Search

Mobility as a Service (MaaS) is seen as a transition from mobility being satisfied by a dominant car ownership model to a service model where mobility needs are met by a multimodal suite of services. The research environment of MaaS is heavily driven by the younger generation's travel behaviour which appears to be less dominated by car ownership (following the peak car literature) and by their interest in all things technological, particularly their smart phones. However, this paper is looking at a different but very specific segment of the population in Australia that have their accessibility provided by Community Transport (CT), focusing specifically on New South Wales (NSW) and Queensland (QLD). Arguably, this population segment is the complete antithesis of the younger generation in terms of chasing technological change but in other ways, for example, a lack of access to private cars, shows some similarities. This paper is motivated by likely changes in funding for CT providers. Currently CT providers receive a supply side subsidy but there are plans to introduce funding to be placed directly with clients, in the form of person centred funding (PCF). Clients will then have a single budget to purchase mobility along with other services they require. The paper investigates the mobility services which comprise bundles that CT clients would be willing to pay in the new era of PCF. Five participating CT providers from a cross section of operating areas recruited clients to take part in a stated choice experiment, processed by a computer assisted personal interview (CAPI). Advanced choice models are used to develop models using the behavioural data collected by the CAPI and estimates of a CT client's willingness to pay (WTP) for the MaaS bundle are presented. WTP provides a ceiling for pricing the elements within a MaaS bundle which is an important part of the CT providers' future strategy. The WTP estimates were much smaller than the CT providers' unit costs of providing the service. This poses a challenge for CT providers in the creation of mobiltiy bundles which cover costs, suggesting that the possible transition to PCF using MaaS bundles will not be an easy process and will require significant education as to the cost of provision. The paper concludes with some suggestions as to how CT providers could make the transition to PCF building on the evidence of this research. [ABSTRACT FROM AUTHOR]

Uncertainty of how fully automated vehicles (AVs) will interact with other road users, including vulnerable road users and other manual automated operated vehicles in towns is one major concern with introducing these vehicles. Based on Walker, Rahman, and Cave's (2001) adaptive policymaking model, this paper illustrates how the adaptive approach can be applied to trial fully automated private vehicles. Specifically, the focus is on policy elements which surround consumer acceptance and other road users' acceptability of private AVs. The State of Queensland, Australia was selected as the focus of this paper given that there are no current policies for fully AVs in this country. It is acknowledged, however, that similar frameworks may also be applied outside of Australia. This paper will also briefly discuss legislation barriers for trialling private AVs in Australia, whilst reviewing the regulations which have been introduced to overcome these barriers at an international level. It was concluded that private AV policymaking is required to be flexible in order to keep up with continued advancements in technology, both in Australia and beyond. • Case study of an adaptive approach for fully AVs in Australia and beyond. • Automated vehicle policymaking required to be flexible and adaptable to change. • Amendments to current legislation are required to facilitate on-road trials. [ABSTRACT FROM AUTHOR]

• Most of the injured adults had either short-term, low-dose or no opioid use following their injury hospitalisation. • Longer durations and higher doses of opioids were seen for those with pre-injury opioid use, more readmissions and surgeries. • If dispensing occurred prior to injury, duration increased 10-fold and oral morphine equivalents doubled. • Approximately 45 % of adults with pre-injury opioid use remained at a higher dose than they were pre-injury. • A small but concerning number of adults were diagnosed or treated as drug dependant over the two-year post-injury follow-up period. Despite a focus of opioid-related research internationally, there is limited understanding of long-term opioid use in adults following injury. We analysed data from the 'Community Opioid Dispensing after Injury' data linkage study. This paper aims to describe the baseline characteristics of the injured cohort and report opioid dispensing patterns following injury-related hospitalisations. Retrospective cohort study of adults hospitalised after injury (ICD-10AM: S00-S99, T00-T75) in Queensland, Australia between 1 January 2014 and 31 December 2015, prior to implementation of opioid stewardship programs. Data were person-linked between hospitalisation, community opioid dispensing and mortality collections. Data were extracted for 90-days prior to the index hospital admission, to establish opiate naivety, to 720 days after discharge. Median daily oral morphine equivalents (i.e., dose) were averaged for each 30-day interval. Cumulative duration of dispensing and dose were compared by demographic and clinical characteristics, stratified by drug dependency status. Of the 129,684 injured adults, 61.3 % had no opioids dispensed in the 2-year follow-up period. Adults having any opioids dispensed in the community (38.7 %) were more likely older, female, to have fracture injuries and injuries with a higher severity, compared to those with no opioids dispensed. Longer durations and higher doses of opioids were seen for those with pre-injury opioid use, more hospital readmissions and repeat surgeries, as well as those who died in the 2-year follow-up period. Median dispensing duration was 24-days with a median daily end dose of 13 oral morphine equivalents. If dispensing occurred prior to the injury, duration increased 10-fold and oral morphine equivalents doubled. Adults with a documented dependency prior to, or after, the injury had significantly longer durations of use and higher doses than the rest of the cohort receiving opioids. Approximately 7 % of the total cohort continued to be dispensed opioids at 2-years post injury. This is a novel population-level profile of opioid dispensing patterns following injury-related hospitalisation, described for the time period prior to the implementation of opioid stewardship programs and regulatory changes in Queensland. Detailed understanding of this pre-implementation period is critical for evaluating the impact of these changes moving forward. [ABSTRACT FROM AUTHOR]

