Search

While there is a significant body of research concerning Catholic faith formation in a variety of educational contexts around the world, relatively little attention has been devoted to the notion of missionary discipleship as a foundation for Catholic formation. Recently, the National Catholic Education Commission, in its document Leading Formation for Mission, also elaborates a solid definition of formation and stated: 'Formation is imaginative, creative and honours adult learning principles [...] It engages the 'intellect' and is nurtured by appropriate theological content and it engages the 'Spirit' and is characterised by contemplation and action for mission' (2022). This paper seeks to contribute to a deeper understanding of formation for missionary discipleship by presenting an evaluation of the efficacy of In Altum, a student-focussed ministry and leadership program developed at the University of Notre Dame Australia in response to the developing magisterial teaching concerning the notion of 'missionary discipleship'. In particular, we examine participants' personal faith development, understanding of missionary discipleship on campus, preparation for future ministry, and understanding of contemporary challenges to discipleship. The study progresses in three parts: First, it provides a brief background to In Altum, including the philosophical and sociological context, as well as the key theological principles underpinning the formation offered within the program. Second, following an overview of the mixed-methodology approach taken in the study, which details both the use of qualitative and quantitative data derived from focus groups and an online survey, the paper presents the results of the study, which sought to investigate the efficacy of the program as it pertained to the following: (a) the building of (personal subjective assessment of) faith in participants; (b) the building of participants' understanding of, and confidence in, the task of evangelisation as missionary discipleship in a secularised context; (c) building a strengthened sense of community amongst the participants. In the third and final section, the reported strengths and weaknesses of the program are examined. The paper also comments on implications for the program on the culture of the university more broadly, including precepts of the program's findings that may be applied in light of the Australian Catholic Plenary Council's findings to enhance the future directions of formation programs in the Catholic University Chaplaincy, with possible application to Catholic secondary schools and parish youth groups. [ABSTRACT FROM AUTHOR]

This article examines the experience and effects of a trauma-responsive program that uses creative methods to address the ongoing psychosocial impacts of transgenerational trauma and youth suicide, which disproportionately affect First Nations people in Australia. Our aim is to understand how the aesthetic (sensory-affective) dimensions of such a program serve to promote experiences of growth after trauma, manifesting in a sense of connection to both self and community. The paper focuses on the second of two immersive, experiential workshops delivered seven months apart in the regional town of Warwick in Queensland, Australia. In the light of self-reports of growth and personal transformation following the initial workshop, the paper examines the key drivers of such growth, focusing in particular on how trauma-related experience is metabolised through cultural containment. It builds on Bion's concept of container/contained, combining analysis of the affordances of immersion. Framed in cultural rather than medical terms, the larger goal of the paper is to establish how cultural programs fill a gap in trauma informed support, facilitating the processing of trauma. [ABSTRACT FROM AUTHOR]

In recent years, mine site closure and rehabilitation have emerged as significant global challenges. The escalating number of abandoned mines, exemplified by over 60,000 in Australia in 2017, underscores the urgency. Growing public concerns and governmental focus on environmental issues are now jeopardising sustainable mining practices. This paper assesses the role of unmanned aerial vehicles (UAVs) in mine closure, exploring sensor technology, artificial intelligence (AI), and mixed reality (MR) applications. Prior research validates UAV efficacy in mining, introducing various deployable sensors. Some studies delve into AI's use for UAV data analysis, but a comprehensive review integrating AI algorithms with MR methods for mine rehabilitation is lacking. The paper discusses data acquisition methods, repeatability, and barriers toward fully autonomous monitoring systems for mine closure projects. While UAVs prove adaptable with various sensors, constraints such as battery life and payload capacity impact effectiveness. Although UAVs hold potential for AI testing in mine closure studies, these applications have been overlooked. AI algorithms are pivotal for creating autonomous systems, reducing operator intervention. Moreover, MR's significance in mine closure is evident, emphasising its application in the mining industry. Ultimately, a hybrid UAV–AI–MR technology is not only viable but essential for achieving successful mine closure and sustainable mining practices in the future. [ABSTRACT FROM AUTHOR]

This paper seeks to deepen the understanding of religious plurality using a range of conceptual lenses and then to draw out some implications for a dialogical approach to religious education in Catholic schools. While what was, until very recent times, seen as conventional religious affiliation has certainly weakened in Australia and elsewhere, this does not necessarily lead to a multiplication of communal beliefs, practices and values. Following Smith, Inglehart and others, what has emerged is a dominant cultural hegemony which has a range of characteristics, but the most pertinent for the discussion here is the loss of the transcendent imperative and the subsequent decline in the knowledge of, and identification with, narratives associated with once-dominant religious communities. An understanding of diversity in the current cultural milieu in Australia needs to consider this hegemony as expressed in a commonality of beliefs, values and practices regardless of expressed affiliation, religious or not. Understanding diversity in this framework establishes a basis for better considering what a dialogical approach to religious education would involve. A dialogical approach to religious education is taken as a settled norm and not one that is heavily contested. A number of the implications of the proposed understanding of diversity for religious education are given. These include following a Vygotskian scaffolded approach to pedagogy and seeing an important place for the articulation of the home religious tradition. [ABSTRACT FROM AUTHOR]

The Upper Hunter Valley is a major coal mining area containing approximately 40% of the currently identified total coal reserves in New South Wales (NSW), Australia. Due to the ongoing increase in mining activities, PM10 (airborne particles with an aerodynamic diameter of less than 10 micrometres) pollution has become a major air quality concern in local communities. This paper summarises the spatial and temporal variability modes of PM10 pollution in the region, based on long-term multi-site monitoring data and the application of the rotated principal component analysis (RPCA) and wavelet analysis techniques. RPCA identified two distinct air quality clusters/subregions in the valley: one in the west/northwest and the other in the southeast. Wavelet analysis revealed the annual cycle to be the most persistent temporal mode of PM10 variability in both subregions, with intermittent signals also observed at time scales of around 120, 30~90, and under 30 days. How these variation modes are related to the effects of local PM10 emissions and the influence of meteorology at different time scales deserves further attention in future work. The findings will be used in air quality reporting and forecasting in NSW. The methodology and results can also be useful for air quality research in similar regions elsewhere. [ABSTRACT FROM AUTHOR]

Simple Summary: The current evidence regarding Indigenous* women and breast cancer in Australia shows lower prevalence but higher mortality rates. There are a range of reasons for this, including co-morbidities, lack of access to health services and low health information fluency. Perhaps most importantly, breast cancer health policy and service delivery practice do not meet the needs of Indigenous women in Australia, according to Indigenous women. Talking and listening to Indigenous women about breast cancer highlight that the solutions to improve breast cancer outcomes are available and that they are not complex. Indigenous women must be involved in the improvement of policy and practice in order for these outcomes to improve. *Terminology: We respectfully refer to Aboriginal and Torres Strait Islander people as "Indigenous". In Australia, the incidence rate of breast cancer is lower in Indigenous* women than non-Indigenous women; however, the mortality rate is higher, with Indigenous women 1.2 times more likely to die from the disease. This paper provides practical and achievable solutions to improve health outcomes for Indigenous women with breast cancer in Australia. This research employed the Context–Mechanism–Outcome (CMO) framework to reveal potential mechanisms and contextual factors that influence breast cancer outcomes for Indigenous women, stratified into multiple levels, namely, micro (interpersonal), meso (systemic) and macro (policy) levels. The CMO framework allowed us to interpret evidence regarding Indigenous women and breast cancer and provides nine practical ways to improve health outcomes and survival rates. [ABSTRACT FROM AUTHOR]

