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To effectively control and utilise large amounts of gas emissions from underground coal mining, Australia and many other countries rely heavily on a series of vertical boreholes to capture the gas during mining. This gas capture not only reduces the greenhouse gas impact but also recovers a significant amount of energy. Vacuum pumps are connected to surface boreholes to drive gas flow from the goaf and overlying fractured strata. However, applying high suction pressure to the boreholes may cause more oxygen to enter the goaf from the longwall working face. This influx of oxygen can potentially react with residual coal in the goaf, accelerating coal self-heating and possibly resulting in endogenous fires. By analysing extensive goaf gas drainage data collected from Australian longwalls, researchers have established the normal trend of goaf gas concentration and flow rate as a result of intensive goaf gas drainage. This paper further developed goaf gas flow CFD models with the operating vertical boreholes, which were then calibrated using field borehole production data under certain operating conditions. The CFD model simulated the distribution of O 2 and CH 4 as well as the gas flow pathways in the goaf, considering the complication of goaf gas drainage. This study found that the O 2 concentration is higher on the goaf tailgate side under the influence of tailgate side boreholes compared to the maingate side. Furthermore, for the well-compacted goaf, a significant proportion of the ventilation air travels through 'high permeability flow channels' provided by the goaf edge on tailgate side, and then circulates back into the goaf boreholes. These CFD modelling results not only enable ventilation engineers to visualize the goaf gas flow patterns under the impact of multiple operating boreholes, but also to understand the impact on goaf atmosphere through sensitivity analysis of natural goaf characteristics, such as goaf permeability distributions and gas emission rates. [ABSTRACT FROM AUTHOR]

In 2016, the Australian Government legislated to allow cannabis to be prescribed to patients as an unapproved medicine under the special access provisions of the Therapeutic Goods Act. This paper compares the Australian regulatory approach with other national approaches, outlines the main provisions of the Special Access Scheme for medical cannabis, describes how the program has evolved since 2017, includes an analysis of adverse events reported to the Therapeutic Goods Administration, and discusses the barriers that remain for patients who wish to access medical cannabis. It assesses how well the Australian program has addressed the challenges of providing patients with easier access to medical cannabis while ensuring that high-quality products are used safely and effectively under medical guidance. [ABSTRACT FROM AUTHOR]

• Protocol for a study of quality improvement in Australian ECEC services. • A sequential three-phase mixed-methods design informed by ecological systems theory. • Research-industry partnerships with government authorities and early childhood researchers. • Scale and depth in sample identification, data selection and analytical techniques. International recognition of the early years as a crucial foundational period has led to the design and implementation of quality rating and improvement systems (QRIS) that define, communicate, and monitor the components of quality in early childhood education and care (ECEC). The aim of these policies is to achieve effective quality assurance and improvement through a system-oriented approach to assessment and evaluation. Informed by ecological systems theory, this paper outlines a three-phase, mixed-methods design for researching a national sample of child care centres that showed overall improvement on the Australian National Quality Standard (NQS) assessment and rating (A&R) criteria. The study samples are drawn from a national dataset of centre-based child care services with two or more A&R rounds and an initial rating of Working Towards NQS (N = 1,935). The results of this study will provide insights into the macro-, exo-, meso- and micro-systems level factors and strategies that support quality in ECEC services. [ABSTRACT FROM AUTHOR]

• Practice directions should recognise multiple models of CSE and a wider context of vulnerability and unmet needs. • Anxieties about young people's sexual behaviours can detract from CSE making it challenging to identify and respond. • Outreach and support that addresses young people's emotional, social and practical needs are valuable directions. • Suitable placements and ensuring young people have a safe and stable home environment is vital to any response to CSE. • CSE responses should be guided by child-centred practice and informed by young people's perspectives. There is a growing interest in understanding and responding to child sexual exploitation (CSE) in Australia, but limited empirical research from Australian contexts. The research reported here contributes to the evidence base by considering challenges and best practices for responding to CSE from the perspectives of 15 caseworkers in a statutory child protection and out of home care environment in one Australian region. In so doing, the paper also offers insight into CSE along with consideration of the emerging practice directions and systems surrounding these in the Australian context. Findings point to potential problems arising from existing frameworks for understanding and responding to CSE. Participants held concerns about a narrow focus on young people's sexualised behaviours in the wider multi-agency care context. This was understood to obscure a more complex understanding of CSE and its broader context of vulnerability and connection to unmet needs – some of which can arise from the care context itself – making identification and intervention difficult. Findings align with research that emphasises outreach and intensive support for young people centring on strengthening connections, identifying and addressing unmet needs and sustaining safety through consideration of placements and living circumstances. Consideration of practice challenges and opportunities signals the importance of child-centred, wellbeing-oriented directions allowing for multiple models of CSE victimisation, underpinned by a shared language in the multi-agency context and enhanced provision in existing systems. [ABSTRACT FROM AUTHOR]

Stormwater has been acknowledged as a major concern in cities because of mismanagement of this resource. It has also been underestimated as a resource in climate change actions and policies. Water sensitive urban design (WSUD) is considered as an effective adaptation measure to address these issues while providing many co-benefits. This paper reports the challenges of implementing WSUD in the Australian context. Semi-structured interviews were conducted with 57 experts in Australia. The experts are involved in design, research, engineering, and planning policy in both public and private sectors. The qualitative analysis of the interviews involved thematic and content analysis through NVivo12. Analysis of the responses indicated six main challenges including financial, innovation and evaluation tools, capacity, institutional arrangements, and policy. The experts believe that a lack of standardized design and implementation can be addressed through collaborative design processes. They suggest a robust structure of approval process and establishing clarity of roles and responsibilities in all sectors. All respondents confirm the critical role of monitoring and maintenance in these projects. It is suggested that allocating recurrent funding for these ongoing activities from the beginning and setting incentives to engage communities and local councils in maintaining the projects can be helpful. • Provides insights in investigating the impact of social and organisational structure towards achieving WSCs. • Conducted qualitative analysis of interviews and survey questions. • Recommendations to advance stormwater management planning and design. [ABSTRACT FROM AUTHOR]

• A framework to evaluate stochastic rainfall models with a quantitative scale. • 'Good' modelled rainfall does not guarantee 'good' modelled streamflow. • Streamflow-based evaluation is more holistic than rainfall-based evaluation. • Component-wise evaluation can misrepresent ultimate model performance. Stochastic rainfall models are important tools for evaluating hydrological risks such as flooding and drought because of their ability to randomly generate alternative plausible climatic timeseries. The stochastic generation of climatic timeseries is not an end in itself, since they are typically applied to a catchment to determine the performance of water-related infrastructure systems, such as reservoirs or flood-control measures. This methodology typically involves a train of models to determine the end-of-system impact, yet the evaluation of stochastically generated rainfall timeseries is usually a stand-alone procedure focused on metrics directly related to the stochastic generator. This paper demonstrates discrepancies in this approach by evaluating two, daily-timestep, stochastic rainfall models in terms of rainfall metrics and their subsequently generated flow metrics after rainfall-runoff transformation. The two models are a Markov-based model and a latent-variable model, where each model is calibrated and evaluated showing 'overall good' performance. Stochastically generated timeseries, alongside observed rainfall timeseries are inputted to a calibrated catchment model (GR4J) to derive daily flow timeseries. Whereas the rainfall metrics typically showed 'good' performance, streamflow-based metrics are not necessarily 'good'. The procedure is repeated for 277 stations from Australia and 106 stations from the United States of America. Depending on the strictness of the flow-based comparison and region analysed, using the Markov-based model 12–26% of sites were classified as 'poor' performing, and 1%-9% of sites were classified as 'poor' using the latent-variable model. The results demonstrate that catchment-based performance of flow metrics is more holistic since it magnifies features of the rainfall not otherwise visible to rainfall-based evaluation. [ABSTRACT FROM AUTHOR]