The peak period of an energy-generating wave is one of the most important parameters that describe the spectral shape of the oceanic wave, as this indicates the duration for which the waves prevail with respect to their maximum extractable energy. In this paper, a half-hourly peak wave energy period (T P) forecast model is constructed using a suite of statistically significant lagged inputs based on the partial auto-correlation function with an extreme learning machine model developed and its predictive utility is benchmarked against deep learning models, i.e., convolutional neural network (CNN/CovNet) and recurrent neural network (RNN) models and other traditional M5tree, Conditional Maximization based Multiple Linear Regression (MLR-ECM) and MLR models. The objective model (ELM) vs. the comparison models (CNN, RNN, M5tree, MLR-ECM, and MLR) were trained and validated independently on the test dataset obtained from coastal zones of eastern Australia that have a high potential for implementation of wave energy generation systems. The outcomes ascertain that the ELM model can generate significantly accurate predictions of the half-hourly peak wave energy period, providing a good level of accuracy relative to deep learning models in selected coastal study zones. The study establishes the practical usefulness of the ELM model as being a noteworthy methodology for the applications in renewable and sustainable energy resource management systems. • A real-time peak wave energy period forecasting model is constructed using ELM model. • The advance ELM is benchmarked against a deep learning and other traditional models. • The advance ELM generates better predictions than deep learning models in this region. • ELM model provides significant energy management implications for ocean waves. [ABSTRACT FROM AUTHOR]

• Up to a half of motor vehicle suicides may be unreported. • Unreported and confirmed cases of motor vehicle suicide share many common factors. • Unreported cases of motor vehicle suicide had a higher prevalence of females and multiple vehicle truck impacts compared to confirmed cases. • Information pertaining to the driver's psychosocial history is missing or unavailable in many coroners reports of driver fatalities. • A standardised procedure for conducting a psychological autopsy for motor vehicle suicide, may increase the accuracy of reporting the cause of such crashes. While suicide is recognised as one of the leading causes of death in Australia, it is often presumed that fatal road crashes are primarily accidental in nature. However, international research has indicated that deliberate attempts at self-harm while driving may account for between 1.1% and 7.4% of road crashes. Despite the personal and financial costs associated with such events, few studies have examined the extent of motor vehicle suicides (MVS) or the circumstances surrounding such incidents in Australia. Given this, the current study reviewed coronial, police and toxicology findings of 762 motor vehicle fatalities in Queensland (Australia) during the period 2011 to 2015 to determine the frequency of confirmed cases and explore the prevalence (and characteristics) of possible MVS that remain undetected. In total, 22 confirmed cases were identified, and such events shared significant similarities with 14 possible events, including evidence of recent emotional upset, adversity and mental health diagnoses. In contrast, differences between the groups were limited to confirmed cases being more likely to involve males and contain a suicide note or evidence of past suicidality, while possible cases were more likely to involve a multiple vehicle impact with a truck. Importantly, crucial information regarding the deceased's psychological state and life circumstances (e.g., psychological autopsy) was not reported in many cases. Corresponding qualitative analysis of the coroners final determination (between the two groups) revealed the occurrence of the word suicide to occur seven times (31.8%) among confirmed cases and five times (35.7%) for possible casers. Furthermore, the coroners final determination of intent to suicide was open or undetermined in six of the possible cases (43%), which further suggests a reluctance (or procedural uncertainty) to categorically identify MVS. The paper further reviews the main findings, illuminates core challenges associated with identifying MVS and proposes a need for future investigations to incorporate a more standardised and evidence-based approach in order to effectively identify such events. [ABSTRACT FROM AUTHOR]

• A PV variability tolerant multifunctional control strategy for BESS is proposed. • Four control functions of BESS with possible user-defined extensions were formulated. • A use-case to control PV plant's power ramp rate is demonstrated using real data. • Validation is performed in real-time software-in-loop platform using real-field data. • Evaluation of proposed strategy shows the potential for real-world deployment. This paper proposes a multifunctional control strategy for battery energy storage systems (BESSs) in solar photovoltaic (PV) plants to avoid the unacceptable PV-power ramp-rate caused by PV variability. In addition to the PV variability tolerant ramp-rate control, the proposed multifunctional BESS control strategy is capable of maintaining a user-specified charging profile to store excess PV power while providing backup power support and charge maintenance, by accommodating diverse control functions time to time. Four control functions, namely, Rest (RST), Surplus Energy Storage (STR), Back-up Power Support (SPT) and Charge Maintenance (CMT) functions, are proposed in this article. Besides, extendibility of the proposed multifunctional strategy is presented by adding two action strategies – one with the STR function and another with the SPT function. Validation of the proposed control strategy is conducted by using real historical data from a utility-scale solar PV plant located in Queensland, Australia. Numerical analyses show that the strategy can successfully keep the PV ramp-rate within specified limit along with the user specified charge profile. Further, exploiting the real-field data, the proposed strategy is demonstrated through a real-time co-simulation study conducted in a MATLAB interfaced RSCAD-RTDS platform that can be used as Digital Twin (DT) for the PV plant. [ABSTRACT FROM AUTHOR]