The Forest Fire Danger Index (FFDI) is the main measure used in Australia for estimating fire risk. Recent work by the authors showed that the FFDI forms stable state regimes, nominated as fire climate regimes. These regimes shifted to greater intensity in southern and eastern Australia around the year 2000 and, a decade later, further north. Reductions in atmospheric moisture were the primary contributor. These changes have not been fully incorporated into future projections. This paper compares the recent regime shifts with the most recent national projections of FFDI, published in 2015. They show that for most states and regions, the 2030 upper limit is approached or exceeded by the recent shift, except for two states with large arid zones, South Australia and Western Australia. Methods for attributing past changes, constructing projections, and the inability of climate models to reproduce the recent decreases in atmospheric moisture, all contribute to these underestimates. To address these shortcomings, we make some suggestions to modify efforts aiming to develop seamless predictions and projections of future fire risk. [ABSTRACT FROM AUTHOR]

People with innate variations of sex characteristics (also known as intersex traits or disorders or differences of sex development) have any of a wide range of innate physical traits that differ from medical and social norms for female and male bodies. Responses to these physical differences create experiences and risks of stigmatisation, discrimination, violence, and harmful medical practices intended to promote social and familial integration and conformity with gender stereotypes. As is evident globally, the Australian policy response to the existence and needs of people with innate variations of sex characteristics has been largely incoherent, variously framing the population as having disordered sex development in need of "fixing", and a third sex/gender identity group in need of recognition, with only recent engagement by intersex community-controlled civil society organisations. This paper presents an overview of the context and goals of the intersex human rights movement in Australia. Australian intersex community organisations have sought to apply human rights norms and develop new infrastructure to address key health and human rights issues, and necessitating new ways of resolving policy incoherence. Together with human rights, mental health, and public health institutions, they have called for significant changes to medical models of care and reform to research and classification systems. Intersex community organising and resourcing have made a tangible difference. The Australian Capital Territory is the first jurisdiction in the country to move ahead with reforms to clinical practice, including a legislative prohibition of certain practices without personal informed consent, oversight of clinical decision-making, and investment in psychosocial support. A national community-controlled psychosocial support service has also commenced. [ABSTRACT FROM AUTHOR]

This paper explores the application and advantages of remote sensing, machine learning, and mid-infrared spectroscopy (MIR) as a popular proximal sensing spectroscopy tool in the estimation of soil organic carbon (SOC). It underscores the practical implications and benefits of the integrated approach combining machine learning, remote sensing, and proximal sensing for SOC estimation and prediction across a range of applications, including comprehensive soil health mapping and carbon credit assessment. These advanced technologies offer a promising pathway, reducing costs and resource utilization while improving the precision of SOC estimation. We conducted a comparative analysis between MIR-predicted SOC values and laboratory-measured SOC values using 36 soil samples. The results demonstrate a strong fit (R² = 0.83), underscoring the potential of this integrated approach. While acknowledging that our analysis is based on a limited sample size, these initial findings offer promise and serve as a foundation for future research. We will be providing updates when we obtain more data. Furthermore, this paper explores the potential for commercialising these technologies in Australia, with the aim of helping farmers harness the advantages of carbon markets. Based on our study's findings, coupled with insights from the existing literature, we suggest that adopting this integrated SOC measurement approach could significantly benefit local economies, enhance farmers' ability to monitor changes in soil health, and promote sustainable agricultural practices. These outcomes align with global climate change mitigation efforts. Furthermore, our study's approach, supported by other research, offers a potential template for regions worldwide seeking similar solutions. [ABSTRACT FROM AUTHOR]

One of the significant effects of the September 11 terrorist attacks in New York was the politics of the US-led war on terror encompassing secularism and calls for Islamic reformation. The political discourse of war on terror was not limited to the Americas but was witnessed in other Western nations, such as Australia. The discourse of "Islam needs reforming" by the Prime Minister of Australia, Tony Abbott, in response to the Lindt Café siege (labelled as "Islamic terrorism") tacitly associates Islam with terrorism and represents Muslims negatively to the wider Australian society. This paper with the research question of "How does 'Islam needs reforming' discourse perpetuate Islamophobia?" carried out critical discourse analysis on the selected speeches of Tony Abbott in response to the Lindt Café siege in 2014 to find out the context and implications of Abbott's discourse in relation to calls for Islamic revolution. The study found that Abbott through the example of al-Sisi's (Egypt's president) calls for Islamic reformation forwarded his stance of the need for change in Islam to counter terrorism. Therefore, the present paper argues that the calls for Islamic reformation in response to terrorism can associate Islam with terrorism, thus, perpetuating Islamophobia. [ABSTRACT FROM AUTHOR]

Racialised and culturally distinct refugee groups increasingly face hostilities and negative representations in countries of resettlment. The experience of African refugee youth in Australia illustrates this general trend. This paper explores how racial Othering discourse seriously undermines the group's wellbeing. The article concentrates in particular on two aspects of relational wellbeing, the capacity to move in public without fear or shame and the ability to feel a sense of belonging to the place where one lives in. Theoretically, the paper draws together work on wellbeing from a capability approach and relational perspective with interdisciplinary literature on racial Othering. Empirically, the paper demonstrates the pervasive culture of racial Othering through media identifications of African youth with criminality and gang violence and illustrates impacts on young people's wellbeing through data from interviews with African refugee youth. The youth's accounts show how it feels to be a problem and what it means not to belong. [ABSTRACT FROM AUTHOR]

Using rock art conservation as a focus, this paper outlines the levels of legislated protection afforded to designated natural and cultural areas/sites in Australia and describes the co-management approach adopted in 1998 in relation to Mutawintji National Park in western New South Wales. The park encompasses four different protection categories: a Historic Site, a Nature Reserve, a National Park, and a State Conservation Area. Known for more than a century, the Historic Site is a major area of rock art containing Aboriginal engravings, paintings and stencils. Management of the Historic Site is a key concern, given the tourist interest and associated potential for accelerated deterioration of cultural heritage. The Mutawintji Plan of Management pointed to the importance of Mutawintji for Aboriginal people to connect with the country, and the co-management model encouraged tourism development as a means of providing employment opportunities as Aboriginal guides. No special legislative requirements in relation to rock art conservation, beyond those already in existence, were applied to the co-management system. Using field knowledge involving rock art research and early guide training programs at Mutawintji and literature sources, this paper suggests possible future approaches to rock art conservation in the Mutawintji Lands. [ABSTRACT FROM AUTHOR]

This paper introduces an innovative framework for wind power prediction that focuses on the future of energy forecasting utilizing intelligent deep learning and strategic feature engineering. This research investigates the application of a state-of-the-art deep learning model for wind energy prediction to make extremely short-term forecasts using real-time data on wind generation from New South Wales, Australia. In contrast with typical approaches to wind energy forecasting, this model relies entirely on historical data and strategic feature engineering to make predictions, rather than relying on meteorological parameters. A hybrid feature engineering strategy that integrates features from several feature generation techniques to obtain the optimal input parameters is a significant contribution to this work. The model's performance is assessed using key metrics, yielding optimal results with a Mean Absolute Error (MAE) of 8.76, Mean Squared Error (MSE) of 139.49, Root Mean Squared Error (RMSE) of 11.81, R-squared score of 0.997, and Mean Absolute Percentage Error (MAPE) of 4.85%. Additionally, the proposed framework outperforms six other deep learning and hybrid deep learning models in terms of wind energy prediction accuracy. These findings highlight the importance of advanced data analysis for feature generation in data processing, pointing to its key role in boosting the precision of forecasting applications. [ABSTRACT FROM AUTHOR]