As more and more photovoltaic (PV) systems are integrated into the grid, the intelligent operation of the grid system is facing significant challenges. Therefore, accurately forecasting PV power output at various time scales is particularly urgent. To meet this demand, this paper proposes an LSTM-Informer model based on an improved Stacking ensemble algorithm (ISt-LSTM-Informer). The proposed model improves the k-fold cross validation in the traditional Stacking algorithm to a time-series cross validation for integrating time-series forecasting models. Simultaneously, it utilizes long short-term memory (LSTM) and Informer as the base models. By integrating the advantages of the two base models, the ISt-LSTM-Informer achieves accurate short and medium-term PV power forecasting. To validate the effectiveness of the model, a historical dataset from a PV system located in Uluru, Australia, is used for various types of experiments. Among them, comparative experiments validate the superiority of the model. Compared with five other methods, the ISt-LSTM-Informer obtains 21 optimal results for the four evaluation metrics of RMSE, MAE, MAPE, and R 2 across eight forecasting time scales. In addition, different combinations of base models are conducted to verify the advantages of the Stacking ensemble algorithm and the two base models, respectively. • A novel multi-timescale photovoltaic power forecasting model is proposed. • Time-series cross validation is introduced into the Stacking algorithm. • LSTM and Informer are utilized as the base models of the Stacking algorithm. • Various methods are compared to verify the proposed model's effectiveness. • The model's predictive accuracy is illustrated through various visualization methods. [ABSTRACT FROM AUTHOR]

Obesity remains a significant public health concern globally with over one billion adults projected to be obese by 2025. To better understand the drivers of obesity and to inform policy, it is important to explore the factors that influence obesity. The objective of this paper to examine if the crime rates in the neighbourhood or local area in which a person lives influences their likelihood of being obese. Thus, we seek to contribute to the literature on the determinants of obesity by asking the question: what is the effect of neighbourhood (i.e., postcode) crime on obesity? We also examine the pathways through which neighbourhood crime influences obesity with a focus on the role of social capital, physical activity and sleep quality. Using 14 waves of longitudinal data from the Household, Income and Labour Dynamics in Australia (HILDA) survey merged with official police statistics on crime rates at the postcode level, we apply identification strategies that address endogeneity arising from endogenous sorting and omitted variable bias. We find that an increase in neighbourhood crime rates is associated with an increase in body mass index (BMI) and the likelihood of being obese. Exploring the pathways through which neighbourhood crime influences obesity, we find that social capital and physical activity are important channels, while sleep quality is not. The evidence also suggests that the effects of violent crime are more pronounced compared to property crime. Our findings suggest that targeting crime, and in particular violent crime, which seems to be driving the findings, is a core mechanism for reducing BMI and maintaining healthy body weight. The mediating role of physical activity and social capital also suggest that public policy can specifically target these areas by providing interventions that promote social capital and physical activity even amidst high crime rates. • We examine the impact of neighbourhood crime on obesity. • We use 14 waves of longitudinal data from Australia. • Neighbourhood crime increases obesity. • Social capital and physical activity are important channels. • Effects are stronger for females than males. [ABSTRACT FROM AUTHOR]

Despite the considerable success of deep learning methods in modelling physical processes, they suffer from a variety of issues such as overfitting and lack of interpretability. In hydrology, conceptual rainfall-runoff models are simple yet fast and effective tools to represent the underlying physical processes through lumped storage components. Although conceptual rainfall-runoff models play a vital role in supporting decision-making in water resources management and urban planning, they have limited flexibility to take data into account for the development of robust region-wide models. The combination of deep learning and conceptual models has the potential to address some of the aforementioned limitations. This paper presents a sub-model hybridization of the GR4J rainfall-runoff model with deep learning architectures such as convolutional neural networks (CNN) and long short-term memory (LSTM) networks. The results show that the hybrid models outperform both the base conceptual model as well as the canonical deep neural network architectures in terms of the Nash–Sutcliffe Efficiency (NSE) score across 223 catchments in Australia. We show that our hybrid model provides a significant improvement in predictive performance, particularly in arid catchments, and generalizing better across catchments. • Hybrid modelling features parsimony of data-driven and conceptual hydrologic models. • We present a deep learning-based hybridization for the GR4J rainfall-runoff model. • We present a hierarchical training approach consisting of gradient-based and evolutionary optimization of the respective models. • The results show that hybrid models outperform the canonical (base) hydrologic and deep learning model. • The addition of surface temperature and antecedent streamflow further improves the predictive performance. [ABSTRACT FROM AUTHOR]

• There has been growing concern, globally, regarding use of nitrous oxide (N 2 O). • Use, google search probabilities and social media posts increased from 2009 and 2020. • Sharpest increases were noted between 2015 and 2018, plateauing in recent years. • Frequency and quantity of N 2 O use remained stable and low. • Number of N 2 O-related calls to Poisons Information Centres increased sixfold. There is growing concern, globally, regarding use of nitrous oxide (N 2 O) for intoxication purposes. This paper aims to examine trends in: (i) past six month N 2 O use among a sample of people who use regularly use ecstasy and/or other illicit stimulants (2003–2020); (ii) volume of N 2 O-related Google searches and social media posts (2009–2020); and (iii) N 2 O-related calls to Poisons Information Centres (PIC) (2004–2020). Data were obtained from annual interviews with sentinel samples of Australians aged ≥16 years who used ecstasy and/or other illicit stimulants ≥monthly and resided in a capital city (∼800 each year); Google search activity; social media posts; and exposure calls to four PIC. Among samples of people who regularly use ecstasy and/or other illicit stimulants, past six-month N 2 O use increased 10% each year from 2009 to 2020, with the sharpest increase observed between 2015 and 2018 (25.4% p/year; 95% CI: 14.6–37.1). Frequency and quantity of N 2 O use remained stable and low. Google search probabilities increased by 1.8% each month from January 2009 and December 2019 (95% CI: 1.5–2.2), with the sharpest increase observed between July 2016 to December 2017 (6.0% p/month; 95% CI: 4.4–7.5). Social media posts increased 2.0% per month from January 2009 and December 2019 (95% CI: 1.1–3.0), with the sharpest increase observed between March and October 2017 (19.2% p/month; 95% CI: 1.7–39.7). The number of N 2 O-related calls to Australian PIC increased sixfold between 2016 (16) and 2020 (111). Triangulation of various data sources indicate significant shifts in N 2 O use and harms in Australia. This includes increases in use, Google searches and social media posts, although these have plateaued in recent years, coupled with increased rates of harm. These findings correspond with evidence of a global increase in N 2 O use and harm, highlighting the need for education of both people who use N 2 O and health professionals. [ABSTRACT FROM AUTHOR]

Integrating disparate and distributed vegetation data is critical for consistent and informed national policy development and management. Australia's National Vegetation Information System (NVIS) under the Department of Climate Change, Energy, the Environment and Water (DCCEEW) is the only nationally consistent vegetation database and hierarchical typology of vegetation types in different locations. Currently, this database employs manual approaches for integrating disparate state and territory datasets which is labour intensive and can be prone to human errors. To cope with the ever-increasing need for up to date vegetation data derived from heterogeneous data sources, a Semi-Automated Hybrid Matcher (SAHM) is proposed in this paper. SAHM utilises both schema level and instance level matching following a two-tier matching framework. A key novel technique in SAHM called Multivariate Statistical Matching is proposed for automated schema scoring which takes advantage of domain knowledge and correlations between attributes to enhance the matching. To verify the effectiveness of the proposed framework, the performance of the individual as well as combined components of SAHM have been evaluated. The empirical evaluation shows the effectiveness of the proposed framework which outperforms existing state of the art methods like Cupid, Coma, Similarity Flooding, Jaccard Leven Matcher, Distribution Based Matcher, and EmbDI. In particular, SAHM achieves between 88% and 100% accuracy with significantly better F1 scores in comparison with state-of-the-art techniques. SAHM is also shown to be several orders of magnitude more efficient than existing techniques. • The Integration of the National vegetation database is key for policy development. • A novel semi-automated hybrid schema matching framework, SAHM is proposed. • SAHM is a two-tiered matching solution that uses schema and instance information. • SAHM yields better schema matching results in comparison with the State-of-the-art. [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]