• We work on multiple wild animals detection and pose estimation. • We constructed a large wild animal surveillance dataset. • We proposed a ratio based data distillation framework. Monitoring wildlife populations and activities have significance for biology and ecology. With the rapid development of computer vision and deep learning techniques, it is possible to employ state-of-the-art convoluntional neural network (CNN) based detectors to process the big data from field surveillance cameras and assist in the following studies. However, data labelling during the training stage is a very time-consuming, labour intensive and expensive task. In this paper, we detect multiple animals (Kangaroo, emu, dingo, bird and wildcat) in the wild in an Omni-supervised learning setting. The unlabeled data from the surveillance cameras will be filtered and used for training via data distillation approach. Moreover, we also perform joint pose estimation and detection for Kangaroo which has the most samples in the dataset. To study the feasibility, we also built a large full high definition (HD) wild animal surveillance image dataset from collected data from several national parks across the State of Queensland in Australia and this dataset will be made publicly available. Extensive experiments show that the detection and pose estimation results can be further improved by using unlabeled data wisely. [ABSTRACT FROM AUTHOR]

The study conceptualises water security indicators in the regional urban context for water security policy formulation and implementation. The paper used a Process Analysis Method (PAM) to develop and apply a set of Urban Water Security (UWS) indicators suitable for the regional urban water authorities. The UWS indicators were calibrated and validated by the relevant stakeholders of the northern, tropical, urban region of Queensland, Australia. Although the priorities for different regional cities vary, the indicators are expected to help water authorities monitor, measure and track their policy performance over time. • Regional cities are having their unique water supply security challenges. • Urban water supply Indicators designed with stakeholder consultation and verification. • Indicators are developed to support urban water supply policy formulation to improve water security. • Pilots the indicators in a regional urban water context. [ABSTRACT FROM AUTHOR]

Australia has long been observed to experience the ENSO (El Niño Southern Oscillation) of periodic alternation of flooding and drought. Australia has experienced consecutive years of the La Niña cycle of heavy rain and flooding. At some stage, this will revert to one or more years of drought, often severe. In previous years of drought, consideration was given to alternative water supply, including recycled wastewater. This paper reflects on the case of the previous period of El Niño drought in South East Queensland (SEQ), aiming to contribute to drought mitigation planning through reviving consideration of recycled water. • In depth case study on Queensland response to drought conditions. • Includes analysis of attempts to introduce other water sources, particularly recycled water for potable and non potable uses. • Examines reasons for failure and non-acceptance and uses comparisons with successful schemes to suggest policy changes for a way forward. [ABSTRACT FROM AUTHOR]

Abstract Young people with complex support needs who live outside metropolitan areas face unique challenges. Issues such as poor educational and employment opportunities, homelessness, racism, problematic substance use, challenging behaviour, disability and mental illness can be magnified and lead to judgment and marginalisation in small communities such as those in rural and regional areas. As a result of poor resourcing of services in these areas, young people may be forced to transition from place to place, service to service as a way of coping with life challenges. This paper presents findings from interviews and focus groups with service providers who support such young people in regional and rural Queensland, New South Wales and Victoria in Australia. Service providers reported similar challenges to professionals working in urban areas, such as navigating inter-agency and inter-professional work and dealing with funding shortages. However, these issues were amplified by the need to work across broad geographical areas, to recruit and retain skilled workers and to respond to the many structural and resource inadequacies in smaller communities. While services aimed to be responsive to young people, the challenges of providing support in a non-metropolitan context could create a context in which young people either disengaged from services or poor response resulted in systemic escalation to crisis. The implications for policy and practice are explored. Highlights • Supports to young people with complex support needs in non-metropolitan areas in Australia are poorly resourced. • Non-metropolitan services work best when they are based on relationship-based practice and local community needs. • Interagency collaboration is essential when working across broad geographical areas. [ABSTRACT FROM AUTHOR]

The approach and results of our 2019 paper (Brooke et al., 2019) have been criticised by Dougherty (2022). We examined the sensitivity of a tropical, coarse sand strandplain to changes in relative sea level as expressed through beach-ridge morphology and the elevation of beach berms preserved in the succession of cyclone-generated beach ridges at Cowley Beach, Queensland, Australia. Rather than presenting a new sea-level curve for this region as suggested by Dougherty, our 2019 study of the Cowley Beach strandplain revealed that when compared with the modelled Holocene relative sea-level record and sea-level indicator data for north-eastern Queensland, the strandplain morphology and stratigraphy provide a first-order representation of sea-level position. Importantly, Dougherty (2022) has overlooked the processes involved in the formation of beach ridges at this site and the spatial coverage of our analysis of the strandplain morphology. Both these factors are fundamental to the approach and conclusions of our 2019 paper. We reiterate here that the Cowley Beach strandplain morphology and succession of beach-berm deposits have elevation patterns that match well the broad trend in the regional relative sea-level model for the past 7 ka. We highlight those key beach-ridge formative processes and data limitations neglected in the Dougherty Comment. Finally, we note the challenges and opportunities for further research into the sedimentary records preserved in this distinctive type of tropical strandplain. • First-order changes of sea level can be detected in the Cowley Beach strandplain. • The coarse sandy ridges comprise a berm capped by cyclone-generated surge deposits. • Processes forming these ridges are in marked contrast to temperate strandplains. • There is negligible aeolian deposition contributing to these low-relief ridges. • Uncertainties in ridge elevation, age and GPR data limit sea-level reconstruction. [ABSTRACT FROM AUTHOR]