Colonisation, genocide, ecocide, and climate derangement are ongoing, unfurling, global tragedies. In so-called Australia, spiritual practitioners can respond to these crises by deepening their engagement with Aboriginal perspectives/practices. This paper contends that some Eurocentric habitual categorisations subtly misinterpret Aboriginal experiences of the sacred, such as identifying creation myths as beliefs comparable to post-Enlightenment representations of the sacred and identifying the performance of sacred activity with similar characteristics to separateness and priesthood. This leads to erroneous characterisations of Aboriginal ritual practices as being based on a strong hierarchy, distinctive castes, and esotericism. We argue that an embodied and practice-based sense of sacredness guides Aboriginal spirituality. As a living culture, Aboriginal ongoing care for Country provides an enfleshed, real, palpable enactment of human spirituality. We argue that Aboriginal spirituality has been fetishised to the neglect of a call to care for Country in the most 'mundane' sense of tending to food, water, air, etc., as embodied religious experiences. Delving into dadirri and death, we elucidate contemporary cases of practical care for Country that illustrate how being on, in, and with Country can be a contemplative experience. We conclude by outlining how caring for Country 'layers' the various expressions of Aboriginal religious experience socially, psychologically, interpersonally, and ritually. [ABSTRACT FROM AUTHOR]

A large proportion of photovoltaic (PV) power generation is connected to the power grid, and its volatility and stochasticity have significant impacts on the power system. Accurate PV power forecasting is of great significance in optimizing the safe operation of the power grid and power market transactions. In this paper, a novel dual-channel PV power forecasting method based on a temporal convolutional network (TCN) is proposed. The method deeply integrates the PV station feature data with the model computing mechanism through the dual-channel model architecture; utilizes the combination of multihead attention (MHA) and TCN to extract the multidimensional spatio-temporal features between other meteorological variables and the PV power; and utilizes a single TCN to fully extract the temporal constraints of the power sequence elements. The weighted fusion of the dual-channel feature data ultimately yields the ideal forecasting results. The experimental data in this study are from a 26.52 kW PV power plant in central Australia. The experiments were carried out over seven different input window widths, and the two models that currently show superior performance within the field of PV power forecasting: the convolutional neural network (CNN), and the convolutional neural network combined with a long and short-term memory network (CNN_LSTM), are used as the baseline models. The experimental results show that the proposed model and the baseline models both obtained the best forecasting performance over a 1-day input window width, while the proposed model exhibited superior forecasting performance compared to the baseline model. It also shows that designing model architectures that deeply integrate the data input method with the model mechanism has research potential in the field of PV power forecasting. [ABSTRACT FROM AUTHOR]

Simple Summary: Breast cancer is one of the leading causes of cancer-related death in women. The early detection of breast cancer with screening mammograms plays a pivotal role in reducing mortality rates. Although population-based double-reading screening mammograms have reduced mortality by over 31% in women with breast cancer in Europe, continuing this program is difficult due to the shortage of radiologists. Artificial intelligence (AI) is an emerging technology that has provided promising results in medical imaging for disease detection. This study investigates the performance of AI models on an Australian mammographic database, demonstrating how transfer learning from a USA mammographic database to an Australian one, contrast enhancement on mammographic images and the quality of training data according to radiologists' concordance can improve breast cancer diagnosis. Our proposed methodology offers a more efficacious approach for AI to contribute to radiologists' decision making when interpreting mammography images. This paper investigates the adaptability of four state-of-the-art artificial intelligence (AI) models to the Australian mammographic context through transfer learning, explores the impact of image enhancement on model performance and analyses the relationship between AI outputs and histopathological features for clinical relevance and accuracy assessment. A total of 1712 screening mammograms (n = 856 cancer cases and n = 856 matched normal cases) were used in this study. The 856 cases with cancer lesions were annotated by two expert radiologists and the level of concordance between their annotations was used to establish two sets: a 'high-concordances subset' with 99% agreement of cancer location and an 'entire dataset' with all cases included. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of Globally aware Multiple Instance Classifier (GMIC), Global-Local Activation Maps (GLAM), I&H and End2End AI models, both in the pretrained and transfer learning modes, with and without applying the Contrast Limited Adaptive Histogram Equalization (CLAHE) algorithm. The four AI models with and without transfer learning in the high-concordance subset outperformed those in the entire dataset. Applying the CLAHE algorithm to mammograms improved the performance of the AI models. In the high-concordance subset with the transfer learning and CLAHE algorithm applied, the AUC of the GMIC model was highest (0.912), followed by the GLAM model (0.909), I&H (0.893) and End2End (0.875). There were significant differences (p < 0.05) in the performances of the four AI models between the high-concordance subset and the entire dataset. The AI models demonstrated significant differences in malignancy probability concerning different tumour size categories in mammograms. The performance of AI models was affected by several factors such as concordance classification, image enhancement and transfer learning. Mammograms with a strong concordance with radiologists' annotations, applying image enhancement and transfer learning could enhance the accuracy of AI models. [ABSTRACT FROM AUTHOR]

Battery energy storage systems can be integrated with photovoltaic (PV)-diesel microgrids as an enabling technology to increase the penetration of PV systems and aid microgrid stability by smoothing out the power fluctuations of the PV systems. This paper focuses on this topic and aims to derive correlations between the optimal capacity of the smoothing batteries and variabilities in the daily solar irradiance. To this end, the two most commonly used moving average and ramp rate control techniques are employed on a real solar irradiance dataset with a 1-min resolution for a full calendar year across 11 sites in Australia. The paper then presents the developed empirical model, based on linear regressions, to estimate the batteries' optimal capacity without requiring detailed simulation studies, which are useful for practitioners at the early stages of a project's feasibility evaluation. The performance of the developed technique is validated through numerical simulation studies in MATLAB®. The study demonstrates that the empirical model provided reasonably accurate estimates when using the moving average smoothing technique but had limited accuracy under the ramp rate control technique. [ABSTRACT FROM AUTHOR]

Many studies in recent years have been devoted to estimating the per-pixel proportions of three broad classes of materials (e.g., photosynthetic vegetation, non-photosynthetic vegetation and bare soil) using data from multispectral sensors. Oftentimes, the estimated proportions are used to monitor environmental change in both urban and non-urban environments. Many of these papers use proportion estimation methods based on the linear mixture model. Very few of these papers assess the accuracy of their estimators. This paper shows how to produce confidence intervals (CIs) and joint confidence regions (JCRs) for the proportions associated with various linear mixture models. There are two main models, both of which assume that the coefficients in the model are non-negative. The first model assumes that the coefficients sum to 1. The second does not, but uses rescaling of the estimated coefficients to produce estimated proportions. Three variants of these two models are also analysed. JCRs are shown to be particularly informative, because they are typically better at localising the information than CIs are. The methodology is illustrated using examples from Landsat Thematic Mapper data at 1169 locations across Australia, each of which has associated field observations. There is also a discussion about the extent to which the methodology can be extended to hyperspectral data. [ABSTRACT FROM AUTHOR]

Simple Summary: The dairy industry in Australia and New Zealand is pasture-based, therefore, monitoring failed transfer of passive immunity (FTPI) is challenging. This study involved a systematic literature search and meta-analysis of papers reporting FTPI data from dairy calves within eight days of birth in Australia and New Zealand, until the end of 2022. An overall prevalence of 33% of FTPI in dairy calves in Australasia and a prevalence of 38% at the farm level were calculated from the meta-analysis, comparable to rates observed elsewhere. Factors, such as the frequency of calf removal from the calving area, time of the first colostrum feed after birth, colostrum volume and quality, and other management practices, were found to play a significant role in FTPI in Australasia. Monitoring and minimizing the prevalence of failed transfer of passive immunity (FTPI) in dairy replacement calves within the first week of life is crucial for calf health and farm profitability. In this study, a systematic literature search and meta-analysis were conducted on papers reporting the prevalence of FTPI in calves from pasture-based dairy farms in Australia and New Zealand. Two search methods, a "traditional method" and a "search engine method", were conducted to identify published studies on FTPI in Australia and New Zealand. Data from a total of 13,430 calves from eight studies in Australasia were included in the analysis for FTPI within 8 days of birth. The meta-analysis revealed that the average prevalence of FTPI was 33% across the two countries, with the lowest FTPI (9%) in Western Australia and the highest FTPI (59%) in New Zealand. Using farm data from three studies, the average prevalence of FTPI at the farm level in Australasia was 38%, with the lowest prevalence found in a farm in South Australia (6%). In conclusion, the meta-analysis confirmed the need for good management of cows and newborn calves after birth in pasture-based systems to reduce FTPI in calves. Collecting newborn calves from pasture at least twice per day after birth and providing colostrum of sufficient quantity and quality as soon as possible were the best practices for preventing FTPI in Australasian dairy systems. [ABSTRACT FROM AUTHOR]