The majority of research participants in the social sciences are recruited from populations that are Western , educated , industrialized , rich , and democratic. This has the potential to threaten the external validity and limit the generalizability of research findings. It also highlights the need to provide a historical accounting of participant characteristics and reporting practices across coherent disciplines of research. This paper reports the participant characteristics from studies published in 12 leading journals in the sport and exercise psychology literature. In total, 15,650 peer-reviewed articles were published across these outlets from 1930 to 2021, involving 4,487,437 human participants. A descriptive overview of participant characteristics and reporting practices suggests that empirical understanding of human experiences and outcomes in sport and exercise settings is built from an incomplete and unrepresentative sample of participants. Findings illuminate potential knowledge gaps that may have resulted from the lack of diverse samples and offer potential paths forward for contemporary sport and exercise psychology scholars who wish to address these gaps. • 15,650 articles with 4,487,437 human participants have been published across 12 sport and exercise psychology journals from 1930 to 2021. • 75.6% of participants from these studies have been drawn from the United States, Canada, the United Kingdom, and Australia. • Across this literature, many important participant characteristics have gone uncollected and/or unreported. [ABSTRACT FROM AUTHOR]

Geological and geophysical interpretation is characterised by large and localised datasets that are extremely expensive to acquire. There are clear advantages in applying deep learning techniques to such datasets, but this requires a large amount of suitable data for effective training. Creation of training data can be time-consuming, but novel countermeasures such as Generative Adversarial Networks (GANs) are an enticing alternative with the potential to alleviate this issue by providing synthetic data that is representative of the real data. This paper details an investigation of the potential of GANs for the augmentation of labelled seismic facies from a mass transport complex in training a convolutional neural network (CNN) for facies classification. The study adopts a specific GAN approach, known as the Conditional Style-Based Logo GAN (LoGANv2), because of its capability to generate conditioned output with improved training stability. By using LoGANv2 to synthesise examples that mimic the behaviour of the real data, based on a 3D seismic dataset from the North Carnarvon Basin in Australia, the accuracy of the traditional CNN for facies classification improved from 38% (the benchmark result where no augmentation was applied) to 52%, 61%, 94% and 74% for four trials with different degrees of augmentation. The results show that increasing training size, either through manual annotation (trial 2) or standard manipulations such as image rotation (trial 3 and trial 4), improves the performance of LoGANv2 and hence the CNN classification. The experiments indicate that although standard manipulation can increase the diversity of the training dataset, the balance between diversity and consistency within the datasets is also important, and this should be optimized for LoGANv2 to achieve better performance. In addition, we explored the adaptability of the proposed LoGANv2-CNN approach to unlabelled samples from another survey to demonstrate the robustness and flexibility of the model. • A LoGANv2-assisted CNN model was developed for augmentation and classification of seismic facies. • With LoGANv2 proving its capacity to augment different types of seismic facies with minimal manual labelling, the synthetic facies generated and the real ones are passed down to a CNN for further classification. • The streamlined process demonstrates that, with little manual annotation, the generation of synthetic seismic facies could lead to a better understanding of the underlying geological structures. [ABSTRACT FROM AUTHOR]

This paper introduces a novel model for predicting the performance and conducting sensitivity analysis of design parameters in two-body point absorber wave energy converters. The key novelty lies in the examination of design parameter sensitivity and their interaction effects on performance. The model utilizes the response surface method (RSM) in conjunction with central composite design to establish analytical equations for efficiently predicting the resonance frequency and peak generated power of the two-body wave energy converters based on geometric parameters and wave height. This eliminates the need for complex analytical solutions and boundary element simulations. The accuracy and reliability of the RSM prediction models are validated through state-of-the-art numerical simulations and analysis of variance (ANOVA). Using these RSM prediction models, the study proceeds to design and optimize two-body point absorbers for locations along the coastlines of the six Australian states, focusing on two objectives: maximizing peak output power and maximizing the power-to-weight ratio at each location. By incorporating the second optimization target, it is observed that impressive power output with smaller device dimensions or a higher power-to-weight ratio can be achieved across all six Australian states. The developed response surface method prediction model is a versatile mathematical framework applicable to all two-body point absorber wave energy converters and can be adapted for optimizing other types of wave energy converters with expansive search spaces. Australia was selected as a case study due to its abundant wave energy density along its southern shorelines. Notably, no similar studies addressing these specific aspects have been reported in the literature, making this work the first of its kind. • The performance prediction models of two body wave energy converters have been developed from design parameters. • The prediction models are validated against numerical simulations and the analysis of variance (ANOVA). • The sensitivity of design parameters and their interactions has been analyzed and disclosed. • The optimal dimensions for the maximum power and maximum power to weight ratio are derived for all the Australian seas. [ABSTRACT FROM AUTHOR]

• GIS analysis is conducted to quantify the hydrological information for mud pumping prediction. • In-service train data and hydrological variables are combined to develop predictive model. • Incorporating hydrological variables can improve prediction performance. • Explainable deep learning can be used to reveal the effects of a single variable on the probability of mud pumping. • The most vulnerable sections for mud pumping in railway tracks can be identified. Automatic and timely identification of mud pumping is important for the reliability and safety of railroads. The current mud pumping prediction model is based on monitoring the dynamic response of railway tracks. The essential geotechnical trigger factors such as the hydrological conditions are not well-considered in these prediction models, as that information is hard to be quantified, which unavoidably reduces the accuracy of the prediction. This paper proposes to utilize the Geographic Information System (GIS) to quantify the hydrological information along railway tracks. Through GIS analysis, the hydrological variables including elevation, near-river distance, rainfall, sink depth, and soil types are estimated and combined with in-service train monitoring data for model development. To deal with multi-attribute data, a dual-channel neural networks model is proposed to separately mine the characteristics in different attributes data for prediction. To further understand the prediction model, Shapely addictive explanations (SHAP) method is applied to estimate the importance of hydrological variables and reveal the possible relationships between the variables and the probability of mud pumping. The proposed approach is applied to a real-life case from the railway tracks in Australia to validate its effectiveness. The prediction results show that the proposed approach can predict mud pumping with balanced accuracy of 90.84%. The results confirm that integrating of GIS information and monitoring data can generate more accurate prediction and reduce the false prediction rate. Based on the explainable results, it is observed that rainfall is the most important hydrological variable that influences mud pumping occurrence. Apart from rainfall, groundwater-related variables show a greater impact on mud pumping occurrence than surface water-related variables. The explainable results also can help infrastructure managers to identify the most vulnerable sections in railway tracks, which facilitates targeted maintenance planning and track substructure design. [ABSTRACT FROM AUTHOR]

Curtailment of distributed photovoltaic (PV) and battery energy storage systems will have significant implications for power system transition around the world. Australia offers a unique case study as it has highest installation rate of distributed-PV and growing fleet of battery energy storage systems. Distributed-PV and battery inverters in Australia are required to exhibit voltage-responsive power-quality response modes to prevent excessive voltage rise caused by increasing day-time energy exports, but these modes can curtail power output and limit the value that can be gained from the renewable energy assets. For the first time in Australia, this paper studies all three inverter power-quality response modes and develops novel algorithms to assess curtailment. The algorithms are applied to a real-world dataset of 1-sec distributed-PV and battery power measurements from 1300 residential households; therefore, data resolution is higher and sample size is larger than previous related studies. Using these datasets, the study compares the experienced curtailment between distributed-PV only sites and distributed-PV coupled with battery sites for the first time. The study investigates and quantifies the energy loss due to curtailment within the South Australia region with over 40% distributed-PV penetration which has the highest uptake in the world. The results show that average curtailment loss was 1.5% for distributed-PV only sites and 0.2% for distributed-PV coupled with battery sites, however, some sites were heavily impacted losing up to 25% of generation. The reasons for the larger curtailment loss were identified as wiring and network connection faults and high voltage set-points at households' respective local substations. Other potential reason for the heavily impacted sites is being located towards the end of the low voltage feeder, however this couldn't be verified due to lack of spatial data. The large variation in curtailed generation across sites raises concerns for system owners and suggests further inquiry into the power-quality response mode design and regulations. The study also examines inverter conformance using real-world operational data for all three power quality response modes for the first time, and the results showed a low rate of conformance according to the Australian Standards and there were various discrepancies in the execution of these modes which raises concerns considering the increasing importance of distributed-PV and battery inverter fleet in supporting network operations and security. The results therefore warrant further investigation into the reasons behind these discrepancies and devising appropriate mechanisms to tighten inverter conformance checks. • Energy curtailment is calculated for D-PV only and D-PV coupled with BESS sites • Average loss due to curtailment is less than 2% of total D-PV generation • Curtailment is greater for D-PV only sites than D-PV coupled with BESS sites • Some sites lose up to 25% of generation due to curtailment • The large variation of curtailment losses across sites raises concerns • Inverters showed low conformance in power quality response mode standards [ABSTRACT FROM AUTHOR]

