Queensland Research Articles

Phylogeny, envenomation syndrome, and membrane permeabilising venom produced by Australia’s electric caterpillar Comana monomorpha

Zygaenoidea is a superfamily of lepidopterans containing many venomous species, including the Limacodidae (nettle caterpillars) and Megalopygidae (asp caterpillars). Venom proteomes have been recently documented for several species from each of these families, but further data are required to understand the evolution of venom in Zygaenoidea. In this study, we examined the ‘electric’ caterpillar from North-Eastern Australia, a limacodid caterpillar densely covered in venomous spines. We used DNA barcoding to identify this caterpillar as the larva of the moth Comana monomorpha (Turner, 1904). We report the clinical symptoms of C. monomorpha envenomation, which include acute pain, and erythema and oedema lasting for more than a week. Combining transcriptomics of venom spines with proteomics of venom harvested from the spine tips revealed a venom markedly different in composition from previously examined limacodid venoms that are rich in peptides. In contrast, the venom of C. monomorpha is rich in aerolysin-like proteins similar to those found in venoms of asp caterpillars (Megalopygidae). Consistent with this composition, the venom potently permeabilises sensory neurons and human neuroblastoma cells. This study highlights the diversity of venom composition in Limacodidae.

Enhancing rangeland weed detection through convolutional neural networks and transfer learning

The detection of weed species in rangeland environments is a challenging task due to various factors such as dense, variable species vegetation, ocular occlusion, and a wide variety of plant morphology. Most research in weed detection, however, focuses on croplands. This research addresses the need for accurate rangeland weed detection models by leveraging convolutional neural network (CNN) models enhanced with transfer learning applied to the DeepWeeds data set taken in situ in regional North Eastern Australia. It investigates the effectiveness of transfer learning across seven popular models, utilizing data augmentation and fine-tuning. The performance of these models was evaluated using accuracy metrics and compared against each other. The results demonstrated that transfer learning, coupled with fine tuning, could be a viable solution for generating efficient weed plant detection models with lower demands on computational resources and smaller datasets, despite the challenging conditions of rangeland environments. EfficientNetV2B1 had the highest classification accuracy of 94.2 ​%, and lowest training times. Moreover, high levels of accuracy were also achieved using InceptionV3, VGG16, and Densenet121, albeit with a training time penalty. This research provides insights into the performance of CNN models in challenging rangeland environments, demonstrates the potential of using transfer learning to enhance weed detection models, and underscores the significance of model selection in agricultural applications of CNNs.

Parenting, Child Maltreatment, and Social Disadvantage: A Population-Based Implementation and Evaluation of the Triple P System of Evidence-Based Parenting Support.

Child Maltreatment (CM) is a widespread public health problem, with adverse outcomes for children, families, and communities. Evidence-based parenting support delivered via a public health approach may be an effective means to prevent CM. The Every Family 2 population trial applied a public health approach to delivering evidence-based parenting support to prevent CM in disadvantaged communities. Using a quasi-experimental design, 64 matched low socioeconomic communities in the Australian states of Queensland and New South Wales received either the full multi-level Triple P system (TPS) of parenting support, or Care as Usual (CAU). Two population indicators of CM, the number of substantiated cases of CM, and the number of notifications of CM to protective services were compared using Welch's t-test to evaluate intervention effectiveness. After two years of intervention, medium to large effect sizes favoring TPS communities were found for substantiations (d = 0.57, p < .05) and notifications (d = 1.86, p < .001). These findings show the value of the TPS, deployed using a public health approach, in efforts to prevent CM in socially disadvantaged communities. A number of uncontrolled contextual factors are described that may have contributed to some of the differences detected between TPS and CAU communities.

Caring Enough to Counter Extinction: The Work of Volunteer Bat Carers and Educators in Tropical Queensland, Australia

Abstract In the state of Queensland, volunteers perform much of the work needed to prevent the extinction of threatened species who are native and unique to this continent. Acting from an understanding of interspecies justice, caring people rescue and rehabilitate hundreds of thousands of wild animals every year. Many of these same people conduct informal environmental education to bring to community attention the problematics of extinction by seeking the material expression of an ethics of conviviality. Using a document case study approach, this paper narrates aspects of the kindship work of a network of carers and educators of flying foxes who undertake informal environmental education as part of their care practices. Volunteering to care and educate for Australian flying mammals is a form of activism in a nation with a mammalian extinction crisis that still fails to meet its obligations under the United Nations Sustainable Development Goal 15. This paper describes how volunteer run informal environmental education in far north Queensland is driven by a strong sense of multispecies care.