The shift from large-scale centralised energy systems to smaller scale decentralised systems based on Distributed Energy Resources (DER) is likely to cause a sector-wide replacement of current electricity management practices and business models—creating a new energy paradigm. If handled well, such a transition will not be inherently disruptive; however, it can cause major disruption if long-held views and assumptions are not rapidly reconsidered and renewed, and new supporting structures are not swiftly put in place—hence, if disruption is experienced it will be due to a lack of strategic responses rather than the nature of the technology. This paper clarifies the nature of DERs and outlines key issues and opportunities associated with a range of associated service configurations and business models. The paper outlines key factors affecting the viability of such approaches and identifies leverage points for accelerating uptake. The paper concludes by considering how shifting landscape factors and related opportunities in the coming decades will shape the transition to a decentralised energy system. This paper contains findings from research performed at the Renewable, Affordable, Clean Energy Cooperative Research Centre (RACE CRC) in Australia. [ABSTRACT FROM AUTHOR]

Since 2015, religious freedom has become a heated and divisive political and public policy issue in Australia. While rarely defined or interrogated, 'religious freedom' does not exist as a value-neutral principle with a single meaning. Rather, its discursive constructions are varied and serve to promote certain interests at the expense of others. Offering a new perspective on the politics of religious freedom, this paper draws together four separate studies of the public discourse of religious freedom in Australia (spanning 35 years from 1984 to 2019) to chart how its framing has changed over time and to explore the implications of these changes. This analysis reveals three major discourses of religious freedom emerging over three phases: 'religious diversity'; 'balancing rights'; and 'freedom of belief'. This paper demonstrates how, once used to promote a progressive social agenda, religious freedom has become weaponised by the Christian Right and culture warriors in their battle to entrench in law the ongoing acceptability of discrimination against LGBTIQ+ people. [ABSTRACT FROM AUTHOR]

One of the major public health measures to manage and contain the outbreak of the COVID-19 pandemic was to engage in systematic contact tracing, which required gastronomy, community and sporting venues to keep patron registers. Stand-alone and web-based applications, developed by a range of private IT providers, soon replaced pen-and-paper lists. With the introduction of a uniform, state-wide, mandatory data collection system, these private applications became obsolete. Although only active for four months, these applications paved the way for the public acceptance of state-administered collection systems that allowed for an unprecedented, centralized tracking system of the movements of the entire population. This paper discusses the cultural significance of these applications as a game changer in the debate on civil liberties, and addresses the question of how the materiality, or lack thereof, of this digital heritage affects the management of ephemeral smartphone applications, and its preservation for future generations. [ABSTRACT FROM AUTHOR]

Recent events within the Australian National Electricity Market have demonstrated that the system of an energy-only market (a market that only compensates power that has been produced) is no longer fit for purpose. The rate of change in installed capacity and generation requires better planning to ensure reliability is maintained at the lowest total system cost during the transition to net zero. Australian National Electricity Market participants will need sufficient incentives and confidence to invest in new capacity. This paper assesses a "no constraints" scenario and recommends a range of policy and market mechanisms that could be utilized to achieve a net zero National Electricity Market in Australia by 2050. This paper adopts the perspective of total system cost, which allows multiple factors relating to decision-making to be incorporated. In the absence of a carbon price, this paper seeks to put forward technology-based policy and market mechanisms to incentivise the changes required. The "Modelling Energy and Grid Services" model used in this study has shown that this "no constraints" future grid will need to contain approximately 100 GW of variable renewable energy, almost 20 GW of firm, low-emissions generation, such as carbon capture, utilisation and storage, bioenergy with carbon capture and storage, hydroelectric power, or nuclear power. It will also require more than 10 GW of storage, including pumped hydro energy storage and other energy storage technologies, and over 30 GW of firm, dispatchable peaking plants, including thermal power generation. [ABSTRACT FROM AUTHOR]

Domestic water heating accounts for 15% to 27% of the total energy consumption in buildings in Australia. Over the past two decades, the latent heat thermal energy storage (LHTES) system has been widely investigated as a way to reduce fossil fuel consumption and increase the share of renewable energy in solar water heating. However, the research has concentrated on the geometric optimisation of the LHTES heat exchanger for the past few years, and this might not be sufficient for commercialisation. Moreover, recent review papers mainly discussed the development of a particular heat-transfer improvement technique. This paper presents perspectives on various solar hot water systems using LHTES to shift focus to on-demand performance studies, as well as structure optimisation studies for faster commercialisation. Future challenges are also discussed. Since the topic is an active area of research, this paper focuses on references that showcase the overall performance of LHTES-assisted solar hot water systems and cannot include all published work in the discussion. This perspective paper provides directional insights to researchers for developing an energy-efficient solar hot water system using LHTES. [ABSTRACT FROM AUTHOR]

To solve the problem of feature selection and error correction after mode decomposition and improve the ability of power load forecasting models to capture complex time series information, a two-stage short-term power load forecasting method based on recursive feature elimination with a cross validation (RFECV) algorithm and time convolution network–efficient channel attention mechanism–long short-term memory network (TCN–ECA–LSTM) is presented. First, the load sequence is decomposed into a relatively stable set of modal components using variational mode decomposition. Then, the RFECV-based method filters the feature set of each modal component to construct the best feature set. Finally, a two-stage prediction model based on TCN–ECA–LSTM is established. The first stage predicts each modal component and the second stage reconstructs the load forecast based on the predicted value of the previous stage. This paper takes actual data from New South Wales, Australia, as an example, and the results show that the method proposed in this paper can build the feature set reliably and efficiently and has a higher accuracy than the conventional prediction model. [ABSTRACT FROM AUTHOR]

Simple Summary: In radiotherapy treatment, organs at risk and target volumes are contoured by the clinicians to prepare a dosimetry plan. In retrospective data, these structures are not often standardised to universal names across the patients plans, which is required to enable data mining and analysis. In this paper, a new method was proposed and evaluated to automatically standardise radiotherapy structures names using machine learning algorithms. The proposed approach was deployed over a dataset with 1613 patients collected from Liverpool & Macarthur Cancer Therapy Centres, New South Wales, Australia. It was concluded that machine learning techniques can standardise the dosimetry plan structures, taking into consideration the integration of multiple modalities representing each structure during the training process. In progressing the use of big data in health systems, standardised nomenclature is required to enable data pooling and analyses. In many radiotherapy planning systems and their data archives, target volumes (TV) and organ-at-risk (OAR) structure nomenclature has not been standardised. Machine learning (ML) has been utilised to standardise volumes nomenclature in retrospective datasets. However, only subsets of the structures have been targeted. Within this paper, we proposed a new approach for standardising all the structures nomenclature by using multi-modal artificial neural networks. A cohort consisting of 1613 breast cancer patients treated with radiotherapy was identified from Liverpool & Macarthur Cancer Therapy Centres, NSW, Australia. Four types of volume characteristics were generated to represent each target and OAR volume: textual features, geometric features, dosimetry features, and imaging data. Five datasets were created from the original cohort, the first four represented different subsets of volumes and the last one represented the whole list of volumes. For each dataset, 15 sets of combinations of features were generated to investigate the effect of using different characteristics on the standardisation performance. The best model reported 99.416% classification accuracy over the hold-out sample when used to standardise all the nomenclatures in a breast cancer radiotherapy plan into 21 classes. Our results showed that ML based automation methods can be used for standardising naming conventions in a radiotherapy plan taking into consideration the inclusion of multiple modalities to better represent each volume. [ABSTRACT FROM AUTHOR]

