facebook's algorithm changes. While Facebook remains important, we suggest that greater attention needs to be paid to the complex relationships that news organisations have with platforms. This article ends by considering the implications of these findings for international policy discussions centred around the prospect of platform regulation. [ABSTRACT FROM AUTHOR]

The utility of inertial measurement units (IMUs) for sporting skill and performance analysis during training and competition is advantageous for enhancing the objectivity of athlete monitoring. This study aimed to classify Australian Rules football (AF) kick types in an applied environment using ankle-mounted IMUs. IMUs and video capture of a controlled protocol, including four kick types at varying distances, were recorded during a single testing session with female AF athletes (n = 20). Processed IMU data were modelled using support vector machine classifier, random forest, and k-nearest neighbour algorithms under a 2-Kick, 4-Kick, and kick distance (10, 20, 30 m) conditions. The random forest model showed the highest results for overall classification accuracy (83% 2-Kick and 80% 4-Kick), test F1-score (0.76 2-Kick and 0.81 4-Kick), and AUC score (0.58 2-Kick and 0.60 4-Kick). Kick distance classification showed a model test and class weighted F1-score of 0.63 and overall accuracy of 64%, respectively. This study highlights the potential for an applied semi-automated AF training kick detection and type classification system using IMUs. [ABSTRACT FROM AUTHOR]

Background and aims: Clinical staff are typically poor at predicting alcohol dependence treatment outcomes. Machine learning (ML) offers the potential to model complex clinical data more effectively. This study tested the predictive accuracy of ML algorithms demonstrated to be effective in predicting alcohol dependence outcomes, compared with clinical judgement and traditional linear regression. Design Prospective study. ML models were trained on 1016 previously treated patients (training‐set) who attended a hospital‐based alcohol and drug clinic. ML models (n = 27), clinical psychologists (n = 10) and a 'traditional' logistic regression model (n = 1) predicted treatment outcome during the initial treatment session of an alcohol dependence programme. Setting: A 12‐week cognitive behavioural therapy (CBT)‐based abstinence programme for alcohol dependence in a hospital‐based alcohol and drug clinic in Australia. Participants: Prospective predictions were made for 220 new patients (test‐set; 70.91% male, mean age = 35.78 years, standard deviation = 9.19). Sixty‐nine (31.36%) patients successfully completed treatment. Measurements Treatment success was the primary outcome variable. The cross‐validated training‐set accuracy of ML models was used to determine optimal parameters for selecting models for prospective prediction. Accuracy, sensitivity, specificity, area under the receiver operator curve (AUC), Brier score and calibration curves were calculated and compared across predictions. Findings The mean aggregate accuracy of the ML models (63.06%) was higher than the mean accuracy of psychologist predictions (56.36%). The most accurate ML model achieved 70% accuracy, as did logistic regression. Both were more accurate than psychologists (P < 0.05) and had superior calibration. The high specificity for the selected ML (79%) and logistic regression (90%) meant they were significantly (P < 0.001) more effective than psychologists (50%) at correctly identifying patients whose treatment was unsuccessful. For ML and logistic regression, high specificity came at the expense of sensitivity (26 and 31%, respectively), resulting in poor prediction of successful patients. Conclusions: Machine learning models and logistic regression appear to be more accurate than psychologists at predicting treatment outcomes in an abstinence programme for alcohol dependence, but sensitivity is low. [ABSTRACT FROM AUTHOR]

Background: Competing risk models used for midpregnancy prediction of preterm pre‐eclampsia have shown detection rates (DR) of 85%, at fixed false‐positive rate (FPR) of 10%. The full algorithm used between 19+0 and 24+6 weeks includes maternal factors, mean arterial pressure (MAP), mean uterine artery pulsatility index (UtAPI), serum placental growth factor (PlGF) level in multiples of the median (MoM), and soluble Fms‐like tyrosine kinase‐1 (sFlt‐1) level in MoM. Aims: To assess performance of the Fetal Medicine Foundation (FMF) algorithm at midpregnancy to screen for preterm (<37 weeks) pre‐eclampsia. The outcome measured was preterm pre‐eclampsia. Materials and Methods: This is a prospective study including singleton pregnancies at 19–22 weeks gestation. Maternal bloods were collected and analysed using three different immunoassay platforms. Maternal characteristics, medical history, MAP, mean UtAPI, serum PlGF MoM and serum sFlt‐1 MoM were used for risk assessment. DR and FPR were calculated, and receiver operating characteristic curves produced. Results: Five hundred and twelve patients were included. Incidence of preterm pre‐eclampsia was 1.6%. Using predicted risk of pre‐eclampsia of one in 60 or more and one in 100 or higher, as given by the FMF predictive algorithm, the combination with the best predictive performance for preterm pre‐eclampsia included maternal factors, MAP, UtAPI and PlGF MoM, giving DRs of 100% and 100%, respectively, and FPRs of 9.3 for all platforms and 12.9–13.5, respectively. Addition of sFlt‐1 to the algorithm did not appear to improve performance. sFlt‐1 MoM and PlGF MoM values obtained on the different platforms performed very similarly. Conclusions: Second trimester combined screening for preterm pre‐eclampsia by maternal history, MAP, mean UtAPI and PlGF MoM using the FMF algorithm performed very well in this patient population. [ABSTRACT FROM AUTHOR]

In this article, a continuous terminal sliding mode control algorithm is proposed for servo motor systems. A novel full-order terminal sliding mode surface is proposed based on the bilimit homogeneous property, such that the sliding motion is finite-time stable independent of the system's initial condition. A new continuous terminal sliding mode control algorithm is proposed to guarantee that the system states reach the sliding surface in finite-time. Not only the robustness is guaranteed by the proposed controller but also the continuity makes the control algorithm more suitable for the servo mechanical systems. Finally, a numerical example is presented to depict the advantages of the proposed control algorithm. An application in the rotary servo system is done to validate the effectiveness of the proposed control strategy. [ABSTRACT FROM AUTHOR]

Objective: Convolutional neural networks are a subclass of deep learning or artificial intelligence that are predominantly used for image analysis and classification. This proof-of-concept study attempts to train a convolutional neural network algorithm that can reliably determine if the middle turbinate is pneumatised (concha bullosa) on coronal sinus computed tomography images. Method: Consecutive high-resolution computed tomography scans of the paranasal sinuses were retrospectively collected between January 2016 and December 2018 at a tertiary rhinology hospital in Australia. The classification layer of Inception-V3 was retrained in Python using a transfer learning method to interpret the computed tomography images. Segmentation analysis was also performed in an attempt to increase diagnostic accuracy. Results: The trained convolutional neural network was found to have diagnostic accuracy of 81 per cent (95 per cent confidence interval: 73.0–89.0 per cent) with an area under the curve of 0.93. Conclusion: A trained convolutional neural network algorithm appears to successfully identify pneumatisation of the middle turbinate with high accuracy. Further studies can be pursued to test its ability in other clinically important anatomical variants in otolaryngology and rhinology. [ABSTRACT FROM AUTHOR]