In Australia, and internationally, mentoring is proffered as a powerful professional learning experience for both early career teachers (ECTs) and their mentors alike. However, authentically beneficial learning partnerships have proven challenging to achieve. This paper provides a theoretical and practical response to this issue, arguing the criticality of genuine conversations cultivated through balanced, non-hierarchical questioning to position ECTs and mentors as co-learners. Drawing on positioning theory in conjunction with the concept of genuine conversations, the contents of five recorded mentoring conversations involving Australian ECTs and mentors were analysed. These findings have important implications for mentoring practice across educational contexts. • Learning partnerships between early career teachers and mentors are challenging to achieve, regardless of experience. • Innovative use of positioning theory in conjunction with the concept of genuine conversations. • The criticality of genuine conversations cultivated through balanced, non-hierarchical questioning for learning partnerships. [ABSTRACT FROM AUTHOR]

Spotty Liver Disease (SLD) is a serious problem in laying hens farmed in cage-free systems. The causative organism, Campylobacter hepaticus , is regarded as having a fecal-oral method of transmission and hence may build up and spread readily in housing systems which allow ease of direct contact of hens with the flock's fecal material. The epidemiology of SLD has not been thoroughly investigated. An initial cross-sectional analytical epidemiological survey of SLD in free range and barn layer systems was conducted in Australia over 2019 to 2021.The survey involved rearing flocks (n = 32) which were then followed through into laying flocks (n = 24) up to 40 wk of age. Cloacal swabs were collected during rearing and lay for C. hepaticus detection by PCR. Flocks were classified as "Cases" (n = 18) where clinical SLD according to the case definition was observed or "Controls" (n = 6) which were clinically unaffected. No C. hepaticus was detected in cloacal swabs from rearing houses whereas the organism was detected in 18 Case flocks in lay and from 2 Control flocks in lay. All layer houses that incorporated a scratch area (n = 13) were categorized as Cases. Thus, having a scratch area is a key determinant for SLD and no analyses of further contributory factors from these flocks were able to be made. Of the remaining 11 flocks which had floors fully covered by slats, 5 were Cases (45%). Further risk factor analysis was compromised by this small sample size and identification of other significant associations was not possible. A larger survey investigating flocks laying in houses with fully slatted floors was undertaken to further the understanding of SLD epidemiology and is reported in a companion paper. [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]

• We provide new evidence for the benefits and challenges of accessing SMART Recovery mutual-help groups virtually via videoconference. • Identified benefits include availability, ease of access and the zoom chat feature. • Potential challenges included in-group engagement, group size, non-verbal cues, social interaction and technology problems. • Virtual SMART Recovery mutual-help groups appealed to different people under different circumstances. • Our findings have implications for research, training and practice. COVID-19 prompted widespread transition of face-to-face mutual-help groups to virtual delivery. Current understanding of the experience of virtual mutual-help groups is limited to 12-step approaches or asynchronous groups (e.g., forums). This paper explores participant and facilitator perspectives regarding the benefits and challenges of accessing SMART Recovery mutual-help groups virtually via videoconference. A self-selected convenience sample of participants (n = 29) and facilitators (n = 15) from SMART Recovery mutual-help groups in Australia were enrolled. Participants and facilitators were sampled to reflect experience of virtual groups delivered via videoconference ('online'), face-to-face groups ('face-to-face') or both types of groups ('both'). Telephone qualitative interviews were conducted using a semi-structured interview guide. Interviews were audio-recorded, transcribed, and analysed using iterative categorisation. Participant and facilitators discussed their experience across eight interconnected themes benefits were typically discussed with regard to the (1) availability, (2) ease of access and (3) value add of the chat feature in online groups. Challenges largely pertained to (1) in-group engagement, (2) group size, (3) non-verbal cues, (4) social interaction and (5) technology problems. The impact of these challenges on participant and facilitator experience varied, and neither modality was consistently identified as superior. SMART Recovery mutual-help groups provided participants with another option for accessing mutual-help and appealed to different people under different circumstances. Depending on the needs and preferences of the individual, online SMART Recovery mutual-help groups may help to mitigate a range of barriers to help seeking and may also engage people otherwise unable or reluctant to engage in treatment. To inform training, practice and policy, improved understanding of the individual and contextual factors that enhance participant engagement, experience and outcomes is needed. [ABSTRACT FROM AUTHOR]

This paper describes fire safety experiments on Australian native timber samples with a special focus on their use in bushfire-prone areas. Nine species were assessed through testing in a cone calorimeter, thermogravimetric analysis and differential scanning calorimetry (DSC). The effects of density, moisture content and chemical extractives content were evaluated. Marked differences in ignition times were found, possibly due to variations in density across species, as well as the chemical extractives content. Analysis of the heat flow through DSC indicated that the type of extractives can influence the fire safety performance and that this aspect of wood properties merits further study. One additional species was identified as a suitable candidate for bushfire-resisting species in the Australian bushfire context. • Determination of flammability of northern Australia timber species. • Multiscale testing of varied density and extractive content. • Assessment for timber use in bushfire attack level 29 zones. • Extractives content and ignition have linear correlation. [ABSTRACT FROM AUTHOR]

Long distance dispersal (LDD) contributes to the replenishment and recovery of tropical seagrass habitats exposed to disturbance, such as cyclones and infrastructure development. However, our current knowledge regarding the physical attributes of seagrass fragments that influence LDD predominantly stems from temperate species and regions. The goal of this paper is to measure seagrass fragment density and viability in two tropical species, assessing various factors influencing their distribution. We measured the density and viability of floating seagrass fragments for two tropical seagrass species (Zostera muelleri and Halodule uninervis) in two coastal seagrass meadows in the central Great Barrier Reef World Heritage Area, Australia. We assessed the effect of wind speed, wind direction, seagrass growing/senescent season, seagrass meadow density, meadow location and dugong foraging intensity on fragment density. We also measured seagrass fragment structure and fragment viability; i.e., potential to establish into a new plant. We found that seagrass meadow density, season, wind direction and wind speed influenced total fragment density, while season and wind speed influenced the density of viable fragments. Dugong foraging intensity did not influence fragment density. Our results indicate that wave action from winds combined with high seagrass meadow density increases seagrass fragment creation, and that more fragments are produced during the growing than the senescent season. Seagrass fragments classified as viable for Z. muelleri and H. uninervis had significantly more shoots and leaves than non-viable fragments. We collected 0.63 (±0.08 SE) floating viable fragments 100 m−2 in the growing season, and 0.13 (±0.03 SE) viable fragments 100 m−2 in the senescent season. Over a third (38%) of all fragments collected were viable. There is likely to be a large number of viable seagrass fragments available for long distance dispersal. This study's outputs can inform dispersal and connectivity models that are used to direct seagrass ecosystem management and conservation strategies. • There are large numbers of viable seagrass fragments available for dispersal. • Moderate winds with high seagrass density increases seagrass fragment creation. • More seagrass fragments are produced during the growing than the senescent season. • Seagrass fragments have more shoots and leaves than non-viable fragments. • Over a third (38%) of all floating fragments are viable. [ABSTRACT FROM AUTHOR]