Accurate short-term power load forecasting is crucial to maintaining a balance between energy supply and demand, thus minimizing operational costs. However, the intrinsic uncertainty and non-linearity of load data substantially impact the accuracy of forecasting results. To mitigate the influence of these uncertainties and non-linearity in electric load data on the forecasting results, we propose a hybrid network that integrates variational mode decomposition with a temporal convolutional network (TCN) and a bidirectional gated recurrent unit (BiGRU). This integrated approach aims to enhance the accuracy of short-term power load forecasting. The method was validated on load datasets from Singapore and Australia. The MAPE of this paper's model on the two datasets reached 0.42% and 1.79%, far less than other models, and the R2 reached 98.27% and 97.98, higher than other models. The experimental results show that the proposed network exhibits a better performance compared to other methods, and could improve the accuracy of short-term electricity load forecasting. [ABSTRACT FROM AUTHOR]

The frequency and severity of extremes, including extreme precipitation events, extreme evapotranspiration and extreme water storage deficit events, are changing. Thus, the necessity for developing a framework that estimates non-stationary conditions is urgent. The aim of this paper is to develop a framework using the geeSEBAL platform, Generalised Extreme Value (GEV) models and spatiotemporal analysis techniques that incorporate the physical system in terms of cause and effect. Firstly, the geeSEBAL platform has enabled the estimation of actual evapotranspiration (ETa) with an unprecedented level of spatial-temporal resolution. Following this, the Non-stationary Extreme Value Analysis (NEVA) approach employs the Bayesian method using a Differential Evolution Markov Chain technique to calculate the frequency and magnitude of extreme values across the parameter space. Station and global climate datasets have been used to analyse the spatial and temporal variation of rainfall, reference evapotranspiration (ETo), ETa and water storage (WS) variables in the Lockyer Valley located in Southeast Queensland (SEQ), Australia. Frequency analysis of rainfall, ETa, and water storage deficit for 14 stations were performed using a GEV distribution under stationary and non-stationary assumptions. Comparing the ETa, ETo and ERA5 rainfall with station data showed reasonable agreement as follows: Pearson correlation of 0.59–0.75 for ETa, RMSE of 45.23–58.56 mm for ETa, Pearson correlation of 0.96–0.97 for ETo, RMSE of 73.13–87.73 mm for ETo and Pearson correlation of 0.87–0.92 for rainfall and RMSE of 37.53–57.10 mm for rainfall. The lower and upper uncertainty bounds between stationary and non-stationary conditions for rainfall station data of Gatton varied from 550.98 mm (stationary) to 624.97 mm (non-stationary), and for ERA5 rainfall datasets, 441.30 mm (stationary) to 450.77 mm (non-stationary). The results demonstrate that global climate datasets underestimate the difference between stationary and non-stationary conditions by 9.47 mm compared to results of 73.99 mm derived from station data. Similarly, the results demonstrate less variation between stationary and non-stationary conditions in water storage, followed by a sharp variation in rainfall and moderate variation in evapotranspiration. The findings of this study indicate that neglecting the non-stationary condition in some hydrometeorological variables can lead to underestimating their amounts. This framework can be applied to any geographical area for estimating extreme conditions, providing valuable insights for infrastructure planning and design, risk assessment and disaster management. [ABSTRACT FROM AUTHOR]

Australia has clear aspirations to become a major global exporter of hydrogen as a replacement for fossil fuels and as part of the drive to reduce CO2 emissions, as set out in the National Hydrogen Strategy released in 2019 jointly by the federal and state governments. In 2021, the Australian Energy Market Operator specified a grid forecast scenario for the first time entitled "hydrogen superpower". Not only does Australia hope to capitalise on the emerging demand for zero-carbon hydrogen in places like Japan and South Korea by establishing a new export industry, but it also needs to mitigate the built-in carbon risk of its export revenue from coal and LNG as major customers, such as Japan and South Korea, move to decarbonise their energy systems. This places hydrogen at the nexus of energy, climate change mitigation and economic growth, with implications for energy security. Much of the published literature on this topic concentrates on the details of what being a major hydrogen exporter will look like and what steps will need to be taken to achieve it. However, there appears to be a gap in the study of the implications for Australia's domestic energy system in terms of energy security and export economic vulnerability. The objective of this paper is to develop a conceptual framework for the implications of becoming a major hydrogen exporter on Australia's energy system. Various green hydrogen export scenarios for Australia were compared, and the most recent and comprehensive was selected as the basis for further examination for domestic energy system impacts. In this scenario, 248.5 GW of new renewable electricity generation capacity was estimated to be required by 2050 to produce the additional 867 TWh required for an electrolyser output of 2088 PJ of green hydrogen for export, which will comprise 55.9% of Australia's total electricity demand at that time. The characteristics of comparative export-oriented resources and their interactions with the domestic economy and energy system are then examined through the lens of the resource curse hypothesis, and the LNG and aluminium industries. These existing resource export frameworks are reviewed for applicability of specific factors to export-oriented green hydrogen production, with applicable factors then compiled into a novel conceptual framework for exporter domestic implications from large-scale exports of green hydrogen. The green hydrogen export superpower (2050) scenario is then quantitatively assessed using the established indicators for energy exporter vulnerability and domestic energy security, comparing it to Australia's 2019 energy exports profile. This assessment finds that in almost all factors, exporter vulnerability is reduced, and domestic energy security is enhanced by the transition from fossil fuel exports to green hydrogen, with the exception of an increase in exposure of the domestic energy system to international market forces. [ABSTRACT FROM AUTHOR]

Simple Summary: Crofton weed toxicity, caused by Ageratina adenophora, has been recognized as a cause of fatal lung disease in horses for over a century. Despite its impact on horse health in many areas of the world, the toxic syndrome is poorly understood and understudied. This paper looks at the prior research on weed biology, the potential toxicology mechanisms, and the pathology in horses and other species, as well as the future directions to improve our understanding of this fatal toxic weed affecting horses. Crofton weed (Ageratina adenophora) is a global and highly invasive weed, with ingestion causing severe respiratory disease in horses, leading to irreversible and untreatable pulmonary fibrosis and oedema. While reports of equine pneumotoxicity remain common in Australia and New Zealand, equine pneumotoxicity may be underdiagnosed in other countries where Crofton weed is endemic but poorly differentiated. The pathogenesis of Crofton weed toxicity following ingestion has been well described in a number of different animal models, including rodents, rabbits, and goats. However, induced toxicity is organ-selective across different animal species, and these vastly differ from the pathogenesis described in horses, both clinically and after experimental exposure. Sources of variation may include species-specific susceptibility to different toxins present in the plant, different mechanistic processes of toxicity, and species differences in toxin biotransformation and bioactivation across different organs. Considering disease severity and Crofton weed's invasiveness globally, assessing published toxicological and exposure data is necessary to advance research, identify specific toxins for horses, and possible prophylactic and therapeutic strategies. This review presents an overview of the available literature on equine toxicity, parallels between toxicity in horses and other animal species, and important aspects to be included in the future research agenda. [ABSTRACT FROM AUTHOR]