Background: In 2013 the Queensland Government introduced criminal association and mandatory sentencing laws for members of outlaw motorcycle gangs (OMCGs). Forms of "criminal association" or "anti-bikie" laws have been introduced in several Australian jurisdictions, and recent High Court decisions upholding their constitutionality will ensure that they remain part of our justice landscape. Generally, the aims of these laws are to declare a specific organisation as "criminal" and impose various legal orders and offences that thwart the consorting of members and address organised crime, such as unexplained wealth regimes. There have been significant criticisms of these styles of association laws both here and internationally. The aim of this research is to show the extent of involvement of OMCGs in the drug trade and associated organised crime activity, and whether anti-association laws are an effective response to this type of organised criminal activity.Methods: This paper relied on six years of data outlining the criminal activity of OMCGs from the Queensland Police Service (QPS) obtained under the legislative framework of The Queensland Right to Information Act (RTI) 2009. Information obtained from the Queensland Commission into Organised Crime (2015) and Queensland Taskforce into organised crime legislation (2015) was also used.Results: The data suggest that the role of OMCGs in the drug market has been overstated and is not as dominant as has been portrayed by government agencies and the popular media. Generally, OMCGs account for less than one percent of organised crime type activity. This is also true for drug type offences where OMCGs are responsible for less than one percent of offences. The findings show that the Queensland example has highlighted the ineffectiveness of the criminal association laws and the mandatory sentencing provisions in that they have had little impact on drug market activity and little success in the courts.Conclusion: The analysis presented here is twofold: an examination of the legal ramifications and an evaluation of the investigative utility of such laws from a policy evaluation standpoint. In both cases, there is little evidence to suggest that these laws are an effective or appropriate response. [ABSTRACT FROM AUTHOR]

Particulate matter (PM) or particle pollution include the tiny particles of dust and fly ash particles are expelled from coal-burning power plants. Coal combustion is an extremely prevalent source of air pollution, and resulting PM has substantial impacts on human health, especially in industrial zones. This paper aims to design a novel hybrid deep learning framework based on long short-term memory (LSTM) integrated with a two-stage data filtering technique to accurately predict the air quality indices (i.e., PM 2.5 and PM 10) in a chosen study region 'Miles Airport, Queensland,' that meets the needs of the coal seam gas industry in Australia. The data used to construct the novel hybrid two-stage data filtering technique based on LSTM comprising of six meteorological parameters (i.e., wind direction, wind speed, air temperature, relative humidity, solar radiation, and rainfall) and two environmental factors (i.e., ozone and total suspended particulate). In the first stage, two robust feature selection methods, namely, extreme gradient boosting (XGBoost) and the classification and regression tree (CART) approach, were adopted to explore the most significant predictors. Then in the second stage, the best subset regression (BSR) technique is utilized to determine the best subsets input combinations i.e., C1, C2, and C3 based on several particular metrics. The three BSR-based input combinations were employed in the LSTM model to estimate the PM 2.5 and PM 10. Furthermore, to validate the main hybrid framework, two advanced machine learning (ML) methods (i.e., LightGBM and ridge kernel regression (KRR)) and two traditional ML methods (i.e., Adaptive neuro-fuzzy inference system (ANFIS) and multilayer perceptron neural network (MLP)) were hybridized with the multi-level data filtering strategy by examining the optimal input combinations. Several statistical metrics, graphical tools, and diagnostic analyses evaluated the hybrid models. The outcomes of the PM 2.5 simulation based on 2375 data samples showed that the LSTM-C3 containing all the selected predictors yielded the most promising accuracy, followed by the LightGBM-C3 and MLP-C3 models. On the other hand, the simulation of PM 10 distribution demonstrated that the LSTM-C3 was superior to other models, followed by the KRR-C3 and LightGBM-C3 models. [ABSTRACT FROM AUTHOR]