• Challenge the monolingual English norm in intercultural doctoral education. • Motivate bilingual doctoral researchers' translingual capabilities for theorising. • Develop a translingual pedagogy for bilingual doctoral researcher education by drawing upon the Chinese character jiāo/jiào 教. • Resolve bilingual doctoral researchers' doubts and concerns about translingual theorising. • Highlight supervisors' three roles when supervising bilingual doctoral researchers. The transcultural and translingual diversity of bilingual doctoral researchers who speak languages other than English, in particular those with non-Anglophone backgrounds, has been emphasised in recent years to challenge the monolingual English norm. To explore effective pedagogies to motivate these bilingual doctoral researchers to theorise translingually, this paper draws upon methodologies about translingualism and intercultural doctoral education to dispel the recurrent doubts raised by these bilingual doctoral researchers. Thus, semi-structured interviews were conducted with 12 Chinese bilingual doctoral researchers and their supervisors in Australia and China to understand their perceptions and practices regarding using the linguistic and epistemological resources buried in Chinese for academic purposes. In response to the concerns expressed by the participants, three critical roles of supervisors are highlighted, namely exemplifying, teaching and demanding translingual theorising. These three roles are further developed into a pedagogical framework inspired by the Chinese word jiāo/jiào 教, which itself is an example of translingual theorising. [ABSTRACT FROM AUTHOR]

The hydrogen industry in Australia has gained tremendous momentum in 2018 and after the publishing of the National Hydrogen Roadmap. In this study, a comprehensive review of the recent history of hydrogen-related activities and publications, as well as hydrogen funding programs and the funded projects, was conducted. Most of these activities were tabulated and discussed from the perspective of sorting, documentation, and contrast. The broad picture indicates the need and necessity of a unified national database for the hydrogen industry landscape. An innovative modular online (web-based) crowdsourced database platform is introduced in this paper as the "Australia Hydrogen Industry Knowledge-Sharing Platform" to include all hydrogen-related activities in Australia. This web-based platform will be presented in the form of a business to generate revenue to offset operation and maintenance costs and ensure the system updating. This study will not only guide the Australian governments and/or stakeholders to develop a hydrogen economy for the future but also other countries to promote their hydrogen industry. Image 1 • Australia hydrogen industry landscape are reviewed. • Hydrogen industry evolution in Australia is time lined, documented and discussed. • Hydrogen industry knowledge-sharing platform necessity is flagged. • An innovative hydrogen web-based crowed-sourced model is proposed. [ABSTRACT FROM AUTHOR]

Background: Minimally adequate treatment (MAT) is intended to represent treatment minimally sufficient for common mental health problems. For children, MAT has been defined over a twelve-month period as either eight or more mental health visits, or four to seven visits plus relevant medication. MAT is used to identify those missing out on adequate care, but it is unknown whether MAT improves children's outcomes.Methods: This paper examines whether MAT is associated with improved outcomes for children. It uses survey data from the nationally representative Longitudinal Study of Australian children on 596 children with mental health problems based on the Strengths and Difficulties Questionnaire at ages 8-15 years, linked to health service administrative data from 2012 to 2016. Statistical analysis examines the association of MAT with later quality of life (Pediatric Quality of Life Inventory), using a lagged dependent variable model to account for time-varying unobserved confounding.Results: Compared to children with lower levels of treatment, those who received MAT between baseline and follow up had no statistically significant improvement in either quality of life or mental health symptoms.Limitations: The observational data provide insight into real-world practice but require statistical methods to account for selection into treatment.Conclusions: While clinical trials show mental health treatments can be efficacious, this study shows no evidence that children receiving MAT in routine practice have better outcomes. These findings demonstrate the need for better understanding of the nature and impact of children's mental health care as it is delivered and received in routine practice. [ABSTRACT FROM AUTHOR]

Cardiac rehabilitation (CR) programs are effective in reducing cardiovascular mortality and readmissions. However, most patients are denied the benefits of CR due to low referral rates. Of those patients referred, commencement rates vary from 28.4% to 60%. This paper quantifies the scale of health loss in Australia due to poor engagement with the program, and estimates how much public funding can be justifiably reallocated to address the problem. Economic decision modelling was undertaken to estimate the expected lifetime health loss and costs to Medicare. Key parameters were derived from Australian databases, CR registries and meta-analyses. Population health gains associated with uptake rates of 60%, and 85% were calculated. CR was associated with a 99.9% probability of being cost-effective, even at a cost-effectiveness threshold lower than conventionally applied. Importantly, an average of 0.52 years of life expectancy are lost due to national uptake being below 60% achieved in some best performing programs in Australia, equivalent to 0.28 quality adjusted life years. The analysis indicates that $12.9 million/year could be justifiably reallocated from public funds to achieve a national uptake rate of 60%, while maintaining cost-effectiveness of CR due to the large health gains that would be expected. CR is a cost-effective service for patients with coronary heart disease. In Australia, less than a third of patients commence CR, potentially resulting in avoidable patient harm. Additional investment in CR is vital and should be a national priority as the health gains for patients far outweigh the costs. • Cardiac rehabilitation (CR) is effective in reducing mortality and readmissions. • Most patients are denied the benefits of CR due to low referral rates. • In this economic analysis, CR was cost-effective with a mean ICER of $6096/QALY. • Patients in CR programs experience greater health benefits over a lifetime. • 60% uptake of CR will lower readmissions by 823 events and 536 deaths over 10 years. [ABSTRACT FROM AUTHOR]

This study examines how Australian academic librarians perceive effective Web 2.0 tools used to market library services and resources and the factors influencing perceptions of the Web 2.0 tools used. An online survey was sent to 400 academic librarians in 37 Australian universities. The response rate was 57.5%. The qualitative data were analysed using content analysis. The collected quantitative and qualitative data were analysed using descriptive (frequencies, percentages, means, standard deviations) and inferential statistics (ordinal regressions). The key findings show that demographics, human capital and library variables play an important and significant role in predicting librarians' perceptions of effective Web 2.0 tools used to market services and resources. This paper provides a better understanding of academic librarians' attitudes, views as well as effective Web 2.0 tools used to market their services and resources. Librarians can use the results to reflect on the effectiveness of the Web 2.0 tools used, to balance the weight of the factors' influences and to better understand various effective Web 2.0 tools to enable them to market academic library services and resources more effectively in the future. [ABSTRACT FROM AUTHOR]

This paper profiles Australian universities’ website communications about sustainability initiatives, especially relating to Talloires Declaration signification and the ten recommended actions. The research involves a content study of Talloires signatories’ websites and their semiotic and signaling theory aspects across time. The source is publicly available information (time period 2014 and 2015 respectively) in context with education for sustainable development (ESD) in society and the transaction model in communication theory. It is found that some of the signatory universities in Australia exemplify a few of the Talloires ten agreed actions in their public communications, but each point is not emphasised with equal priority. The variance may be due to divergent underlying objectives; such as public communication of Talloires toward genuine benefit for the environment, or to create a strategic positioning tool to signal the university as an environmental champion within the broader society. Focusing upon secondary data from signatory university websites in Australia, the paper provides a study of higher education signification of Talloires. It assists the initial understanding of signaling theory in the public communication transactions that promote Talloires action and implementation. The findings encourage further studies of related communication issues in universities in other countries. The paper also deepens local and global understanding of perceptions of sustainability and contributes to the body of comparative literature of sustainability in higher education as a development component of strategic management of ESD. [ABSTRACT FROM AUTHOR]