Environmental damage has been of much concern, particularly in coastal areas and the oceans, given climate change and the drastic effects of pollution and extreme climate events. Our present-day analytical capabilities, along with advancements in information acquisition techniques such as remote sensing, can be utilised for the management and study of coral reef ecosystems. In this paper, we present Reef-Insight, an unsupervised machine learning framework that features advanced clustering methods and remote sensing for reef habitat mapping. Our framework compares different clustering methods for reef habitat mapping using remote sensing data. We evaluate four major clustering approaches based on qualitative and visual assessments which include k-means, hierarchical clustering, Gaussian mixture model, and density-based clustering. We utilise remote sensing data featuring the One Tree Island reef in Australia's Southern Great Barrier Reef. Our results indicate that clustering methods using remote sensing data can well identify benthic and geomorphic clusters in reefs when compared with other studies. Our results indicate that Reef-Insight can generate detailed reef habitat maps outlining distinct reef habitats and has the potential to enable further insights for reef restoration projects. [ABSTRACT FROM AUTHOR]

Low-carbon building regulations are acknowledged as critical instruments to facilitate the building industry's decarbonization transition. However, recent studies have shown that non-compliance with low-carbon requirements is under-researched, leading to a significant divergence between policy intentions and actual performance. In light of this, the paper aims to provide a synthesis of existing research on non-compliance with low-carbon building regulations. It does this using a systematic literature review combined with bibliometric and text mining techniques. Through reviewing 26 scholarly works from the last decade, the paper demonstrates a peak production year around 2015, the year of the Paris Agreement, with the USA and Australia as key countries of concern. Subsequently, the study reveals three focused research areas: the development of building policy during the low-carbon transition; the role of building energy performance requirements in achieving low-carbon buildings; and building energy code compliance. Findings suggest widespread non-compliance with building energy codes and also indicate influencing factors and associated enhancement strategies. Finally, the paper identifies gaps in the investigation of new forms of building energy codes; an inconsistent conception of compliance; and a lack of understanding in building practitioners' compliance behavior. The study contributes to knowledge by providing future research areas in this under-researched topic and by successfully applying both bibliometric and text mining analysis in the construction management domain. This is found to have advantages in terms of time efficiency and objectivity. It also offers practical implications for industry by minimizing the gap between policy intentions and real compliance performance. [ABSTRACT FROM AUTHOR]

This paper investigates the determinants of refugee students' social integration in Lebanon, Turkey, and Australia. This paper seeks to understand how legal status and the corresponding length of refugee asylum shape refugee children's social integration. The three host countries offer refugees different legal statuses ranging from short-term in Lebanon, medium-term in Turkey, and long-term in Australia. Therefore, our data collection covers a sample of 1298 middle school refugee students from all three countries. Our probit regression analysis sheds light on the importance of micro-level factors related to individual and household characteristics and meso-level factors related to school factors shaping refugee students' social integration. The statistical dominance of meso-level factors indicates that the within-country differences are stronger than the between-country differences, yet it does not rule out the importance of macro policies that indirectly influence refugee students' social integration by shaping provisions at the micro and meso levels. [ABSTRACT FROM AUTHOR]

Accurate electricity price forecasting (EPF) can provide a necessary basis for market decision making by power market participants to reduce the operating cost of the power system and ensure the system's stable operation. To address the characteristics of high frequency, strong nonlinearity, and high volatility of electricity prices, this paper proposes a short-term electricity price forecasting model based on a two-layer variational modal decomposition (VMD) technique, using the sparrow search algorithm (SSA) to optimize the long and short-term memory network (LSTM). The original electricity price sequence is decomposed into multiple modal components using VMD. Then, each piece is predicted separately using an SSA-optimized LSTM. For the element with the worst prediction accuracy, IMF-worst is decomposed for a second time using VMD to explore the price characteristics further. Finally, the prediction results of each modal component are reconstructed to obtain the final prediction results. To verify the validity and accuracy of the proposed model, this paper uses data from three electricity markets, Australia, Spain, and France, for validation analysis. The experimental results show that the proposed model has MAPE of 0.39%, 1.58%, and 0.95%, RMSE of 0.25, 0.9, and 0.3, and MAE of 0.19, 0.68, and 0.31 in three different cases, indicating that the proposed model can well handle the nonlinear and non-stationarity characteristics of the electricity price series and has superior forecasting performance. [ABSTRACT FROM AUTHOR]

To reduce greenhouse gas emissions, nations have introduced energy efficiency regulations for new and existing buildings. This has been considered advantageous as more efficient building envelopes would reduce energy consumed to heat and cool home interiors to within accepted thermal comfort bandwidths. However, as these methods have been adopted, many nations have identified an unintended visible presence of surface and interstitial condensation and mould in new code-compliant buildings. In Australia, it has been estimated that up to 50% of Australian houses constructed in the last decade (2006–2016) have a presence of condensation and mould. Australia introduced its first condensation and mould-related building regulations for new homes in 2019. This paper reports on the hygrothermal and mould growth analysis of the most common low-rise residential external wall system, a timber-framed clay masonry veneer wall. A key component of this paper discusses the application of innovative methods in the Australian context. The external wall's moisture accumulation and mould growth were simulated for a period of ten years using the transient hygrothermal simulation tool, WUFI® Pro, and the mould growth model, WUFI® VTT. This study identified significant risks for this typical external wall system when constructed in a temperate climate. [ABSTRACT FROM AUTHOR]

Previously published studies on Australia's energy security did not examine the country's domestic energy security situation in tandem with its international energy statecraft. This paper fills this research gap. In order to provide a robust analysis of a country's strategic options in the energy sector, it is paramount to balance domestic and international dimensions, along with internal and external factors. The paper utilizes the strengths, weaknesses, opportunities, and threats (SWOT) method to review Australia's strategic options by balancing the inward-looking, domestic risk minimization dimension (energy security), with the outward-looking, international power projection dimension (energy statecraft). The paper also applies the 4A framework (availability, accessibility, affordability, and acceptance) to assess Australia's energy security performance. On the one hand, the results demonstrate that Australia has many strengths and opportunities as a reliable and stable energy supplier, endowed with traditional and renewable energy resources, and critical minerals. On the other hand, numerous internal weaknesses and external threats may affect Australia's strategic options in the future. The most pressing issue is the historical lack of strategic government intervention in the energy market, which has, paradoxically, resulted in domestic energy accessibility and affordability crisis. The market-based approach is also the main reason why Australia has not transformed its energy resources into capabilities to be used as instruments of statecraft. The paper uses the SWOT analysis and the 4A assessment as the basis for discussion on how Australia can transform its energy sector weaknesses and threats into strengths and opportunities, to benefit the national interest. [ABSTRACT FROM AUTHOR]

Simple Summary: Existing food production systems and dietary behaviours are not healthy nor sustainable due to the higher environmental footprint of animal-derived foods. Alternative dietary choices could provide better outcomes. We investigated Generation Z (Gen Z)'s alternative food preferences within a planetary health framework which combines human and ecological well-being. The paper is based on data from a 2021 cross-national survey conducted in the main Australian cities, which explored Gen Z's attitudes towards meat consumption in relation to climate change and alternatives to animal-based proteins. Climate change is seen as a result of human activities by 86% of the survey participants. More than a third (38%) of them believe that livestock production and the consumption of animal-sourced foods are contributing significantly to climate change and environmental deterioration. The remaining majority (62%), however, has a low awareness and understanding of the food systems' impacts, disbelieving that diet is a major contributor to climate change. We discuss how these findings will shape Australia's Gen Z, climate change and the future of alternative proteins. Scientific evidence shows that current food systems are impacting the planet in ways that are unsustainable and detrimental to human health. Various technological advances have been made in response, one of them being the development of new food products known as novel alternative proteins, including cultured meat, plant-based meat analogues, algae- and insect-based foods. The future of these alternative proteins to a large extent depends on consumer acceptance from young people. This study investigates the attitudes of Australia's adult Generation Z (Gen Z), born between 1995 and 2003, regarding climate change and more sustainable food choices. Gen Z is a diverse, important and trendsetting group known for organising globally on causes related to climate, social justice and health. The study of Australia's Gen Z is based on a 2021 cross-national survey in the main Australian cities. It shows that, although 86% of the participants perceive climate change as anthropogenic, only 38% believe that livestock-based foods are contributing significantly to global warming and environmental deterioration. The paper discusses the implications for Gen Z and novel alternative proteins given that the majority of Australia's young people has low awareness of the environmental impacts of food systems and dietary choices. [ABSTRACT FROM AUTHOR]