The impact of university rankings has driven scholars to increase productivity, and expanding collaboration has dramatically changed the publishing patterns in the academic publication system. The aim of this study was to develop a scholar classification scheme from publication patterns in academic science. Classification schemes are ways of describing groups that display different clusters of behaviors, approaches, or perspectives, and useful in the development of typologies. In this research, sample data are selected from three representative universities, considered a leading university, a middle‐tier university, and a noncomprehensive university. A final set of 11,427 effective scholars and their 284,128 journal publication records were used to develop the classification scheme via cluster analysis. The results identify six types of scholars, labeled as: singleton (8%), small‐team low performer (16%), small‐team high performer (17%), big‐team strategist (22%), free‐style follower (21%), and life‐time warrior (17%). These six scholar types demonstrate different approaches to publishing that can be used to understand both individual and research team performance across different institutional settings. Additionally, possible future work was identified that uses the scholar classification scheme to define the behavior for agents in an agent‐based model to simulate the strategic‐behavior‐driven academic publication system. [ABSTRACT FROM AUTHOR]

Aim: As a sample of research outputs supported by the nutrition and dietetics profession in Australia, the present study aimed to conduct a content analysis of Dietitians Association of Australia (DAA) conference abstracts to identify themes, methods and contribution by geographical location over time. Methods: Conference abstracts published during the period 2008‐2018 (excluding those from the International Congress of Dietetics in 2012) were obtained. Key outcome data including topics of research and methodological approach were extracted. Leximancer, a computer‐assisted content analysis program, was used in the development of concept maps. Thematic analysis was undertaken independently by two authors and consensus was obtained. Results: A total of 2246 oral and poster presentation abstracts and 56 plenary abstracts were imported and synthesised. The most commonly utilised research designs were cross‐sectional studies and evaluation research. There was a significant increase in the proportion of systematic literature reviews, and a decreasing proportion of randomised controlled trials presented across the study period. Output was greatest from authors in Queensland and New South Wales. A clear spike in abstracts was observed for the host state across all years. Since 2015 concept maps appeared more interconnected, suggesting a trend for research focus towards integrated nutrition topics. Overarching themes for emerging research topics included Indigenous nutrition and the curriculum for dietetics education. Food/foods emerged as a theme across multiple research methods and in a wide range of contexts and settings. Conclusions: The synthesis of findings suggests that research presented at the DAA conference is largely practice driven. [ABSTRACT FROM AUTHOR]

Australian northwest cloudbands (NWCBs) are continental-scale bands of continuous cloud that stretch from northwest to southeast Australia. In earlier studies, where the characteristics of NWCBs and their relationship with precipitation were identified from satellite imagery, there was considerable uncertainty in the results due to limited quality and availability of data. The present study identifies NWCBs from 31 years of satellite data using a pattern-matching algorithm. This new climatology is the longest record based entirely on observations. Our findings include a strong annual cycle in NWCB frequency, with a summer maximum and winter minimum, and a statistically significant increase in annual NWCB days over the period 1984–2014. Physical mechanisms responsible for NWCB occurrences are explored to determine whether there is a fundamental difference between summer and winter NWCBs as hypothesized in earlier studies. Composite analyses are used to reveal that a key difference between these is their genesis mechanisms. Whereas summer NWCBs are triggered by cyclonic disturbances, winter NWCBs tend to form when meridional sea surface temperature gradients trigger baroclinic instability. It was also found that while precipitation is enhanced over parts of Australia during a cloudband day, it is reduced in other regions. During a cloudband day, precipitation extremes are more likely over northwest, central, and southeast Australia, while the probability of extreme precipitation decreases in northeast and southwest Australia. Additionally, cold fronts and NWCBs can interact, leading to enhanced rainfall over Australia. [ABSTRACT FROM AUTHOR]

The purpose was to develop a foot image capture and measurement system with web cameras (the 3-FIS) to provide reliable and valid foot anthropometric measures with efficiency comparable to that of the conventional method of using a handheld anthropometer. Eleven foot measures were obtained from 10 subjects using both methods. Reliability of each method was determined over 3 consecutive days using the intraclass correlation coefficient and root mean square error (RMSE). Reliability was excellent for both the 3-FIS and the handheld anthropometer for the same 10 variables, and good for the fifth metatarsophalangeal joint height. The RMSE values over 3 days ranged from 0.9 to 2.2 mm for the handheld anthropometer, and from 0.8 to 3.6 mm for the 3-FIS. The RMSE values between the 3-FIS and the handheld anthropometer were between 2.3 and 7.4 mm. The 3-FIS required less time to collect and obtain the final variables than the handheld anthropometer. The 3-FIS provided accurate and reproducible results for each of the foot variables and in less time than the conventional approach of a handheld anthropometer. [ABSTRACT FROM AUTHOR]

Many Aboriginal Community Controlled Health Services (ACCHS) embrace Facebook as an organisational tool to share positive stories, which counter the negative narrative surrounding Aboriginal issues. However, the Facebook algorithm prioritises posts on personal pages over organisations. To take advantage of the algorithm, this project paid three Yolŋu employees of a north-east Arnhem Land ACCHS to share quit smoking messages on their personal Facebook pages. Smoking prevalence among Aboriginal and Torres Strait Islander Australians is nearly three-fold higher than non-Indigenous Australians, and previous research has identified the need for culturally appropriate communication approaches to accelerate the decline in Indigenous smoking. This research found Yolŋu participants nurtured healthy behaviours through compassionate non-coercive communications, in contrast to fear-inducing health warnings prevalent in tobacco control. Cultural tailoring of tobacco control messages was achieved by having trusted local health staff sharing, and endorsing, messages regardless of whether the content was Indigenous specific. This research also revealed online Facebook activity does not reflect the reach of posts, which may extend beyond social media users to individuals who do not have a Facebook profile. [ABSTRACT FROM AUTHOR]

Why do issues "fade" from the problem stream? This is an important but underresearched question, which this article examines by looking at the dynamic interaction between frames and frame sponsors. We develop a novel methodological approach that combines algorithmic coding (topic modelling) with hand-coding to track changes in the presence of frames and frame sponsors during periods of intense problematisation ("problem windows") both within continuous contexts and diachronically across different contexts. We apply this approach empirically in a corpus of newspaper articles that pertain to the coal seam gas controversy in Australia – a divisive policy issue where frame conflicts are common. We find that elite actors have a particularly decisive impact on the problem stream in terms of both the evolution and duration of debate. Further, problem windows close in response to three different mechanisms: elite frame convergence; public statements (by government and industry); and elections. [ABSTRACT FROM AUTHOR]