• Women cycling patterns were observed in an innovative naturalistic study approach. • Proportions of women riders were similar (22 %) in road and off-road bicycle paths. • Greater likelihood of observing a woman rider on roads with cycling-friendly features. • Lower likelihood observed among road bike riders. • Greater likelihood observed during day hours, on weekends, and in group riding. Women are less likely to ride than men in low cycling countries such as Australia. In Australia, self-reported cycling participation appears to be declining, particularly for women. This paper examines the rider and road environment correlates of women's cycling. While most earlier studies relied on self-report data to understand gender differences in cycling, this study video-recorded 24,868 riders (22 % female) at 17 sites across Queensland, Australia. The probabilities of an observed rider being female under different circumstances (e.g., speed limit, riding location, time of riding, group riding) at these sites were modelled in a binomial logistic regression framework. The likelihood of a rider being a woman was greater during the day (9am-8pm) than the early morning (5–9 a.m.); on weekends than on weekdays; in groups of two or more riders than among single riders; in lower speed zones than speed zones of 60 km/h or over; on roads with bike lanes or multiple traffic lanes or raised medians than on roads without these, and in urban areas than suburban areas. The likelihood of the rider being a woman was lower among those riding road bikes than other types of bicycles. The use of a naturalistic study design marks the key strength of this paper. Findings of this study should help better understand women's cycling patterns and preferred cycling locations, which cycling communities and organisations can use to advocate for better roads and paths that make female riders feel safe. [ABSTRACT FROM AUTHOR]

This study proposes a new hybrid deep learning (DL) model, the called CSVR, for Global Solar Radiation (GSR) predictions by integrating Convolutional Neural Network (CNN) with Support Vector Regression (SVR) approach. First, the CNN algorithm is used to extract local patterns as well as common features that occur recurrently in time series data at different intervals. Then, the SVR is subsequently adopted to replace the fully connected CNN layers to predict the daily GSR time series data at six solar farms in Queensland, Australia. To develop the hybrid CSVR model, we adopt the most pertinent meteorological variables from Global Climate Model and Scientific Information for Landowners database. From a pool of Global Climate Models variables and ground-based observations, the optimal features are selected through a metaheuristic Feature Selection algorithm, an Atom Search Optimization method. The hyperparameters of the proposed CSVR are optimized by mean of the HyperOpt method, and the overall performance of the objective algorithm is benchmarked against eight alternative DL methods, and some of the other Machine Learning approaches (LSTM, DBN, RBF, BRF, MARS, WKNNR, GPML and M5TREE) methods. The results obtained shows that the proposed CSVR model can offer several predictive advantages over the alternative DL models, as well as the conventional ML models. Specifically, we note that the CSVR model recorded a root mean square error/mean absolute error ranging between ≈ 2.172–3.305 MJ m2/1.624–2.370 MJ m2 over the six tested solar farms compared to ≈ 2.514–3.879 MJ m2/1.939–2.866 MJ m2 from alternative ML and DL algorithms. Consistent with this predicted error, the correlation between the measured and the predicted GSR , including the Willmott's, Nash-Sutcliffe's coefficient and Legates & McCabe's Index was relatively higher for the proposed CSVR model compared to other DL and Machine Learning methods for all of the study sites. Accordingly, this study advocates the merits of CSVR model to provide a viable alternative to accurately predict GSR for renewable energy exploitation, energy demand or other forecasting-based applications. [Display omitted] • This paper presents a hybrid CSVR algorithm for global solar radiation prediction. • The proposed approach combines Convolutional Neural Network with a Support Vector Machine. • An Atom Search-based feature selection is applied to improve the performance of the system. • Experiments are carried out in data at six solar energy farms in Queensland, Australia. • The results show the efficacy of deep learning CSVR for solar energy prediction problems. [ABSTRACT FROM AUTHOR]

The sustainable in situ regeneration of microbial (biogenic) methane or microbially enhanced coal bed methane (‘MECoM’) is an emerging concept being investigated globally. Promising results and recommendations of a preliminary culture study of Walloon Subgroup co-produced coal seam gas (CSG) waters from the Surat Basin, Queensland established the presence of viable methanogens and suggested that in situ methanogenesis could be stimulated using physical and chemical reservoir treatments. This paper represents the culmination of a stepwise basin analysis project ultimately aimed at siting potential in situ bioreactor locations in the eastern Surat Basin. The integration of stratigraphically located data on the molecular and isotopic composition of desorbed gases, host coal properties and spatially associated waters through the core production zone has allowed the spatial variability and relative influence of hydro-geological factors on methanogenesis to be evaluated in detail for the first time. Higher gas contents and systematically enriched CH 4 and CO 2 carbon isotopic compositions in the stratigraphically central coal seams (oldest-youngest: in the upper Taroom Coal Measures, Tangalooma Sandstone lower Juandah Coal Measures) are best explained by increased rates of microbial CO 2 reduction and substrate depletion. There is a building case to trial MECoM in the central coal seams in a depleted/underperforming well in an area of high permeability. Integrated microbiological, chemical engineering, hydro-chemical and geological studies are ongoing to further enhance understanding of Walloon Subgroup CSG and the bioreactor potential of the Surat Basin. [ABSTRACT FROM AUTHOR]