This document is an editorial from the journal "Viruses" discussing tobamoviruses, which are plant-infecting viruses with an ancient lineage dating back to the Cretaceous period. Tobamoviruses are known for their resilience and ability to remain viable for long periods of time. Some tobamoviruses pose a threat to crops, and efforts are being made to understand their transmission and develop biosecurity measures. The editorial highlights several research papers on topics such as the host range of cucumber green mottle mosaic virus, the transmission of tomato brown rugose fruit virus, and the effectiveness of biosecurity measures in Australia. Additionally, the editorial mentions a study on using tobamovirus particles for biomedical applications. The author concludes by acknowledging that more tobamoviruses will likely be discovered in the future, presenting both challenges and opportunities for scientists. [Extracted from the article]

Fires in buildings are significant public safety hazards and can result in fatalities and substantial financial losses. Studies have shown that the socioeconomic makeup of a region can impact the occurrence of building fires. However, existing models based on the classical stepwise regression procedure have limitations. This paper proposes a more accurate predictive model of building fire rates using a set of socioeconomic variables. To improve the model's forecasting ability, a backward elimination by robust final predictor error (RFPE) criterion is introduced. The proposed approach is applied to census and fire incident data from the South East Queensland region of Australia. A cross-validation procedure is used to assess the model's accuracy, and comparative analyses are conducted using other elimination criteria such as p-value, Akaike's information criterion (AIC), Bayesian information criterion (BIC), and predicted residual error sum of squares (PRESS). The results demonstrate that the RFPE criterion is a more accurate predictive model based on several goodness-of-fit measures. Overall, the RFPE equation was found to be a suitable criterion for the backward elimination procedure in the socioeconomic modeling of building fires. [ABSTRACT FROM AUTHOR]

As the COVID-19 pandemic begins to abate and national public health systems are treating the SARS-CoV-2 virus as endemic, many public health measures are no longer mandated but remain recommended with voluntary participation. One of these is the wearing of fitted face masks, initially mandated to contain, or at least slow, the spread of SARS-CoV-2, which is primarily transmitted via aerosols emitted while breathing, coughing, or sneezing. Although the habit of once wearing fitted face masks recedes into memory for much of the population, so does the knowledge of the various types of masks that were once en vogue. To create a record for the future, this paper provides the first comprehensive documentation of the nature and range of fitted facemasks that circulated during the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

The increasing attacks on traffic signals worldwide indicate the importance of intrusion detection. The existing traffic signal Intrusion Detection Systems (IDSs) that rely on inputs from connected vehicles and image analysis techniques can only detect intrusions created by spoofed vehicles. However, these approaches fail to detect intrusion from attacks on in-road sensors, traffic controllers, and signals. In this paper, we proposed an IDS based on detecting anomalies associated with flow rate, phase time, and vehicle speed, which is a significant extension of our previous work using additional traffic parameters and statistical tools. We theoretically modelled our system using the Dempster–Shafer decision theory, considering the instantaneous observations of traffic parameters and their relevant historical normal traffic data. We also used Shannon's entropy to determine the uncertainty associated with the observations. To validate our work, we developed a simulation model based on the traffic simulator called SUMO using many real scenarios and the data recorded by the Victorian Transportation Authority, Australia. The scenarios for abnormal traffic conditions were generated considering attacks such as jamming, Sybil, and false data injection attacks. The results show that the overall detection accuracy of our proposed system is 79.3% with fewer false alarms. [ABSTRACT FROM AUTHOR]

Wood is a renewable material that can store biogenic carbon, and waste wood can be recycled to recover bioenergy. The amount of energy recovery from the waste wood can vary depending on the type of wood and its chemical and structural properties. This paper will analyse the life cycle environmental impact of energy recovery from waste wood, starting from the wood production stage. These are cradle-to-cradle systems, excluding the use phase and the waste collection phase. The types of waste wood considered in the current study are softwood, hardwood, medium-density fibreboard (MDF), plywood, and particleboard. The results showed that all waste wood has great potential to produce energy while reducing climate change impact. Hardwood and softwood products showed the most beneficial aspects in terms of energy recovery from waste wood and thus could help to reduce harmful environmental emissions. However, MDF and particleboard show the least potential for energy recovery as they contribute to the greatest emissions among all types of wood products. The outcomes of this study could be used as guiding principles for Australia to consider waste-to-energy recovery facility establishment to generate additional energy while reducing waste wood. [ABSTRACT FROM AUTHOR]

The degree of difficulty in crushing an ore depends on the composition of the ore itself. Due to different types and compositions of ores, the crushing mechanism of ores during the crushing process is also different. In order to quantitatively analyze the impact crushing characteristics of mineral components in ores, this paper takes pure mineral quartz, pyrrhotite, and pyrite as the research objects and uses the universal drop weight impact crushing test equipment and standard test methods developed by the JK Mineral Research Center of the University of Queensland, Australia, to conduct JK drop weight tests on these three pure mineral samples. The results show that the particle size distribution of impact crushing products is wide, covering all particle sizes from "0" to close to the feed particle size, and the yield distribution of each product particle size is relatively uniform. There are critical values and "energy barrier" effects for the impact-specific crushing energy. The impact-specific crushing energy has a significant impact on the particle size composition and crushing effect of the crushing product, and there is an interactive effect between the impact-specific crushing energy and the feed particle size and mineral type. The impact crushing resistance of the sample can be characterized by using Mohs hardness, impact crushing characteristic parameters, impact crushing resistance level, and the yield limit value t10 of the characteristic crushing particle size. The overall characterization results have good consistency. [ABSTRACT FROM AUTHOR]

Offshore wind farms are a current area of interest in Australia due to their ability to support its transition to renewable energy. Climate reanalysis datasets that provide simulated wind speed data are frequently used to evaluate the potential of proposed offshore wind farm locations. However, there has been a lack of comparative studies of the accuracy of wind speed predictions from different reanalysis datasets for offshore wind farms in Australian waters. This paper assesses wind speed distribution accuracy and compares predictions of offshore wind turbine power output in Australia from three international reanalysis datasets: BARRA, ERA5, and MERRA-2. Pressure level data were used to determine wind speeds and capacity factors were calculated using a turbine bounding curve. Predictions across the datasets show consistent spatial and temporal variations in the predicted plant capacity factors, but the magnitudes differ substantially. Compared to weather station data, wind speed predictions from the BARRA dataset were found to be the most accurate, with a higher correlation and lower average error than ERA5 and MERRA-2. Significant variation was seen in predictions and there was a lack of similarity with weather station measurements, which highlights the need for additional site-based measurements. [ABSTRACT FROM AUTHOR]