Introduction: The detection of harmful alcohol use and the delivery of brief advice in primary care are less than optimal. Given limited health care resources, deciding where best to allocate funding to optimize health outcomes is imperative. A simple data-based tool could be useful when access to specialist health economic advice is unavailable. This study aimed to examine the utility of a simple data-based calculator to facilitate priority setting in general practice for reducing alcohol-related harm.Methods: A simple algorithm was developed within Microsoft Excel to allow comparison of hypothetical intervention scenarios that aimed to increase detection and brief advice for harmful alcohol use in general practice. The calculator accommodated varying implementation costs, size of effect and reach for each scenario created. The incremental costs of the intervention scenarios, the incremental number of successes (i.e. abstinence or drinking at safe levels) and the incremental costs-effectiveness ratio (ICER) were calculated for each hypothetical scenario and compared with a usual care scenario.Results: In the hypothetical scenarios modelled, increasing both the detection of harmful alcohol consumption and the provision of brief advice produced the greatest number of incremental successes above baseline. Increasing detection alone produced fewer incremental successes but was the most cost-effective approach, as indicated by the lowest ICER.Discussion: The data-based calculator provides a simple method of exploring reach and cost-effectiveness outcomes without the need for any specific skills. Although this approach has limitations, the calculator can be used by decision makers to guide intervention planning. [ABSTRACT FROM AUTHOR]

Pulmonary arterial hypertension is an important cause of death and disability in patients with systemic sclerosis (SSc). Yearly screening of all SSc patients with transthoracic echocardiography (TTE) is recommended in international guidelines and currently utilised by the Australian Scleroderma Interest Group (ASIGSTANDARD). Owing to the limitations of TTE, the ASIG developed a new screening algorithm (ASIGPROPOSED) utilising a serum biomarker, NT‐proBNP, in place of TTE, which has been shown to be equally accurate as the current algorithm. The aim of this study was to compare the cost of these two algorithms using different scenarios. The new algorithm resulted in significant yearly cost savings of between AU$42 913.35 and AU$84 570 in screening and diagnosis of an Australian cohort which, if extrapolated to the Australian population, would result in a yearly cost saving of between AU$367 066 and AU$725 564. There was no scenario in which the proposed algorithm did not result in a cost saving. [ABSTRACT FROM AUTHOR]

This study cross validates the radar reflectivity Z; the rainfall drop size distribution parameter (median volume diameter Do); and the rainfall rate R estimated from the Tropical Rainfall Measuring Mission (TRMM) satellite Precipitation Radar (PR), a combined PR and TRMM Microwave Imager (TMI) algorithm (COM), and a C-band dual-polarized ground radar (GR) for TRMM overpasses during the passage of tropical cyclone (TC) and non-TC events over Darwin, Australia. Two overpass events during the passage of TC Carlos and 11 non-TC overpass events are used in this study, and the GR is taken as the reference. It is shown that the correspondence is dependent on the precipitation type whereby events with more (less) stratiform rainfall usually have a positive (negative) bias in the reflectivity and the rainfall rate, whereas in the Do the bias is generally positive but small (large). The COM reflectivity estimates are similar to the PR, but it has a smaller bias in the Do for most of the greater stratiform events. This suggests that combining the TMI with the PR adjusts the Do toward the "correct" direction if the GR is taken as the reference. Moreover, the association between the TRMM estimates and the GR for the two TC events, which are highly stratiform in nature, is similar to that observed for the highly stratiform non-TC events (there is no significant difference), but it differs considerably from that observed for the majority of the highly convective non-TC events. [ABSTRACT FROM AUTHOR]

With incomplete data, the "missing at random" (MAR) assumption is widely understood to enable unbiased estimation with appropriate methods. While the need to assess the plausibility of MAR and to perform sensitivity analyses considering "missing not at random" (MNAR) scenarios has been emphasized, the practical difficulty of these tasks is rarely acknowledged. With multivariable missingness, what MAR means is difficult to grasp, and in many MNAR scenarios unbiased estimation is possible using methods commonly associated with MAR. Directed acyclic graphs (DAGs) have been proposed as an alternative framework for specifying practically accessible assumptions beyond the MAR-MNAR dichotomy. However, there is currently no general algorithm for deciding how to handle the missing data given a specific DAG. Here we construct "canonical" DAGs capturing typical missingness mechanisms in epidemiologic studies with incomplete data on exposure, outcome, and confounding factors. For each DAG, we determine whether common target parameters are "recoverable," meaning that they can be expressed as functions of the available data distribution and thus estimated consistently, or whether sensitivity analyses are necessary. We investigate the performance of available-case and multiple-imputation procedures. Using data from waves 1–3 of the Longitudinal Study of Australian Children (2004–2008), we illustrate how our findings can guide the treatment of missing data in point-exposure studies. [ABSTRACT FROM AUTHOR]

Objectives: The assessment and management of a patient who refuses medical treatment requires clinical skill, and consideration of the relevant law and the patient's decision-making capacity. Psychiatrists are often asked to advise in these situations. We aimed to develop an algorithm describing the relevant legal pathways to assist clinicians, especially psychiatrists, working in New South Wales (NSW), Australia.Methods: We reviewed the academic literature on treatment refusal, relevant legislation, judicial rulings and NSW Health policy directives and guidelines. We consulted with clinicians and representatives of relevant tribunals.Results: We developed an algorithm for managing patients who refuse medical treatment in NSW. The algorithm emphases the evaluation of decision-making capacity and tracks separate pathways depending upon a person's status under the Mental Health Act 2007 (NSW).Conclusions: The algorithm provides a clear decision tree for clinicians responding to a patient refusing medical treatment in NSW. [ABSTRACT FROM AUTHOR]

Abstract: Background: Electronic health (eHealth) decision support tools have the potential to: facilitate inflammatory bowel disease (IBD) self‐management, reduce health care utilisation and alleviate the pressure on overburdened outpatient clinics. The purpose of this study was to explore the perspectives of key stakeholders on the potential use of a decision support tool for IBD patients. Methods: A qualitative study using focus group methodology was conducted at a tertiary IBD centre in Melbourne, Australia in February 2015. Key stakeholders, including physicians, nurses and patients, were included in the study. Two independent reviewers undertook inductive coding and generated themes. Results: In total, 31 participants were included in the study (including 16 males; 11 physicians; 6 nurses). An eHealth decision support tool was thought to be beneficial to facilitate IBD self‐management. Four themes emerged: (i) Framework for the decision support tool – the tool should be an adjunct to current models of care and facilitate shared decision‐making and patient engagement; (ii) Target population – stable patients with mild to moderate disease; (iii) Functionalities of the intervention – a web‐based platform encompassing patient‐reported outcomes, objective markers of disease and clinical algorithms based on international guidelines; and (iv) Design and Implementation – patients should be involved in the design. Conclusions: eHealth interventions are thought to be an important strategy to facilitate self‐management for patients with IBD. A multi‐stage iterative approach should be adopted in the design and implementation process of eHealth interventions. Patient perspectives need to be sought prior to and throughout the development of an eHealth decision support tools for IBD. [ABSTRACT FROM AUTHOR]