Cardicola Short, 1953 is a genus of the Aporocotylidae Odhner, 1912 (Digenea), with 25 currently recognised species described from 32 species of Perciformes and Mugiliformes fishes around the world, including eight species from the Great Barrier Reef. Here, we describe two new species from this region, namely Cardicola beveridgei n. sp. from the ventricle and atrium of the mangrove jack, Lutjanus argentimaculatus (Forsskål) (Perciformes: Lutjanidae), and Cardicola bullardi n. sp. from the ventricle of the Australian spotted mackerel, Scomberomorus munroi Collette & Russo (Perciformes: Scombridae), from off Lizard Island, Queensland, Australia. These two new species are most easily distinguished from the 25 current members of Cardicola in having the combination of i) a spinous oral sucker, ii) an anteriorly intercaecal ovary, iii) a uterus that extends anteriorly from the oötype, iv) the number of spines per ventrolateral transverse row, and in v) body size and the length/width ratio, vi) the oesophagus and caecal length(s) relative to body total length, vii) the length of the posterior caeca relative to the anterior pair, viii) the testis length/width ratio and its total size relative to that of the body, ix) the postovarian field as a percentage of body length, and x) egg size. In addition, C. beveridgei n. sp. is further differentiated by possessing a female genital pore that opens anterodextral to the male pore while C. bullardi n. sp. differs further in possessing a testis that is almost entirely intercaecal and does not extend anteriorly to the level of the intestinal bifurcation. Employing genetic analysis of ITS2 rDNA sequence data, representing these species and a further 13 recognised and three putative species of Cardicola, we were able to unequivocally confirm these specimens as distinct (9-22% different over 420 nucleotide positions). Distance analysis of ITS2 showed that i) species of Cardicola from the Siganidae formed a monophyletic clade, to the exclusion of other Cardicola species reported from the Scombridae, Sparidae, Lutjanidae and Chaetodontidae, ii) a general phylogenetic isolation exists between the species of Cardicola reported from scombrid fishes, and iii) C. beveridgei n. sp. and Cardicola milleri Nolan & Cribb, 2006 from lutjanids and Cardicola chaetodontis Yamaguti, 1970 from chaetodontids are phylogenetically close, despite the evolutionary remoteness between the host groups and their highly disparate biology. Given the likelihood of many additional species being attributed to Cardicola, we predict that continued molecular analyses will indicate that this genus will prove to incorporate a series of radiations in association with particular fish taxa as well as evidence of host-switching. (Nucleotide sequences reported in this paper are available in the GenBank database under accession no. KF752497). [ABSTRACT FROM AUTHOR]

[Display omitted] • A low-cost sensor was developed for monitoring coal flotation performance. • The sensor measures drag exerted by the overflowing froth using two strain gauges. • Excellent diagnostic performance of the sensor was demonstrated by on-site trial. This paper presents a simple new sensor for real-time monitoring of coal flotation. The sensor was developed based on measurement of the drag exerted by the overflowing froth onto a cantilever beam. The effectiveness of this sensor for flotation monitoring was demonstrated by an on-site trial in a coking coal flotation plant in Queensland, Australia. The trial was carried out using one of the full-scale column flotation cells in the plant for five days, with the froth depth being fixed at 1.0 m but frother dosage and aeration rate being varied over a wide range. The output of the drag sensor had a strong linear correlation with the clean coal yield (mass recovery), with the coefficient of determination being 0.97. [ABSTRACT FROM AUTHOR]

• Developing a novel approach for using trip sequences instead of separate trips. • Developing a unique similarity measure for the trip sequences. • Focusing only on the temporal attributes of the trip sequences. • Running the method on real-world case studies. • Evaluating the performance of the developed method. • Comparing the outcome with the existing literature. • Achieving a considerable improvement in inferring the trip purpose. Smart card transactions are known as a rich and continuous source of public transit data, but they miss some important attributes about trips and passengers. One of these missing attributes is the trip purpose attribute. This paper proposes a novel method to infer the trip purpose attribute from the sequences of trips of passengers instead of separate trips. The proposed method infers the trip purpose attribute (a missing attribute in the smart card data) from the temporal attributes (available attributes in the smart card data). First, the relation between the temporal attributes and the trip purpose attribute is learnt by discovering clusters of passengers in the Household Travel Survey dataset while each passenger is represented by one sequence of trips. Then, the discovered clusters are utilized to infer the trip purpose of smart card transactions by allocating each passenger to the closest clusters. The proposed method is implemented on the smart card and HTS datasets from southeast Queensland, Australia. The evaluation results showed a considerable improvement in inferring the trip purpose compared to the results published in the literature. Notably, the effect of considering the trip sequence was more significant than considering land use variables. [ABSTRACT FROM AUTHOR]

Aboriginal and Torres Strait Islander children are disproportionately represented in the statutory child protection system across Australia. A strategy gaining traction to address this disproportionate representation is to recruit more Indigenous practitioners into statutory child protection work. However, the experiences of Indigenous people who undertake child protection work have not been explored thoroughly, particularly in an Australian research context. While it has been established in contemporary literature that exposure to trauma is an expected occupational hazard of undertaking statutory child protection work, the experience of racism as a potential source of traumatic stress for practitioners has not been explicitly explored. This paper reports on results from a recent doctoral study which explored the experiences of Indigenous child protection practitioners based in Queensland, Australia. This research relied on the stories of participants, shared through qualitative in-depth semi-structured interviews, to answer the primary research question: what are the experiences of Indigenous child protection workers? The findings emerged from a research design that was underpinned by critical theory and decolonisation frameworks, which placed the participants as experts of their own experiences. The experiences of the research participants tell the story of a deficiency within the statutory child protection system to meet the wellbeing needs of Indigenous workers and provide a workplace environment that is culturally safe. Participants described recurrent experiences of racist behaviour displayed by non-Indigenous colleagues and a lack of support that acknowledges the distinctive experience of Indigenous people who undertake child protection work. [ABSTRACT FROM AUTHOR]