This paper presents a random forest classification approach for identifying and mapping three types of lowland native grassland communities found in the Tasmanian Midlands region. Due to the high conservation priority assigned to these communities, there has been an increasing need to identify appropriate datasets that can be used to derive accurate and frequently updateable maps of community extent. Therefore, this paper proposes a method employing repeat classification and statistical significance testing as a means of identifying the most appropriate dataset for mapping these communities. Two datasets were acquired and analysed; a Landsat ETM+ scene, and a WorldView-2 scene, both from 2010. Training and validation data were randomly subset using a k- fold ( k = 50) approach from a pre-existing field dataset. Poa labillardierei, Themeda triandra and lowland native grassland complex communities were identified in addition to dry woodland and agriculture. For each subset of randomly allocated points, a random forest model was trained based on each dataset, and then used to classify the corresponding imagery. Validation was performed using the reciprocal points from the independent subset that had not been used to train the model. Final training and classification accuracies were reported as per class means for each satellite dataset. Analysis of Variance (ANOVA) was undertaken to determine whether classification accuracy differed between the two datasets, as well as between classifications. Results showed mean class accuracies between 54% and 87%. Class accuracy only differed significantly between datasets for the dry woodland and Themeda grassland classes, with the WorldView-2 dataset showing higher mean classification accuracies. The results of this study indicate that remote sensing is a viable method for the identification of lowland native grassland communities in the Tasmanian Midlands, and that repeat classification and statistical significant testing can be used to identify optimal datasets for vegetation community mapping. [ABSTRACT FROM AUTHOR]

Forensic science is increasingly used to help exonerate the innocent and establishing links between individuals and criminal activities. With increased reliance on scientific services provided by multi-disciplinary (police, medicine, law, forensic science), and multi-organisational in the private and government sectors (health, justice, legal, police) practitioners, the potential for miscommunication resulting unjust outcomes increases. The importance of identifying effective multi-organisational information sharing is to prevent the 'justice silo effect'; where practitioners from different organisations operate in isolation with minimal or no interaction. This paper presents the findings from the second part of the Interfaces Project, an Australia-wide study designed to assess the extent of the justice silos. We interviewed 121 police, forensic scientists, lawyers, judges, coroners, pathologists and forensic physicians. The first paper published in 2013 presented two key findings: first investigative meetings were rare in adult sexual assault cases; second many medical practitioners were semi-invisible in case decision-making with this low level of visibility being due to lawyers, forensic scientists or police not being aware of the role/expertise medical practitioners offer. These findings led to the development of a flowchart model for adult sexual assault that highlights the range of agencies and practitioners typically involved in sexual assault. The rationale for the flowchart is to produce a visual representation of a typical sexual assault investigative process highlighting where and who plays a role in order to minimise the risk of justice silos. This is the second paper in a series of two. [ABSTRACT FROM AUTHOR]

Australians are one of the world’s highest per capita emitters of greenhouse gases, yet the country’s target for emissions reductions by 2030 remains modest. This paper looks at policy options for Australian cities to deliver faster emissions reductions than the national commitment level. The main focus is on an accelerated reduction in emissions from urban road transport, through technological improvements and behaviour changes. Targets are proposed for improved emissions intensities, to bring Australia much closer to US and EU performance expectations. A range of behaviour change measures is then tested on Melbourne and Sydney, the Sydney analysis using MetroScan-TI, an integrated evaluation framework, to explore how behaviour changes might enhance emissions outcomes. The potential contribution of public transport is a particular focus. The paper concludes that, with sufficient political will, Australia could reduce its 2030 road transport emissions to 40% below 2005 levels. This is a much larger reduction than the current 26–28% Australian target but is more consistent with longer term pathways to acceptable carbon budgets. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive substance flow analysis (SFA) of phosphorus (P) for a six-year period (2008–13) in Gippsland, a key agricultural region of Australia with high economic and environmental significance. The analysis has revealed that around 71% (10,904 t) of the mean annual total inflow of P was stored in this region. This finding is different from other published regional scale SFAs, where more than 50% of the P in annual total inflow eventually left the region. Per capita P inflow in Gippsland is also found substantially higher compared to available SFAs. In Gippsland, the annual inflow of P primarily occurred as commercial fertilizer (66% or 10,263 t) and livestock feed (29% or 4443 t), and the outflow mainly occurred as livestock products (94% or 4181 t); while the majority (66% or 7218 t) of the P storage occurred in soils of the livestock farming area. A comparative analysis of the magnitude of P flow in different subsystems indicates that more than 80% of the annual total inflow, outflow, and storage of P in this region is associated with the livestock (mainly dairy and meat cattle) farming subsystem. For the Gippsland region as a whole and almost all subsystems, significant annual variations in the magnitudes of P inflow, outflow, storage and internal flow have been observed. Between 2008 and 2013, both the annual total inflow (mainly as commercial fertilizer) and the annual total storage (mainly in soils) of P in this region showed a substantial decrease (41% and 54% of the 2008 level, respectively), while the annual total outflow (mainly as livestock and crop products) remained nearly the same, indicating an improvement towards sustainable P management. Despite such a positive sign, there is still adequate room for improvement. This analysis indicates that over the study period, about 65,424 t P were accumulated (mainly as soil storage) that is approximately six times the mean annual P inflow as commercial fertilizer in this region; while approximately 3241 t P lost as soil erosion and runoff, indicating substantial adverse economic and environmental implications. Based on the findings of the current analysis, this paper outlines a wide range of policy and management interventions to reduce the downstream loss of P and other nutrients as well as the region's dependency on imported commercial fertilizers and grain based feed. This paper also presents new criteria for data quality analysis and a set of P concentration data of various materials that could be readily utilized in future SFAs of P at any geographical scale. This paper suggests that considering the inter-annual variations in P flow as assessed in this SFA, future research should focus on identifying the influence of socio-environmental, technological and political factors on the magnitude P flow in Gippsland. [ABSTRACT FROM AUTHOR]

In Australia, heatwaves are the deadliest natural hazard and a major driver of peak electricity demand. The disproportionately high peak demand increases electricity prices, causes occasional blackouts and exacerbates energy poverty, all of which limit one’s ability to use air conditioning. Meanwhile, increased energy efficiency of dwellings may decrease their heat stress resistance. This paper challenges whether the current Australian Nationwide Energy Rating Scheme encourages heat stress resistance. Cooling consumption, peak cooling demand and the risk of indoor overheating were assessed for a typical single-storey home in Adelaide and Sydney. Design options between 6 and 8 stars, plus two traditional, energy-inefficient homes were simulated with the AccuRate energy simulation program. This paper demonstrates that the NatHERS does not directly encourage heat stress resistance in new homes and can even deliver buildings with worse heat resistance and increased reliance on air conditioning than traditional, energy-inefficient buildings. This overreliance on air conditioning can present a public health hazard, consequently, the integration of heat stress resistance in the Nationwide House Energy Rating Scheme is recommended. Recommendations for the analysis and assessment of heat stress resistance are provided. [ABSTRACT FROM AUTHOR]

Housing affordability is traditionally measured using the percentage of household income spent on housing. An important cost that is usually overlooked in measuring location affordability is the transportation or accessibility costs. In this paper, we present a modeling approach, driven by urban open data, to measure location affordability that incorporates both housing and transportation costs. We apply the developed model to assess housing affordability in Melbourne, Australia as a case study. Results suggest that neighbourhoods that appear to be affordable when only housing cost is considered are not necessarily affordable when transportation costs are taken into account. A negative correlation between housing affordability and transportation affordability is observed. We also identify the presence of a strong spatial clustering pattern in the affordability measure across the study area. A major methodological contribution of the paper is the inclusion of comprehensive private vehicle costs and public transportation expenses in the model that contributes to a more robust estimation and understanding of location affordability. The model also distinguishes between different trip purposes. Results suggest that plans and policies to improve housing affordability should be made in coordination with transportation infrastructure investment plans to ensure effective and equitable outcomes. Nevertheless, the focus of the paper is more on the measurement of affordability; rather than reviewing and recommending housing related policies. [ABSTRACT FROM AUTHOR]

Recycled concrete waste in the form of recycled concrete aggregate (RCA) is presently used mostly as a road base filler in Australia. However, instead of producing natural aggregate (NA) to manufacture natural aggregate concrete (NAC) to use in structural concrete, there is potential to use RCA to manufacture recycled aggregate concrete (RAC). While the material performance of RAC compared to NAC is analysed in the existing literature, it is not evident whether the use of RCA in structural concrete results in financial and environmental benefits. Previous literature analysing these aspects mostly focuses on a single area of investigation. This paper presents an integrated methodology for the assessment of the use of RCA replacing NA in structural concrete, considering technical, financial, environmental and social perspectives. Cost-benefit assessment (CBA) has been used to evaluate the internalised impacts as well as external costs concerning the use of both RAC and NAC. The scope of each discipline-focused assessment is presented demarcating the relevant scope for further study, and the specific tools and methodologies to be adopted are specified. Finally, amalgamating the different discipline-focused assessments, a unique approach for comparing a sustainable, alternative raw material for concrete, is presented in this paper. [ABSTRACT FROM AUTHOR]