Identifying and targeting those at greatest risk will likely play a significant role in developing the most efficient and cost-effective sexually transmissible infections (STI) prevention programs. We aimed to develop a risk prediction algorithm to identify those who are at increased risk of STI. A cohort (N = 2320) of young sexually active Aboriginal and Torres Strait Islander people (hereafter referred to as Aboriginal people) were included in this study. The primary outcomes were self-reported high-risk sexual behaviors and past STI diagnosis. In developing a risk algorithm, our study population was randomly assigned to either a development (67%) or an internal validation data set (33%). Logistic regression models were used to create a risk prediction algorithm from the development data set for males and females separately. In the risk prediction models, older age, methamphetamine, ecstasy, and cannabis use, and frequent alcohol intake were all consistently associated with high-risk sexual behaviors as well as with a past STI diagnosis; identifying as gay/bisexual was one of the strongest factors among males. Those who had never tested for STIs, 52% (males) and 66% (females), had a risk score >15, and prevalence of undiagnosed STI was estimated between 30 and 40%. Since universal STI screening is not cost-effective, nor practical in many settings, targeted screening strategies remain a crucial and effective approach to managing STIs among young Aboriginal people. Risk prediction tools such as the one developed in this study may help in prioritizing screening for STIs among those most at risk. [ABSTRACT FROM AUTHOR]

Background: Missing data is a common problem in epidemiological studies, and is particularly prominent in longitudinal data, which involve multiple waves of data collection. Traditional multiple imputation (MI) methods (fully conditional specification (FCS) and multivariate normal imputation (MVNI)) treat repeated measurements of the same time-dependent variable as just another 'distinct' variable for imputation and therefore do not make the most of the longitudinal structure of the data. Only a few studies have explored extensions to the standard approaches to account for the temporal structure of longitudinal data. One suggestion is the two-fold fully conditional specification (two-fold FCS) algorithm, which restricts the imputation of a time-dependent variable to time blocks where the imputation model includes measurements taken at the specified and adjacent times. To date, no study has investigated the performance of two-fold FCS and standard MI methods for handling missing data in a time-varying covariate with a non-linear trajectory over time - a commonly encountered scenario in epidemiological studies.Methods: We simulated 1000 datasets of 5000 individuals based on the Longitudinal Study of Australian Children (LSAC). Three missing data mechanisms: missing completely at random (MCAR), and a weak and a strong missing at random (MAR) scenarios were used to impose missingness on body mass index (BMI) for age z-scores; a continuous time-varying exposure variable with a non-linear trajectory over time. We evaluated the performance of FCS, MVNI, and two-fold FCS for handling up to 50% of missing data when assessing the association between childhood obesity and sleep problems.Results: The standard two-fold FCS produced slightly more biased and less precise estimates than FCS and MVNI. We observed slight improvements in bias and precision when using a time window width of two for the two-fold FCS algorithm compared to the standard width of one.Conclusion: We recommend the use of FCS or MVNI in a similar longitudinal setting, and when encountering convergence issues due to a large number of time points or variables with missing values, the two-fold FCS with exploration of a suitable time window. [ABSTRACT FROM AUTHOR]

Background One of the strategies proven most successful in curbing rising rates of childhood obesity involves targeting parents as agents of change. Prior studies have focused on what messages to communicate, but few have investigated how they should be communicated. Objective To identify the channels most effective for communicating with parents of overweight and obese children and understand whether their use of parenting information sources differs from others in the community. Design/setting This study utilizes data from the Longitudinal Study of Australian Children ( LSAC). Families were included if weight and height information was available for parents and children at three data collection points: Waves 1, 2 and 4 (collected 2004, 2006 and 2010, respectively, n = 5107). Analysis A priori and a posteriori segmentation methods identified groups of parents that were similar in the sources used to obtain information about parenting, and examined whether some segments were more likely to have obese children. Results Four segments were identified that differed in their information source use: the 'personal networks', 'books', 'official sources' and 'mixed approach' segments. The 'official sources' and 'mixed approach' segments were most likely to have obese children, and they used doctors, government/community organizations and friends to obtain information on parenting. These segments were also less educated and had lower employment. Conclusions Messages are most likely to reach families with obese children if communicated through doctors, government publications and community organizations. Further, messages targeting social groupings of parents will leverage the power of advice from friends, which is another valuable information source for this group. [ABSTRACT FROM AUTHOR]

Clinical practice guidelines (CPGs) have been shown to improve processes of care and health outcomes, but there is often a discrepancy between recommendations for care and clinical practice. This study sought to explore general practitioner (GP) attitudes towards CPGs, in general and specifically for osteoarthritis (OA), with the implications for translating OA care into practice. A self-administered questionnaire was conducted in January 2013 with a sample of 228 GPs inNewSouth Wales and South Australia. Seventy-nine GPs returned questionnaires (response rate 35%). Nearly all GPs considered that CPGs support decision-making in practice (94%) and medical education (92%). Very few respondents regarded CPGs as a threat to clinical autonomy, and most recognised that individual patient circumstances must be taken into account. Shorter CPG formats were preferred over longer and more comprehensive formats, with preferences being evenly divided among respondents for short, 2-3-page summaries, flowcharts or algorithms and single page checklists. GPs considered accessibility to CPGs to be important, and electronic formats were popular. Familiarity and use of The Royal Australian College of General PractitionersOAGuideline was poor, with most respondents either not aware of it (30%; 95% confidence interval (CI) 27 - 41%), had never used it (19%; 95% CI 12 - 29%) or rarely used it (34%; 95% CI 25-45%). If CPGs are to assist with the translation of evidence into practice, they must be easily accessible and in a format that encourages use. [ABSTRACT FROM AUTHOR]