Incorporating demand constraints into piecewise frontier models of public service provision

Evaluating the performance of public service providers is often complicated by the fact that they must choose input levels before demands for their services are known. We consider an even more complicated situation in which service providers have no opportunity to directly influence demands. This means that their predetermined inputs may be more than what is required to meet realised demands. In such cases, conventional measures of revenue efficiency will generally mis-classify rational and efficient managers as inefficient. We develop a more appropriate measure of revenue efficiency that accounts for exogenously-determined demands. We explain how data envelopment analysis (DEA) methods can be used to estimate our measure. The methodology is applied to hospital and health service networks in Queensland (Australia). We find that most of these networks were able to maximise the revenue they could obtain from their predetermined inputs.

The relationship between hair cortisol concentration and autism diagnosis

BackgroundAutistic children are prone to experience heightened levels of distress and physiological reactivity to a range of sensory, social, and emotional stimuli. In line with this, multiple studies have demonstrated that autistic children have higher acute cortisol stress responses to adverse or threatening stimuli and altered cortisol awakening responses. However, few studies have examined whether this sensitivity may relate to heightened levels of chronic stress and persistently elevated hypothalamic-pituitary-adrenal (HPA) axis activity. The measurement of cortisol accumulation in hair is considered a non-invasive biomarker of chronic stress and has been associated with several childhood diseases. Here, we investigated whether hair cortisol concentration in a large sample of autistic children differed from non-autistic children, and after accounting for a range of child, parental and family-level characteristics. MethodsHair cortisol concentration was measured in 307 autistic children and 282 non-autistic controls aged between 2 and 17 years recruited from four Australian states who participated in providing hair samples and demographic data to the Australian Autism Biobank. Independent samples t-test or one-way analysis of variance (ANOVA) were conducted to determine significant differences in the mean hair cortisol concentration (pg/mg) between potential covariates. Primary analysis included multivariable regression modelling of the collapsed sample to identify variables that were significantly associated with hair cortisol concentration after controlling for covariates. We also accounted for the potential interaction of multiple biological (e.g., age, sex, BMI) and psychosocial characteristics at the level of the child, the mother and the father, and the family unit. ResultsOur findings suggest that the diagnosis of autism was not a significant predictor of chronic stress, as measured by hair cortisol concentration. However, findings of the multivariable regression analysis showed that key factors such as area of residence (Queensland vs Victorian state of residence) and decrease in child's age were significantly associated with higher hair cortisol concentration whereas lower family income was significantly associated with higher hair cortisol concentration. ConclusionTo our knowledge, this is the first study to show that socioeconomic factors such as family annual income affect hair cortisol status in autistic children, indicating that the psychosocial environment may be a potential mediator for chronic stress in autistic children just as it has been demonstrated in non-autistic children.

“The reasons you believe …”: An exploratory study of text driven evidence gathering and prediction from first responder records justifying state authorised intervention for mental health episodes

Objective First responders’ mandatory reports of mental health episodes requiring emergency hospital care contain rich information about patients and their needs. In Queensland (Australia) much of the information contained in Emergency Examination Authorities (EEAs) remains unused. We propose and demonstrate a methodology to extract and translate vital information embedded in reports like EEAs and to use it to investigate the extreme propensity of incidence of serious mental health episodes.Methods The proposed method integrates clinical, demographic, spatial and free text information into a single data collection. The data is subjected to exploratory analysis for spatial pattern recognition leading to an observational epidemiology model for the association of maximum spatial recurrence of EEA episodes.Results Sentiment analysis revealed that among EEA presentations hospital and health service (HHS) region #4 had the lowest proportion of positive sentiments (18 %) compared to 33 % for HHS region #1 pointing to spatial differentiation of sentiments immanent in mandated free text which required more detailed analysis.At the postcode geographical level, we found that variation in maximum spatial recurrence of EEAs was significantly positively associated with spatial range of sentiments (0.29, p < 0.001) and the postcode-referenced sex ratio (0.45, p = 0.01). The volatility of sentiments significantly correlated with extremes of recurrence of EEA episodes. The predicted (probabilistic) incidence rate when mapped reflected this correlation.Conclusions The paper demonstrates the efficacy of integrating, machine extracted, human sentiments (as potential surrogates) with conventional exposure variables for evidence-based methods for mental health spatial epidemiology.Such insights from informatics-driven epidemiological observations may inform the strategic allocation of health system resources to address the highest levels of need and to improve the standard of care for mental patients while also enhancing their safe and humane treatment and management.

Industrial relations as power, place and time: the case of Queensland coal mining

ABSTRACT How has the coal mining industry been changing as employers and unions organise their power resources to control and remake spaces of working and living? The most obvious likely changes are those driven by climate change policies. These are, however, only the most obvious, albeit fundamental, transformations facing coal mining workforces and unions. In the massive export coalfields of the State of Queensland, which have been central to the Australian politics of climate change, a less discussed phenomenon has been unfolding, a remaking of place and power in industrial relations. Employer-driven changes, namely automation, the geography of work and bargaining processes, and workforce composition, have presented themselves as the immediate threats to local traditions of work and social practice, not climate policy. ‘Power resources approaches’, when spatialised, historicised and entwined with labour process analysis, help to explain the breadth of employer-driven change and the unevenness of union responses.