Harmful Sexual Behavior and Child Sexual Exploitation are problems of significant proportion for children & young people living in out-of-home care. The aim of this review was to conduct a scoping exercise of the evidence about preventing these problems with the intent of summarising and disseminating knowledge to policy-makers, practitioners and researchers. Five electronic databases were searched in November and December 2016, including: PscyhINFO; Applied Social Science Index and Abstracts; SocINDEX; Web of Science; and Education Resource Information Centre. The search was guided by the research question: What is known about preventing Harmful Sexual Behavior and Child Sexual Exploitation for children & young people living in residential out-of-home care settings? Twenty papers were included in the review, including: seven peer-reviewed journal articles; three reports for government; two presentation transcripts; two literature reviews; one qualitative research report; one report for a government inquiry; one submission to a government inquiry; one consultation paper for a government inquiry; one guideline; and one educational resource. Three major thematic categories were identified in the evidence: (i) constructing educative interventions for children & young people and workers ; (ii) targeting grooming and problematic sexual behavior ; and (iii) providing a holistic response and a way out . The review revealed that the current prevention response to Harmful Sexual Behavior and Child Sexual Exploitation for children & young people living in residential care is under-developed. Promising program, service or practice elements relating to the prevention of Harmful Sexual Behavior and Child Sexual Exploitation were identified and three interventions suggested for future prevention efforts. [ABSTRACT FROM AUTHOR]

Objective: This paper aimed to investigate whether distinct sleep quality subtypes predicted health-related quality of life in a nonclinical sample of children.Methods: This paper utilized data from two waves of the Longitudinal Study of Australian Children, a cohort study that follows a representative population of children in Australia. This paper examined data from Waves 4 and 5 of the LSAC (covering the period 2010-2012) and included 3974 children aged 10-11 years at Wave 4 (51.4% male). Multiple dimensions of sleep quality were assessed using a combination of child- and parent-reported measures. Health-related quality of life (HRQOL) was assessed through the Pediatric Quality of Life Inventory.Results: Latent class analysis indicated six distinct sleep quality classes in children, namely good sleep, moderate sleep quality, mild sleep disturbances, short sleep, long sleep, and disordered sleep. In general, the disordered sleep and minor sleep disturbance classes had poorer HRQOL, which worsened over time. The long sleep and moderate sleep quality classes also showed some decreases in HRQOL over time.Conclusions: This study demonstrates that there are distinct sleep quality subtypes in children that could have implications for HRQOL. These findings may inform future strategies to promote improved sleep and HRQOL in children. [ABSTRACT FROM AUTHOR]

When 2020 began, we had no idea what was to unfold globally as we learnt about the Novel-Coronavirus in Wuhan, in the Hubei province of China. As this virus spread rapidly, it became a matter of time before many countries began to implement measures to try and contain the spread of the disease. COVID-19 as it is referred to, resulted in two main approaches to fighting the viral pandemic, either through a progressive set of measures to slow down the number of identified cases designed to 'flatten the curve' over time (anticipated to be at least six months), or to attack it by the severest of measures including a total lock-down and/or herding exposure to fast track 'immunisation' while we await a vaccine. The paper reports the findings from the first phase of an ongoing survey designed to identify the changing patterns in travel activity of Australian residents as a result of the stage 2 restrictions imposed by the Australian government. The main restrictions, in addition to social distancing of at least 1.5 m, are closure of entry to Australia (except residents returning), and closure of non-essential venues such as night clubs, restaurants, mass attendee sporting events, churches, weddings, and all social gatherings in any circumstance. With some employers encouraging working from home and others requiring it, in addition to job losses, and many children attending school online from home, the implications on travel activity is extreme. We identify the initial impacts associated with the first month of stricter social distancing measures introduced in Australia. • General support for the actions of government and business. • Widespread suppression of travel demand for all trip purposes across all modes. • Sizeable shift to working from home by those who can. • Public transport will face the largest hurdles in regaining confidence. • Retail and food logistics will need to examine distribution processes • The aviation sector will likely need to restart with a heavy focus on domestic travel. • Public transport will need to take overt measures to restore confidence. • The dominance of the car is further enforced in the context of biosecurity concerns. • Active transport is a viable option for short inner-city trips. • Infrastructure investment should be carefully considered. • Flexible working arrangements are perhaps the biggest policy lever available to governments. [ABSTRACT FROM AUTHOR]

• We will monitor compliance with the intervention and adverse events. • Data will be analyzed following intention-to-treat principles. • A cost-effectiveness analysis will be performed. This a priori statistical analysis plan describes the methods of analysis for the Trial Of Prevention Strategies for low back pain (TOPS). TOPS aimed to investigate the effectiveness and cost-effectiveness of exercise and education classes compared with a minimal intervention control in preventing recurrence of low back pain (LBP) in people who have recently recovered from an episode of LBP. TOPS is a superiority, pragmatic, parallel-group randomized controlled trial with allocation concealment, blinded outcome assessors, and intention-to-treat analysis. Participants were randomized to a physical therapist-led exercise and education program for 12 weeks or minimal intervention. The primary outcome was days to recurrence of an episode of LBP. The three key secondary outcomes were days to recurrence of an episode of LBP resulting in (1) activity limitation, (2) care seeking for LBP; and (3) work absence of at least 1 day. Differences in survival curves for the primary (days to recurrence) and secondary outcome (days to LBP with activity limitation, days to care seeking due to LBP, and days to work absence due to LBP) will be compared using Cox regression. Hazard ratios (HRs) and median survival times with 95% confidence intervals (CI) will be calculated. The number of adverse events, including serious adverse events will be reported and the proportion of adverse events between groups will be compared using a Chi-squared test. This paper will provide a detailed description of the planned analyses for the TOPS trial. Australian New Zealand Clinical Trials Registry (ACTRN12615000939594). [ABSTRACT FROM AUTHOR]

Background: Cardiovascular diseases (CVDs) and diabetes are two of the most important public health problems. Outcomes for patients with these disorders vary considerably, likely due to the added influence of a range of interacting clinical, metabolic, environmental, lifestyle, genetic and psychosocial risk factors associated with these diseases. The Baker Biobank study was designed to characterise these factors to inform better risk prediction, earlier diagnosis and better treatment of CVDs and diabetes.Methods: This paper describes the detailed methods for the establishment of the Baker Biobank. The study collected extensive phenotypic detail about the participants recruited from Victoria, Australia. Data and samples were collected at the Departments of Cardiology and Respiratory Medicine at the Alfred Hospital and Healthy Hearts Program at the Baker Institute.Results: A total of 6,530 adults with age 18-69 years were recruited into the Biobank. The majority of these participants (63%) were male. The mean (standard deviation [SD]) age of the Biobank Cohort at the time of data collection was 57(15) years. The study collected data on socio-demographic characteristics, behavioural and lifestyle factors, anthropometric measurements, medical and medication history, and blood levels of various biomarkers. The study also collected and stored Guthrie cards, serum, plasma, buffy coat, whole blood collected in Tempus tubes (for RNA extraction). For some samples extracted DNA and RNA is stored. The Biobank data is also linked to echocardiogram, hospital admission, pathology and mortality datasets. The Baker Biobank data and samples are available for health researchers with approval of Biobank Steering Group and Human Research Ethics Committee.Conclusion: The Baker Biobank provides valuable data and samples into the study of the interplay among cardiovascular diseases risk factors and their impact on morbidity and mortality in Australia. [ABSTRACT FROM AUTHOR]