Aim: The aim of this study was to examine the identification of Aboriginal children in multiple administrative datasets and how this may affect estimates of health and development.Methods: Data collections containing a question about Aboriginal ethnicity: birth registrations, perinatal statistics, Australian Early Development Census and school enrolments were linked to datasets recording developmental outcomes: national literacy and numeracy tests (National Assessment Program - Literacy and Numeracy), Australian Early Development Census and perinatal statistics (birthweight) for South Australian children born 1999-2005 (n = 13 414-44 989). Six algorithms to derive Aboriginal ethnicity were specified. The proportions of children thus quantified were compared for developmental outcomes, including those scoring above the national minimum standard in year 3 National Assessment Program - Literacy and Numeracy reading.Results: The proportion of Aboriginal children identified varied from 1.9% to 4.7% when the algorithm incremented from once to ever identified as Aboriginal, the latter using linked datasets. The estimates of developmental outcomes were altered: for example, the proportion of Aboriginal children who performed above the national minimum standard in year 3 reading increased by 12 percentage points when the algorithm incremented from once to ever identified as Aboriginal. Similar differences by identification algorithm were seen for all outcomes.Conclusions: The proportion of South Australian children identified as Aboriginal in administrative datasets, and hence inequalities in developmental outcomes, varied depending on which and how many data sources were used. Linking multiple administrative datasets to determine the Aboriginal ethnicity of the child may be useful to inform policy, interventions, service delivery and how well we are closing developmental gaps. [ABSTRACT FROM AUTHOR]

Background: Evidence-informed policymaking is more likely if organisations have cultures that promote research use and invest in resources that facilitate staff engagement with research. Measures of organisations' research use culture and capacity are needed to assess current capacity, identify opportunities for improvement, and examine the impact of capacity-building interventions. The aim of the current study was to develop a comprehensive system to measure and score organisations' capacity to engage with and use research in policymaking, which we entitled ORACLe (Organisational Research Access, Culture, and Leadership).Method: We used a multifaceted approach to develop ORACLe. Firstly, we reviewed the available literature to identify key domains of organisational tools and systems that may facilitate research use by staff. We interviewed senior health policymakers to verify the relevance and applicability of these domains. This information was used to generate an interview schedule that focused on seven key domains of organisational capacity. The interview was pilot-tested within four Australian policy agencies. A discrete choice experiment (DCE) was then undertaken using an expert sample to establish the relative importance of these domains. This data was used to produce a scoring system for ORACLe.Results: The ORACLe interview was developed, comprised of 23 questions addressing seven domains of organisational capacity and tools that support research use, including (1) documented processes for policymaking; (2) leadership training; (3) staff training; (4) research resources (e.g. database access); and systems to (5) generate new research, (6) undertake evaluations, and (7) strengthen relationships with researchers. From the DCE data, a conditional logit model was estimated to calculate total scores that took into account the relative importance of the seven domains. The model indicated that our expert sample placed the greatest importance on domains (2), (3) and (4).Conclusion: We utilised qualitative and quantitative methods to develop a system to assess and score organisations' capacity to engage with and apply research to policy. Our measure assesses a broad range of capacity domains and identifies the relative importance of these capacities. ORACLe data can be used by organisations keen to increase their use of evidence to identify areas for further development. [ABSTRACT FROM AUTHOR]

Time can be thought of as a resource that people need for good health. Healthy behaviour, accessing health services, working, resting and caring all require time. Like other resources, time is socially shaped, but its relevance to health and health inequality is yet to be established. Drawing from sociology and political economy, we set out the theoretical basis for two measures of time relevant to contemporary, market-based societies. We measure amount of time spent on care and work (paid and unpaid) and the intensity of time, which refers to rushing, effort and speed. Using data from wave 9 (N = 9177) of the Household, Income and Labour Dynamics of Australia Survey we found that time poverty (> 80 h per week on care and work) and often or always rushing are barriers to physical activity and rushing is associated with poorer self-rated and mental health. Exploring their social patterning, we find that time-poor people have higher incomes and more time control. In contrast, rushing is linked to being a woman, lone parenthood, disability, lack of control and work-family conflicts. We supply a methodology to support quantitative investigations of time, and our findings underline time's dimensionality, social distribution and potential to influence health. [ABSTRACT FROM AUTHOR]

Micro-sensors were used to quantify macro kinematics of classical cross-country skiing techniques and measure cycle rates and cycle lengths during on-snow training. Data were collected from seven national level participants skiing at two submaximal intensities while wearing a micro-sensor unit (MinimaxX™). Algorithms were developed identifying double poling (DP), diagonal striding (DS), kick-double poling (KDP), tucking (Tuck), and turning (Turn). Technique duration (T-time), cycle rates, and cycle counts were compared to video-derived data to assess system accuracy. There was good reliability between micro-sensor and video calculated cycle rates for DP, DS, and KDP, with small mean differences (Mdiff% = −0.2 ± 3.2, −1.5 ± 2.2 and −1.4 ± 6.2) and trivial to small effect sizes (ES = 0.20, 0.30 and 0.13). Very strong correlations were observed for DP, DS, and KDP for T-time (r = 0.87–0.99) and cycle count (r = 0.87–0.99), while mean values were under-reported by the micro-sensor. Incorrect Turn detection was a major factor in technique cycle misclassification. Data presented highlight the potential of automated ski technique classification in cross-country skiing research. With further refinement, this approach will allow many applied questions associated with pacing, fatigue, technique selection and power output during training and competition to be answered. [ABSTRACT FROM PUBLISHER]

The article offers information regarding airway education in intensive care medicine in Australia and New Zealand. It mentions that advanced airway management by College of Intensive Care Medicine (CICM) Fellows is relatively infrequent and that a majority of CICM Fellows support mandatory airway education in their continuing professional development (CPD3). It mentions information on use of CICO algorithms in intensive care.

Introduction and aims: Illicit methamphetamine (MA) use is an important public health concern. There is a dearth of knowledge about effective and cost-effective treatments for methamphetamine (MA) dependence in Australia. This article evaluates the cost-effectiveness of counselling as a treatment option for illicit MA use compared with no treatment option. Design and methods: Data are from 501 individuals recruited into Methamphetamine Treatment Evaluation Study (MATES). The population of MA users from MATES is extrapolated to a total number of 1000 MA users in the intervention group (counselling treatment) and control group (non-treatment group). A decision analytic model is developed that examines the costs and health outcomes [measures as quality adjusted life years (QALYs) gained] for the treatment and comparison group over a 3-year period. A societal perspective is adopted and model inputs are subject to sensitivity and uncertainty analysis to test the robustness of results to parameter variability. Results are discounted by using 3% discount rate and expressed in 2011 Australian dollars. Results: The incremental cost-effectiveness analysis suggests that counselling is a dominant health care intervention, i.e. saves money and is more effective than a do nothing intervention. The incremental difference in costs is −AU$18.36 million (95% CI −AU$22.80 million to −AU$14.31 million) and the incremental difference in QALY is 107 (95% CI −640 to 820) with a probability of 78.64% of counselling being a dominant and cost-effective treatment within the acceptable incremental cost-effectiveness ratio (ICER) of $63 832 per QALY in the Australian society. The results of the sensitivity analysis show that the ICER is most sensitive to change in five major inputs: baseline utility, utility at 3 months, dealing crime costs, property crime costs and fraud crime costs. Discussion and Conclusions: The economic evaluation of the cost-effectiveness of counselling for MA dependence, as a first cost-effectiveness study to assess psychosocial treatment options for MA dependence, shows that greater investment in this cost-effective strategy will produce significant cost-savings and improve health outcomes as well as improve a lot of externality issues associated with drug use. [ABSTRACT FROM AUTHOR]