Plutonium (Pu) interactions in the environment are highly complex. Site-specific variables play an integral role in determining the chemical and physical form of Pu, and its migration, bioavailability, and immobility. This paper aims to identify the key variables that can be used to highlight regions of radioecological sensitivity and guide remediation strategies in Australia. Plutonium is present in the Australian environment as a result of global fallout and the British nuclear testing program of 1952–1958 in central and west Australia (Maralinga and Montebello islands). We report the first systematic measurements of 239+240Pu and 238Pu activity concentrations in distal (≥1000 km from test sites) catchment outlet sediments from Queensland, Australia. The average 239+240Pu activity concentration was 0.29 mBq.g −1 (n = 73 samples) with a maximum of 4.88 mBq.g −1.238Pu/239+240Pu isotope ratios identified a large range (0.02–0.29 (RSD: 74%)) which is congruent with the heterogeneous nuclear material used for the British nuclear testing programme at Maralinga and Montebello Islands. The use of a modified PCA relying on non-linear distance correlation (dCorr) provided broader insight into the impact of environmental variables on the transport and migration of Pu in this soil system. Primary key environmental indicators of Pu presence were determined to be actinide/lanthanide/heavier transition metals, elevation, electrical conductivity (EC), CaO, SiO 2 , SO 3 , landform, geomorphology, land use, and climate explaining 81.7% of the variance of the system. Overall this highlighted that trace level Pu accumulations are associated with the coarse, refractive components of Australian soils, and are more likely regulated by the climate of the region and overall soil type. • 73 outlet catchment sediments analysed for 239+240Pu trace-level activity concentration. • Combined with a large national geochemical dataset to investigate the transport of Pu as a contaminant in the Australian soil surface. • Statistical analysis reveals linear and non-linear interrelationships between Pu activity and environmental variables. • Highlighted an association of Pu with the coarse, refractive components of the soils (heavy minerals). • Trace level Pu accumulations are more likely regulated by the climate of the region and overall soil type. [ABSTRACT FROM AUTHOR]

Domestic food waste (DFW) is an important policy issue because it represents inefficiencies in supply chains and consumption behaviour, creates pressures on urban landfills, and causes downstream environmental impacts such as greenhouse gas (GHG) emissions and odour from landfills. However, the evaluation of proposals to minimise or treat food waste, such as through separate disposal streams, is difficult because those impacts are not registered through normal market price signals. This paper presents non-market valuations for a hypothetical kerbside DFW collection service from a survey of households in two local government areas in the Central Queensland region, Australia. Choice modelling (CM) and contingent valuation methods (CVM) were employed to elicit potential participation and estimate willingness to pay (WTP) of the community for a domestic food waste collection service. Latent class analysis results for the sub-groups supporting an improvement option revealed that cost, odour and fortnightly collection frequency limit both WTP for and participation in the potential kerbside collection program. While there was support because it would extend the lifespans of the local landfills, potential reduction of methane emissions was not a strong driver. No difference in support or willingness to pay could be identified between the two local government populations. While the CVM results showed a WTP of $30.42 and a 58% participation rate for the proposed option, the latent class models showed that potential participation and willingness to pay varied across negative, indifference and positive sub-samples. This study provides a useful example of how a new policy option to improve waste management at a local area level might be evaluated, where the willingness to pay estimates can be factored into a benefit cost analysis and the estimates of likely support or opposition can be inputted into a political economy framework. • The study assessed household preferences to reduce domestic food waste. • Stated preference experiments were used to estimate WTP for reduction options. • Behavioural and attitudinal factors were important in explaining choices. • Two-stage contingent valuation models estimated both participation and WTP. • Latent class analysis models were used to classify responses to key attributes. [ABSTRACT FROM AUTHOR]

Greater public and professional awareness of the extent and impact of child sexual abuse (CSA) has prompted the inclusions of prevention initiatives within school curricula. However CSA education is not always soundly grounded in empirical evidence, and evaluations of the impact of programs often inadequate. This paper reports on a randomized-control trial of an empirically informed serious-game for CSA prevention, for children aged 8–10 years. The study also evaluates the impact on learning of complementary classroom lessons and part completion of the Orbit game. The evaluation involved 139 students (female = 78; male = 61) aged 8–10 years (Mage = 9.64, SD = 0.33), from an elementary school in Queensland , Australia. All children were pre-tested and post-tested (at 3 months) for knowledge of abuse prevention using the Children's Knowledge of Abuse Questionnaire-Revised (CKAQ-R-III), and a short form (SF) mapped to the learning objectives of Orbit. Children were assigned to one of three groups; i) play Orbit (n = 50); ii) play Orbit and CSA lessons (n = 55); and iii) control (n = 34). Children in the Orbit play, and Orbit play and lesson groups, significantly (p <.001) increased their CKAQ SF scores, whereas those in the control group did not. Furthermore, those children who completed all of Orbit significantly (p <.001) increased their post-test CKAQ scores, whereas those who didn't complete the game did not. This study shows the strength of a serious-games approach for school CSA prevention whilst reporting how child completion can impact learnings. [ABSTRACT FROM AUTHOR]