Towards decarbonizing the global economy, hydrogen produced through water electrolysis is expected to be one of the key solutions for variable renewable energy storage and sector coupling, in particular, via the transport sector in the next few decades. Even though water is an important aspect of the environmental impact, the impact assessment of hydrogen production on water is lacking. This paper proposes a comprehensive methodology for assessing the water footprints of hydrogen production from electrolysis. A major innovative aspect is to demonstrate the geographical distribution of the footprints along the supply chain. The water footprints for hydrogen produced from grid electricity, wind and solar power in Australia was analysed as a case study. Sensitivity analysis was used to evaluate the influence of key parameters including Solar Radiation Level, Silicon Efficiency, and Lifetime of PV Modules. The study finds that the water consumption footprint is much less than that reported in the literature and large part of the water could be consumed indirectly outside of hydrogen producing countries. The quantity of water footprint varies significantly among different assumptions. The findings provide insights into both domestic and cross-boundary water impacts of hydrogen electrolysis and can thus inform policy debates in each nation and beyond. • Water consumption and scarcity footprint of hydrogen production through water electrolysis is quantified. • The water scarcity footprint of hydrogen is 3,000 times less than the quantity reported in the literature. • Water consumption for Australia's highest hydrogen export in 2040 will only be 2% of the national total. • Water consumption from solar PV to hydrogen can vary from 22 to 126 L per kg of hydrogen. • Australia's hydrogen production from solar PV consumes more water in China than in Australia. [ABSTRACT FROM AUTHOR]

This paper reports on an empirical study that explores the ways students approach learning to find and use information. Based on interviews with 15 education students in an Australian university, this study uses phenomenography as its methodological and theoretical basis. The study reveals that students use three main strategies for learning information literacy: 1) learning by doing; 2) learning by trial and error; and 3) learning by interacting with other people. Understanding the different ways that students approach learning information literacy will assist librarians and faculty to design and provide more effective information literacy education. [Copyright &y& Elsevier]

To meet the future energy demand and avert any looming crises, efforts are being carried out to utilize sustainable and renewable energy resources. In this paper, the naturally occurring non-linearity and non-stationarity deficiencies within the climatological predictors to forecast solar radiation (Rdn) are resolved via a multivariate empirical mode decomposition method (MEMD). First, a set of antecedent weekly lags at timescale (t -1) of input datasets were collated and then were divided into training and testing subsets. The MEMD method is restricted to dissolve the training and testing climatic data independently into intrinsic modes functions (IMFs). As the numbers of total IMFs were very large, the singular value decomposition (SVD) algorithm is accustomed for dimensionality reduction simultaneously capturing the most relevant oscillatory features embedded within the IMFs. Finally, the random forest (RF) model is applied to forecast Rdn at selected solar-rich regions in Australia. The resulting hybrid MEMD-SVD-RF model was established as a consequence of the aforementioned modelling strategy. The results are benchmarked with other comparative models. The hybrid MEMD-SVD-RF model generates better and reliable forecasts having significant implications for renewable and sustainable energy applications and resources management. • A double decomposition based solar radiation forecasting model incorporating climate drivers. • Multivariate decomposition splits climate drivers into intrinsic mode functions (IMF). • Singular value decomposition reduces dimensionality to pertinent features from a pool of IMFs. • Random Forest (RF) algorithm used to design newly integrative hybrid model. • Hybrid model provides significant energy management implications. [ABSTRACT FROM AUTHOR]

Introduction: The availability and implementation of evidence-based care is essential to achieving safe, quality trauma patient outcomes. Little is documented, however, about the challenges trauma clinicians face in their day-to day practice, or their views on the availability of evidence. This paper presents the most significant clinical practice challenges reported by multidisciplinary trauma care professionals in Australia and New Zealand, in particular those that may be resolved with focussed research or enhanced implementation activity.Methods: An exploratory survey of trauma professionals from relevant Australia and New Zealand professional organisations was conducted between September 2018 and February 2019 using the Snowballing Method. Participants were recruited via a non-random sampling technique to complete an online survey. Thematic analyses were conducted.Results: There were nine significant clinical practice challenge themes in trauma care, arising from 287 individual clinical practice challenges reported. The most reported being clinical management (bleeding, spinal, older patients) and operationalisation of the trauma system. There was no consensus as to the availability of evidence to guide each theme.Conclusion: Future research should seek to address the clinical practice challenge of Australian and New Zealand trauma community to enable safe, quality trauma patient outcomes. [ABSTRACT FROM AUTHOR]

An accurate predictive model is essential for monitoring the energy produced by a solar system based on different meteorological parameters. In the present paper, a novel machine-learning model named DNN-RODDPSO is proposed to improve the real-time prediction accuracy of the hourly energy produced by four dual-axis solar trackers. This model integrates a new deep neural network (DNN) model with a recent variant of PSO algorithm referred to as a randomly occurring distributed delayed particle swarm optimization (RODDPSO) algorithm. This algorithm is adopted to enhance the training process of the DNN model by reducing the risk of being trapped into local optima and for the search space diversification. Furthermore, to develop the DNN-RODDPSO model, the hourly observations of seven meteorological parameters including time variable measured during 2014–2015 in Alice Springs city, Australia, are used. This model integrates two novel hidden layers, the first one is a selective layer based on daytime/nighttime data selection. The second one named automatic inputs relevance determination to point out the most relevant inputs for an accurate prediction. The obtained results demonstrate the high performance of the two novel hidden layers and the RODDPSO algorithm to improve significantly the prediction accuracy compared to the actual literature standards. • A novel hybrid ANN based on RODDPSO algorithm is developed. • A novel selective layer based on daytime/nighttime data selection is introduced. • A novel automatic inputs relevance determination layer is proposed and validated. • The energy potential produced by four solar trackers is monitored. [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]

• Government schools have lower HPV vaccination coverage compared to other schools. • Absenteeism, consent, language barriers and low literacy are barriers to uptake. • Process improvements with a focus on low coverage schools can address barriers. Human papillomavirus (HPV) vaccination is offered in Australia through school-based programs. While HPV vaccination coverage is high, coverage of the full course of vaccination is suboptimal in Australia and there is a drop in coverage between the first and third doses. This study aimed to describe the drivers of low HPV vaccination coverage in Western Australian (WA) schools and barriers and enablers to improving vaccine coverage. This paper focusses on process and system-level factors. This was a mixed methods study. We analysed WA vaccination coverage data by school, undertook an online survey targeting the individuals responsible for the HPV vaccination program in their schools and school nurses, and compared survey findings and HPV vaccine dose three coverage in schools with 50 or more students in the eligible cohort. We also conducted focus groups with students and interviews with parents in schools with low HPV vaccine coverage. Schools with low HPV vaccine coverage had low coverage for the first dose of HPV vaccine as well as a higher drop off between first and third doses compared to schools with higher HPV vaccine coverage. Respondents from low and middle HPV vaccine coverage schools reported more issues with return of consent forms, low parental literacy, language barriers, absenteeism and difficulty contacting parents compared to schools with high coverage. Parents and students raised a number of challenges in relation to HPV vaccination including student absenteeism, language barriers, and issues with the return of consent forms. A multifaceted approach to improving HPV vaccination coverage should be targeted at schools with low coverage. Based on our findings, these actions should include a range of approaches to obtaining parental consent and intensive follow up with students who are absent on vaccination days. [ABSTRACT FROM AUTHOR]

This paper examines the impact of three fiscal policy shocks on per capita real GDP and income inequality in Australia during the period 1965–2014. A small structural vector autoregressive (SVAR) model is constructed for an open economy for contemporaneous identification and estimation purposes. Based on the evidence of one cointegrating vector among the variables, a structural vector error correction (SVEC) model is specified for the long run. Direct taxation, indirect taxation receipts and government spending are identified as permanent fiscal policy shocks. The convergent use of two different models (SVAR & SVEC) strengthens the credibility of the results. The results have three key policy implications. First, a reduction in direct taxation receipts increases per capita real GDP without increasing income inequality. Second, a reduction in government expenditure significantly increases income inequality. Third, the adverse effect of indirect taxation receipts on income inequality is greater than the redistributive effect of government expenditure, which questions the widely held fiscal policy strategy of using indirect taxation to finance redistributive expenditure. [ABSTRACT FROM AUTHOR]