Seasonal rainfall forecasts in Australia are issued based on concurrent sea surface temperature anomalies (SSTAs) using a Bayesian model averaging (BMA) approach. The SSTA fields are derived from the Predictive Ocean-Atmosphere Model for Australia (POAMA) initialized in the preceding season. This study investigates the merits of the rainfall forecasted using POAMA SSTAs in contrast to that forecasted using a multimodel combination of SSTAs derived using five existing models. In addition, seasonal rainfall forecasts derived from multimodel and POAMA SSTA fields are subsequently combined to obtain a single weighted forecast over Australia. These three forecasts are compared against 'idealized' forecasts where observed SSTAs are used instead of those predicted. The results indicate that while seasonal rainfall forecasts derived using multimodel-based SSTA indices offer improvements in selected seasons over a majority of grid cells in comparison to the case where a single SSTA model is used in two seasons, these improvements are not as significant as the improvements in the SSTA field that drive the rainfall forecasting model. The forecasts derived from the combination of multimodel and POAMA SSTA indices forecasts are found to offer greater improvements over the multimodel or the POAMA forecasts for a majority of grid cells in all seasons. It is also observed that these combined forecasts are touching the upper limits of forecastability, which are reached when observed SSTAs are used to forecast the rainfall. This suggests that further improvements in rainfall forecasting are only possible through the use of an improved forecasting algorithm, and not the driver (SSTA) information used in the current study. [ABSTRACT FROM AUTHOR]

This study of 1,601 students in the middle years of schooling (Grades 5-8, each student measured twice, 1 year apart) from 200 classrooms in 44 schools sought to identify factors explaining gains and declines in mathematics engagement at key transition points. In multilevel regression modeling, findings showed that compared with Grade 6 students (upper elementary; the reference category), students in Grades 7 (typically the first secondary school year) and 8 have significantly declined in mathematics engagement from their previous year. Notably, in further analyses, these declines were found to be related to student (particularly mathematics self-efficacy and valuing), home (parent valuing of mathematics and availability of a computer for mathematics), classroom (class-average achievement and perceived climate), and school (socio-economic status and ethnic composition) factors. Implications for research and practice are discussed. [ABSTRACT FROM PUBLISHER]

A number of antiviral agents used against Human Immunodeficiency Virus (HIV) infection and hepatitis B virus (HBV) mono or co-infection have been associated with real nephrotoxicity (including tenofovir disoproxil fumarate (TDF), atazanavir, indinavir and lopinavir) or apparent changes in renal function (e.g. cobicistat, ritonavir, rilpivirine and dolutegravir). Patients with HIV are at higher risk of acute and chronic renal dysfunction, so baseline assessment and ongoing monitoring of renal function is an important part of routine management of patients with HIV. Given the paucity of evidence in this area, we sought to establish a consensus view on how routine monitoring could be performed in Australian patients on ART regimens, especially those involving TDF. A group of nephrologists and prescribers (an HIV physician and a hepatologist) were assembled by Gilead to discuss practical and reasonable renal management strategies for patients particularly those on TDF-based combination regimens (in the case of those with HIV-infection) or on TDF-monotherapy (in the case of HBV-mono infection). The group considered which investigations should be performed as part of routine practice, their frequency, and when specialist renal referral is warranted. The algorithm presented suggests testing for serum creatinine along with plasma phosphate and an assessment of urinary protein (rather than albumin) and glucose. Here we advocate baseline tests of renal function at initiation of therapy. If creatinine excretion inhibitors (e.g. cobicistat or rilpivirine) are used as part of the ART regimen, we suggest creatinine is rechecked at 4 weeks and this value used as the new baseline. Repeat testing is suggested at 3-monthly intervals for a year and then at least yearly thereafter if no abnormalities are detected. In patients with abnormal baseline results, renal function assessment should be performed at least 6 monthly. In HBV mono-infected patients advocate that a similar testing protocol may be logical. [ABSTRACT FROM AUTHOR]

Objective. To determine the economic feasibility in Australian general practices of using a practice nurse (PN)-led care model of chronic disease management. Methods. A cost-analysis of item numbers from the Medicare Benefit Schedule (MBS) was performed in three Australian general practices, one urban, one regional and one rural. Patients (n =254; >18 years of age) with chronic conditions (type 2 diabetes, hypertension, ischaemic heart disease) but without unstable or major health problems were randomised into usual general practitioner (GP) or PN-led care for management of their condition over a period of 12 months. After the 12-month intervention, total MBS item charges were evaluated for patients managed for their stable chronic condition by usual GP or PN-led care. Zero-skewness log transformation was applied to cost data and log-linear regression analysis was undertaken. Results. There was an estimated A$129 mean increase in total MBS item charges over a 1-year period (controlled for age, self-reported quality of life and geographic location of practice) associated with PN-led care. The frequency of GP and PN visits varied markedly according to the chronic disease. Conclusions. Medicare reimbursements provided sufficient funding for general practices to employ PNs within limits of workloads before the new Practice Nurse Incentive Program was introduced in July 2012. [ABSTRACT FROM AUTHOR]

Study design:Cross-section design.Objectives:The development of reliable screen technology for predicting those at risk of depression in the long-term remains a challenge. The objective of this research was to determine factors that classify correctly adults with spinal cord injury (SCI) with depressed mood and to develop a diagnostic algorithm that could be applied for prediction of depressed mood in the long-term.Setting:SCI rehabilitation unit, rehabilitation outpatient clinic and Australian community.Methods:Participants included 107 adults with SCI. The assessment regimen included demographic and injury variables, negative mood states, pain intensity, health-related quality of life and self-efficacy. Participants were divided into those with 'normal' mood versus those with elevated depressed mood. Discriminant function analysis (DFA) was then used to isolate factors that in combination, best classify the presence or absence of depressed mood.Results:At the time of assessment, 24 participants (22.4%) had elevated depressed mood. DFA identified six factors that discriminated between those with depressed mood (P<0.01) and those with normal mood, explaining 61% of the variance. Factors consisted of pain intensity, mental health, emotional and social functioning, self-efficacy and fatigue. DFA correctly classified 91.7% (n=22 of 24) of those with depressed mood and 95.2% (n=79 of 83) of those without. Demographic, injury and physical health function variables were not found to discriminate depressed mood.Conclusion:Clinical implications of applying a diagnostic algorithm for detecting depression in adults with SCI are discussed. Prospective research is needed to test the predictive efficacy of the algorithm. [ABSTRACT FROM AUTHOR]