Simple Summary: When nine-week-old Azaria Chamberlain disappeared from a central Australian campsite in 1980, few accepted her mother's claim that 'A dingo's got my baby'. Dingoes, it was popularly believed at this time, simply did not attack humans. A recent spate of dingo attacks has repudiated this widespread narrative—but when and why did it arise? Analysis of historical Australian print media shows that, in fact, dozens of accounts of dingo attacks were published between 1804 and 1928. It is difficult to separate the empirical events from the cultural milieu in which they were reported, but some of these historical accounts are credible, resembling those of modern attacks. It is also evident that up until the early 20th century it was a commonly held perception that dingoes did occasionally prey on humans. By the 1920s, however, a popular belief had taken hold that dingoes were far too timid to attack even children and had never represented a threat to human safety. This cultural shift in the image of the dingo may be traced to the reduced frequency of human–dingo interactions in the more settled regions of eastern Australia, where a veritable war of destruction waged by pastoralists nearly eradicated the population. Intensive shooting, trapping and poisoning may also have selected for dingoes that were more wary of humans, such that the changing public attitude towards the dingo reflected the reality of rural life. This paper investigates the origin of the once popular belief in Australian society that wild dingoes do not attack humans. To address this problem, a digital repository of archived newspaper articles and other published texts written between 1788 and 1979 were searched for references to dingoes attacking non-Indigenous people. A total of 52 accounts spanning the period between 1804 and 1928 was identified. A comparison of these historical accounts with the details of modern dingo attacks suggests that at least some of the former are credible. The paper also examined commonly held attitudes towards dingoes in past Australian society based on historical print media articles and other records. Early chroniclers of Australian rural life and culture maintained that dingoes occasionally killed and ate humans out of a predatory motivation. By the early decades of the 20th century, however, an opposing view of this species had emerged: namely, that dingoes were timid animals that continued to pose a danger to livestock, but never to people. This change in the cultural image of dingoes can possibly be linked to more than a century of lethal dingo control efforts greatly reducing the frequency of human–dingo interactions in the most populous parts of the country. This intensive culling may also have expunged the wild genetic pool of dingoes that exhibited bold behaviour around people and/or created a dingo population that was largely wary of humans. [ABSTRACT FROM AUTHOR]

The principle of 'working with, not on' people with disabilities is widely espoused within inclusive research, yet historically such opportunities have not been fully realized. This paper speaks from the perspective of users of health, rehabilitation, assistive technology services, and the academics with whom they collaborate. We draw on Australia's Disability Inclusive Research Principles to reflect on the practice of inclusive research across the areas of assistive technology policy, digital information, and health access, as well as the co-design of allied health resources. We consider and provide examples of how power and knowledge play out in health and rehabilitation, the developing discourse around consumer co-design and co-production, and the challenges of enacting inclusive research. This paper is about shared power in the mechanisms of research production and our journeys towards it. Engaging in inclusive research has enabled us to assume roles beyond the binary of the 'researcher' and the 'researched'. We conclude by proposing an adaptation of the ladder of participation for inclusive research. [ABSTRACT FROM AUTHOR]

Achieving coastal and shallow-water bathymetry is essential for understanding the marine environment and for coastal management. Bathymetric data in shallow sea areas can currently be obtained using SDB (satellite-derived bathymetry) with multispectral satellites based on depth inversion models. In situ bathymetric data are crucial for validating empirical models but are currently limited in remote and unapproachable areas. In this paper, instead of using the measured water depth data, ICESat-2 (Ice, Cloud, and Land Elevation Satellite-2) ATL03 bathymetric points at different acquisition dates and multispectral imagery from Sentinel-2/GeoEye-1 were used to train and evaluate water depth inversion empirical models in two study regions: Shanhu Island in the South China Sea, and Heron Island in the Great Barrier Reef (GBR) in Australia. However, different sediment types also influenced the SDB results. Therefore, three types of sediments (sand, reef, and coral/algae) were analyzed for Heron Island, and four types of sediments (sand, reef, rubble and coral/algae) were analyzed for Shanhu Island. The results show that accuracy generally improved when sediment classification information was considered in both study areas. For Heron Island, the sand sediments showed the best performance in both models compared to the other sediments, with mean R2 and RMSE values of 0.90 and 1.52 m, respectively, representing a 5.6% improvement of the latter metric. For Shanhu Island, the rubble sediments showed the best accuracy in both models, and the average R2 and RMSE values were 0.97 and 0.65 m, respectively, indicating an RMSE improvement of 15.5%. Finally, bathymetric maps were generated in two regions based on the sediment classification results. [ABSTRACT FROM AUTHOR]

This paper explores the connection between intra-religious dialogue and Muslim identities in Australia. Drawing on empirical literature and analysis, this article investigates the increasing identification and interplay between Australian Muslims from different sects, sub-sects and faith-based groups of Islam. It argues intra-Muslim dialogue is gaining more noticeability among Australian Muslims working to build civic and inclusive identities. At the same time, the article points to the socio-political, organisational and sectarian issues challenging intra-religious unity between Muslim groups in Australia. To achieve genuine and long-lasting intra-faith relations, the article argues for a need to develop organic, theologically inclusive and contextually grounded articulations of intra-Muslim dialogue in Australia. The article concludes that diverse experiences of identity formation in Australia serve as an impetus for strengthening intra-Muslim relations based on previous success with inter-faith initiatives, as well as intergroup contact with non-Muslims. [ABSTRACT FROM AUTHOR]

Electrical infrastructure is one of the major causes of bushfire in Australia alongside arson and lightning strikes. The two main causes of electrical-infrastructure-initiated fires are asset failure and powerline vegetation interactions. In this paper, we focus on powerline–vegetation interactions that are caused by vegetation falling onto or blowing onto electrical infrastructure. Currently, there is very limited understanding of both the spatio-temporal variability of these events and their causative factors. Bridging this knowledge gap provides an opportunity for electricity utility companies to optimally allocate vegetation management resources and to understand the risk profile presented by vegetation fall-in initiated fires, thereby improving both operational planning and strategic resource allocation. To bridge this knowledge gap, we developed a statistical rare-event modelling and simulation framework based on Endeavour Energy's fire start and incident records from the last 10 years. The modelling framework consists of nested, rare-event-corrected, conditional probability models for vegetation events and consequent ignition events that provide an overall model for vegetation-initiated ignitions. Model performance was tested on an out-of-time test set to determine the predictive utility of the models. Predictive performance was reasonable with test set AUC values of 0.79 and 0.66 for the vegetation event and ignition event models, respectively. The modelling indicates that wind speed and vegetation features are strongly associated with vegetation events, and that Forest Fire Danger Index (FFDI) and soil type are strongly associated with ignition events. The framework can be used by energy utilities to optimize resource allocation and prepare future networks for climate change. [ABSTRACT FROM AUTHOR]

Several ungulate species are showing increasing population patterns within their geographical distribution ranges, leading to constant interactions with other animal species. Varying densities and activities of different ungulates may result in diverse impacts on other coexisting species groups, including large numbers of threatened species, such as reptiles. In this study, we performed an analysis of the available literature to investigate the impacts of ungulates on reptiles. We aimed to reveal the diversity of: (1) the geographical and environmental distribution of related investigations; (2) the ungulate and reptile species involved; and (3) the characteristics of interactions (direct or indirect, positive or negative) from 69 publications. Our results show that the most papers were reported from the Americas (42%) and Australia (28%). The proportions of studies were balanced for wild ungulates (53%) and livestock (47%). Wild boar (Sus scrofa) was found to be the most problematic species on reptiles whereas reptiles which suffered the harshest impacts were Squamates (i.e., lizards, and snakes). Ungulate activities (e.g., digging by wild boar) may directly harm reptiles (consuming or killing them) or indirectly affect them by modifying their habitats or destroying their hideouts. Some preferential effects were also noted (e.g., by moderate livestock grazing or when wild ungulates are prey for large reptiles). Published livestock impacts were mainly indirect and mostly negatively linked to overgrazing. We conclude that it is important to manage and monitor the densities of ungulates to minimize their negative impacts on reptile species, especially in case of wild boar and grazing livestock, but also to maintain their moderate beneficial effects (e.g., as prey basis). [ABSTRACT FROM AUTHOR]