In-situ stress pattern and subsurface fractures control the production of Coal Seam Gas (CSG) reservoirs and, hence, comprehensive analyses are required for better development of these reservoirs. The Surat Basin is a prolific CSG province with major economic impacts in eastern Australia. Recent studies have reported significant stress variations in this basin due to local geological structures. However, a systematic analysis of localised stress perturbations within the basin, and their impacts on reservoir permeability have not been presented thus far in the published literature. In this paper, we combine different sets of data including conventional log data, wellbore image logs, 2D seismic lines and interpreted permeability (from well test data) in order to characterise the role of geological structures in the subsurface fluid flow of the Walloon Coal Measures in eastern Surat Basin. Analysis of 7.3 km of borehole image log across 33 vertical wells revealed a regional ENE-WSW orientation of the maximum horizontal stress (S Hmax) in the study area. However, there are massive variability in the S Hmax orientation, spatially and with depth. Analysis of 2D seismic lines highlight the role of geological structures in stress perturbation, and the interpretation of natural fractures using image logs show that most of the open fractures are oriented sub-parallel to the acute angle of local S Hmax orientation. Interpreted well test data in the study wells demonstrates that most of the high permeability data points are located where in-situ stress rotation is observed. This indicates the influence of local S Hmax orientation responding to geological structures on the subsurface fluid flow in the eastern part of the Surat Basin. • Variability of S Hmax orientation laterally and with depth. • Small scale geological structures control the local in-situ stress pattern. • Open fractures are oriented sub-parallel to the acute angle of local S Hmax orientation. • Most of the high permeability data points are located where in-situ stress rotation is observed. [ABSTRACT FROM AUTHOR]

• A two-stage stochastic programming model is developed to investigate the carbon emissions issue in cold supply chains under uncertain demand. • A matheuristic algorithm based on the Iterated Local Search (ILS) algorithm and a mixed integer programming is developed. • Optimal replenishment policies and transportation schedules are considered to minimize both operational and emissions costs. • The proposed model is applied to a real-world case study in Queensland, Australia. • It was found that high emissions price does not necessarily lead to an improvement in efficiency of the cold supply chain system. Increasing awareness of sustainability in supply chain management has prompted organizations and individuals to consider environmental impacts when managing supply chains. The issues concerning environmental impacts are significant in cold supply chains due to substantial carbon emissions from storage and distribution of temperature-sensitive product. This paper investigates the impact of carbon emissions arising from storage and transportation in the cold supply chain in the presence of carbon tax regulation, and under uncertain demand. A two-stage stochastic programming model is developed to determine optimal replenishment policies and transportation schedules to minimize both operational and emissions costs. A matheuristic algorithm based on the Iterated Local Search (ILS) algorithm and a mixed integer programming is developed to solve the problem in realistic sizes. The performance and robustness of the matheuristic algorithm are analyzed using test instances in various sizes. A real-world case study in Queensland, Australia is used to demonstrate the application of the model. The results highlight that higher emissions price does not always contribute to the efficiency of the cold supply chain system. Furthermore, the analyses indicate that using heterogeneous fleet including light duty and medium duty vehicles can lead to further cost saving and emissions reduction. [ABSTRACT FROM AUTHOR]

• A mathematical programming approach for the multi-action problem is proposed (MAMP). • A new MIP model that includes fragmentation penalty in actions (MAMP-E) is presented. • The models are applied to the Mitchell River basin in Queensland, Australia. • MIP models get shorter execution times and higher quality solutions. • The MAMP-E model obtains higher ecological benefits than the MAMP model. Planning for management actions that address threats to biodiversity is important for securing its long term persistence. However, systematic conservation planning (SCP) has traditionally overlooked this aspect and just focused on identifying priority areas without any recommendation on actions needed. This paper develops a mixed integer mathematical programming (MIP) approach for the multi-action management planning problem (MAMP), where the goal is to find an optimal combination of management actions that abate threats, in an efficient way while accounting for connectivity. An extended version of the MAMP model (MAMP-E) is also proposed that adds an expression for minimizing fragmentation between different actions. To evaluate the efficiency of the two models, they were applied to a case study corresponding to a large area of the Mitchell River in Northern Australia, where 45 species of freshwater fish are exposed to the presence of four threats. The evaluation compares our exact MIP approach with the conservation planning software Marxan and the heuristic approach developed in Cattarino et al. (2015). The results obtained show that our MIP models have three advantages over their heuristic counterparts: shorter execution times, higher solutions quality, and a solution quality guarantee. Hence, the proposed MIP methodology provides a more effective framework for addressing the multi-action conservation problem. [ABSTRACT FROM AUTHOR]

In patients with a degenerative mitral bioprosthesis and prohibitive surgical risk there is emerging evidence for the feasibility of valve-in-valve procedures via a percutaneous transvenous transseptal approach. This paper describes the first time this procedure has been performed in Australia. [ABSTRACT FROM AUTHOR]