Unpaid volunteers occupy many roles and provide crucial services in countries around the world. In Australia, for example, volunteers provide emergency response capabilities to most communities outside of major population centres. Despite the valuable function of this volunteer workforce, evidence indicates declining numbers of volunteer emergency service workers, and suggests that interactions between volunteering and family are implicated in falling numbers. The current study considered volunteering as one component of the community microsystem, and examined volunteering-related Work- Family Conflict ( WFC) and Work- Family Facilitation ( WFF) in N = 682 Australian volunteer firefighters. Structural equation modelling ( SEM) analysis indicated that brigade operational demands had a negative indirect effect on intention to remain through volunteer WFC, as well as a concurrent positive effect on satisfaction. Two volunteering resources were considered (training opportunities and effective leadership), and had positive impacts on volunteer WFF through perceived developmental gain. Although developmental gain had a large positive impact on volunteer satisfaction, volunteer WFF did not. Results indicate that theoretical models of interactions between paid work and family can inform understanding of interactions between voluntary work and family, and thus links between community and family roles. Implications for volunteer emergency services organisations are discussed. [ABSTRACT FROM AUTHOR]

Background:Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) is a risk prediction algorithm that can be used to compute estimates of age-specific risk of breast cancer. It is uncertain whether BOADICEA performs adequately for populations outside the United Kingdom.Methods:Using a batch mode version of BOADICEA that we developed (BOADICEACentre), we calculated the cumulative 10-year invasive breast cancer risk for 4176 Australian women of European ancestry unaffected at baseline from 1601 case and control families in the Australian Breast Cancer Family Registry. Based on 115 incident breast cancers, we investigated calibration, discrimination (using receiver-operating characteristic (ROC) curves) and accuracy at the individual level.Results:The ratio of expected to observed number of breast cancers was 0.92 (95% confidence interval (CI) 0.76-1.10). The E/O ratios by subgroups of the participant's relationship to the index case and by the reported number of affected relatives ranged between 0.83 and 0.98 and all 95% CIs included 1.00. The area under the ROC curve was 0.70 (95% CI 0.66-0.75) and there was no evidence of systematic under- or over-dispersion (P=0.2).Conclusion:BOADICEA is well calibrated for Australian women, and had good discrimination and accuracy at the individual level. [ABSTRACT FROM AUTHOR]

A 9-yr dataset of continuous sea noise recording made at the Cape Leeuwin station of the Comprehensive Nuclear-Test-Ban Treaty hydroacoustic network in 2002-2010 was processed to detect calls from pygmy blue whales and to analyze diurnal, seasonal, and interannual variations in their vocal activity. Because the conventional spectrogram correlation method for recognizing whale calls in sea noise resulted in a too high false detection rate, alternative algorithms were tested and the most robust one applied to the multi-year dataset. The detection method was based on multivariate classification using two spectrogram features of transients in sea noise and Fisher's linear discriminant, which provided a misclassification rate of approximately 1% for missed and false detections at moderate sensitivity settings. An analysis of the detection results revealed a consistent seasonal pattern in the whale presence and considerable interannual changes with a steady increase in the number of calls detected in 2002-2006. An apparent diurnal pattern of whales' vocal activity was also observed. The acoustic detection range for pygmy blue whales was estimated to vary from about 50 km to nearly 200 km from the Cape Leeuwin station, depending on the ambient noise level, source level, and azimuth to a vocalizing whale. [ABSTRACT FROM AUTHOR]

The proposition that a relatively new technology such as a differential evolutionary algorithm (DEA) can violate the weak form of the efficient market hypothesis is tested using daily data from the Australian share market from 2000 until 2008. An option trading strategy based on forecasts from a DEA is shown to perform better than a buy and hold strategy over parts of the sample space and, on average, over all of it. Speculators may make supernormal profits using new methodologies however such profits are unlikely to be sustained. [ABSTRACT FROM AUTHOR]

We develop a new linearly-constrained recursive total least squares adaptive filtering algorithm by incorporating the linear constraints into the underlying total least squares problem using an approach similar to the method of weighting and searching for the solution (filter weights) along the input vector. The proposed algorithm outperforms the previously proposed constrained recursive least square (CRLS) algorithm when both input and output data are observed with noise. It also has a significantly smaller computational complexity than CRLS. Simulations demonstrate the efficacy of the proposed algorithm. [ABSTRACT FROM PUBLISHER]

Background: The Brown Marmorated Stink Bug (BMSB), Halyomorpha halys (Stål) (Hemiptera: Pentatomidae), native to Asia, is becoming an invasive species with a rapidly expanding range in North America and Europe. In the US, it is a household pest and also caused unprecedented damage to agriculture crops. Exploring its climatic limits and estimating its potential geographic distribution can provide critical information for management strategies. Methodology/Principals: We used direct climate comparisons to explore the climatic niche occupied by native and invasive populations of BMSB. Ecological niche modelings based on the native range were used to anticipate the potential distribution of BMSB worldwide. Conversely, niche models based on the introduced range were used to locate the original invasive propagates in Asia. Areas with high invasion potential were identified by two niche modeling algorithms (i.e., Maxent and GARP). Conclusions/Significance: Reduced dimensionality of environmental space improves native model transferability in the invade area. Projecting models from invasive population back to native distributional areas offers valuable information on the potential source regions of the invasive populations. Our models anticipated successfully the current disjunct distribution of BMSB in the US. The original propagates are hypothesized to have come from northern Japan or western Korea. High climate suitable areas at risk of invasion include latitudes between 30°-50° including northern Europe, northeastern North America, southern Australia and the North Island of New Zealand. Angola in Africa and Uruguay in South America also showed high climate suitability. [ABSTRACT FROM AUTHOR]

This article presents a brief survey of two-sided matching. We introduce the reader to the problem of two-sided matching in the context of the college admission model and explain two central requirements for a matching mechanism: stability and non-manipulability. We show how the frequently used 'Boston Mechanism' fails these key requirements and describe how an alternative, the Deferred Acceptance Algorithm, leads to stable matchings but fails to be non-manipulable in general. A third mechanism, the Top Trading Cycle, is efficient and non-manipulable when only one side of the match acts strategically. We also discuss some applications of matching theory. [ABSTRACT FROM AUTHOR]

The study aimed to examine the factor structure of the Obsessive Beliefs Questionnaire (OBQ), the most widely used measure of dysfunctional beliefs in obsessive—compulsive disorder (OCD). Multiple exploratory methods (exploratory factor analysis, cluster analysis by variable, multidimensional scaling) were used to examine the questionnaire. Confirmatory factor analyses were also performed in two large nonclinical samples from Australia (N = 1,234) and Israel ( N = 617). Our analyses suggested a four-factor solution with 38 items, where threat and responsibility formed separate dimensions (the “OBQ-TRIP”). This version had superior fit statistics across the two divergent confirmatory samples, when compared with four alternative models suggested by previous authors. Of the OBQ dimensions, the threat scale correlated most strongly with OCD symptom measures, even when controlling for depression. A short, 20-item version of the scale is offered for further study. Implications and limitations are discussed. [ABSTRACT FROM PUBLISHER]

In this study, the effectiveness of semi-active tuned mass dampers (STMDs) for the response control of a wind-excited tall building was investigated. To this end, a 76-storey, 306 m benchmark building proposed for the city of Melbourne, Australia was used. Across wind load, data from wind tunnel tests were employed as excitation. A variable damping device and a magnetorheological (MR) damper were used to compose STMDs. A groundhook control algorithm was used to appropriately modulate the damping force of the semi-active damper. The control performance of the STMD was compared to that of a sample TMD, an active TMD (ATMD) and a semi-active variable stiffness TMD. The robustness of the STMD was investigated through the uncertainty in the building's stiffness. This study also investigated whether each of the mass dampers could satisfy the design requirements and constraints. The numerical studies show that the STMD can reduce the structural responses similar to an ATMD, but with a significant reduction in power consumption. It is also shown that the STMD with a 50 kN capacity MR damper can effectively control a full-scale tall building subjected to wind excitation, and it can satisfy the design requirements and constraints of the benchmark problem. Copyright © 2010 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This research deals with an innovative methodology for optimising the coal train scheduling problem. Based on our previously published work, generic solution techniques are developed by utilising a ' toolbox' of standard well-solved standard scheduling problems. According to our analysis, the coal train scheduling problem can be basically modelled a Blocking Parallel- Machine Job- Shop Scheduling (BPMJSS) problem with some minor constraints. To construct the feasible train schedules, an innovative constructive algorithm called the SLEK algorithm is proposed. To optimise the train schedule, a three-stage hybrid algorithm called the SLEK- BIH- TS algorithm is developed based on the definition of a sophisticated neighbourhood structure under the mechanism of the Best- Insertion- Heuristic (BIH) algorithm and Tabu Search (TS) metaheuristic algorithm. A case study is performed for optimising a complex real-world coal rail system in Australia. A method to calculate the lower bound of the makespan is proposed to evaluate results. The results indicate that the proposed methodology is promising to find the optimal or near-optimal feasible train timetables of a coal rail system under network and terminal capacity constraints. [ABSTRACT FROM AUTHOR]

The stable marriage problem is a well-known problem of matching men to women so that no man and woman who are not married to each other both prefer each other. Such a problem has a wide variety of practical applications, ranging from matching resident doctors, to hospitals to matching students to schools. A well-known algorithm to solve this problem is the Gale-Shapley algorithm, which runs in quadratic time in the number of men/women. It has been proven that stable marriage procedures can always be manipulated. Whilst the Gale-Shapley algorithm is computationally easy to manipulate, we prove that there exist stable marriage procedures which are NP-hard to manipulate. We also consider the relationship between voting theory and stable marriage procedures, showing that voting rules which are NP-hard to manipulate can be used to define stable marriage procedures which are themselves NP-hard to manipulate. Finally, we consider the issue that stable marriage procedures like Gale-Shapley favour one gender over the other, and we show how to use voting rules to make any stable marriage procedure gender neutral. [ABSTRACT FROM AUTHOR]

Background: Accurate predictions of species distributions are essential for climate change impact assessments. However the standard practice of using long-term climate averages to train species distribution models might mute important temporal patterns of species distribution. The benefit of using temporally explicit weather and distribution data has not been assessed. We hypothesized that short-term weather associated with the time a species was recorded should be superior to long-term climate measures for predicting distributions of mobile species. Methodology: We tested our hypothesis by generating distribution models for 157 bird species found in Australian tropical savannas (ATS) using modelling algorithm Maxent. The variable weather of the ATS supports a bird assemblage with variable movement patterns and a high incidence of nomadism. We developed "weather" models by relating climatic variables (mean temperature, rainfall, rainfall seasonality and temperature seasonality) from the three month, six month and one year period preceding each bird record over a 58 year period (1950-2008). These weather models were compared against models built using long-term (30 year) averages of the same climatic variables. Conclusions: Weather models consistently achieved higher model scores than climate models, particularly for wide-ranging, nomadic and desert species. Climate models predicted larger range areas for species, whereas weather models quantified fluctuations in habitat suitability across months, seasons and years. Models based on long-term climate averages overestimate availability of suitable habitat and species' climatic tolerances, masking species potential vulnerability to climate change. Our results demonstrate that dynamic approaches to distribution modelling, such as incorporating organism-appropriate temporal scales, improves understanding of species distributions. [ABSTRACT FROM AUTHOR]

A methodology for determining the optimal spatial distribution of a river pollutant detection network using a geographic information system and genetic algorithms (GAs) is developed. Two case studies are investigated to evaluate the performance of the developed methodology: (1) a hypothesized river system consisting of only 11 reaches; (2) the Logan and Albert Rivers in Southeast Queensland. Plausible results are obtained, encouraging the possibility of applying GAs in designing a river monitoring network. [ABSTRACT FROM AUTHOR]

Clustering of cumulative grainsize distribution curves was trialled with the publicly available software program CLARA as a means of finding sediment samples and geographical areas or parts of the geological record with highly similar particle-size characteristics. CLARA proved effective for this purpose. Tests were made with large datasets from the shallow-marine environments of Sydney Harbour (Australia), Oronsay (Inner Hebrides, Scotland), and Darss Sill (Baltic Sea). CLARA has four possible configurations depending on choices of distance metric and standardisation. One configuration identified outliers and small groups of samples most dissimilar from others, a very useful function. A second configuration clustered cumulative curves in a geometrical fashion similar to manual clustering. Compared to CLARA, an entropy algorithm was several orders of magnitude slower and did not identify outliers. When smaller numbers of clusters were requested, cumulative curves with strongly opposite curvature were grouped by the entropy algorithm, and by CLARA for non-standardised (but not standardised) variables. This potential problem is removed for CLARA by initially forming more clusters than suggested by statistical methods, in conjunction with outlier detection and removal. Entropy and CLARA clustering of frequency distributions provided the best resolution of size modes, and best separation of overlapping size modes, but clustering of cumulative curves provided better overall groupings. However, CLARA is not suitable for direct clustering of all conceivable frequency distributions, a problem not occurring with the corresponding cumulative curves. [ABSTRACT FROM AUTHOR]