Cost-effectiveness analysis of an ambulance service-operated specialised cardiac vehicle with mobile extracorporeal cardiopulmonary resuscitation capacity for out-of-hospital cardiac arrests in Queensland, Australia.

Extracorporeal CPR (E-CPR) has been primarily limited to the in-hospital setting. A few systems around the world have implemented pre-hospital mobile E-CPR in the form of a dedicated cardiac vehicle fitted with specialised equipment and clinicians required for the performance of E-CPR on-scene. However, evidence of the outcomes and cost-effectiveness of mobile E-CPR remain to be established. We evaluated the cost-effectiveness of a hypothetical mobile E-CPR vehicle operated by Queensland Ambulance Service in the state of Queensland, Australia. We adapted our published mathematical model to estimate the cost-effectiveness of pre-hospital mobile E-CPR relative to current practice. In the model, a specialised cardiac vehicle with mobile E-CPR capability is deployed to selected OHCA patients, with eligible candidates receiving pre-hospital E-CPR in-field and rapid transport to the closest appropriate centre for in-hospital E-CPR. For comparison, non-candidates receive standard ACLS from a conventional ambulance response. Cost-effectiveness was expressed as Australian dollars ($, 2021 value) per quality-adjusted life year (QALY) gained. Pre-hospital mobile E-CPR improves outcomes compared to current practice at a cost of $27 323 per QALY gained. The cost-effectiveness of pre-hospital mobile E-CPR is sensitive to the assumption around the number of patients who are the targets of the vehicle, with higher patient volume resulting in improved cost-effectiveness. Pre-hospital E-CPR may be cost-effective. Successful implementation of a pre-hospital E-CPR programme requires substantial planning, training, logistics and operational adjustments.

Kinematics of the Clarke River Shear Zone (northeastern Australia) and implications for the tectonic evolution of the Tasmanides

The Clarke River Shear Zone marks the boundary between the Thomson and Mossman orogens in the northeastern Tasmanides. To better understand the kinematic history of this east-northeast-trending shear zone, and its role during the tectonic history of eastern Gondwana, we investigated rock deformation along a segment of the Clarke River Shear Zone. Based on field observations, interpretation of aeromagnetic data and microstructural analysis, we show that the Clarke River Shear Zone experienced at least three phases of reactivation. Gently plunging stretching lineation and kinematic indicators, such as steeply plunging asymmetric folds and asymmetric porphyroclasts, correspond to an early phase of sinistral strike-slip ductile shearing. Subsequent general dextral shear deformation is suggested based on the presence of S-tectonites, symmetric porphyroclasts and kinematic indicators with dominant dextral and subordinate sinistral shear senses. This phase, which occurred under amphibolite-facies metamorphic conditions, was contemporaneous with the emplacement of the Craigie Tonalite, for which we obtained a new zircon U–Pb crystallisation age of 410.3 ± 1 Ma. A later reactivation phase along the Clarke River Shear Zone, under brittle conditions, is indicated by the presence of cataclasite zones and chlorite–epidote alteration. Based on our findings, and regional information on the tectono-magmatic evolution of northeastern Queensland, we suggest that the Clarke River Shear Zone was possibly a sinistral transform fault during the Silurian. During the Devonian, it is possible that deformation along the Clarke River Shear Zone was related to the transition between the non-retreating subduction zone in the north, and the highly mobile (retreating) plate boundary farther south. However, the dextral kinematic component associated with this deformation is not fully explained. Brittle deformation, likely associated with dextral transpression during the Carboniferous, marked the last stage of activity along the Clarke River Shear Zone.

How Much Physiotherapy, Chiropractic, and Osteopathy Care Do Compensated Australian Workers with Low Back Pain Receive? A Retrospective Cohort Study.

To identify the prevalence and frequency of physiotherapy, chiropractic, and/or osteopathy care in Australians with workers' compensation claims for low back pain (LBP). We included workers with accepted workers' compensation claims longer than 2weeks from the Australian states of Victoria, Queensland, South Australia, and Western Australia. Workers were grouped by whether they attended physiotherapy, chiropractic, and/or osteopathy in the first 2years of their claim. Descriptive statistics and logistic regression were used to describe differences between groups. Descriptive statistics and negative binomial regression were used to describe differences in the number of attendances in each group. Most workers had at least one physical therapy attendance during the period of their claim (n = 23,619, 82.0%). Worker state, socioeconomic status, and remoteness were the largest contributing factors to likelihood of physical therapy attendance. Most workers only attended physiotherapy (n = 21,035, 89.1%, median of 13 times). Far fewer only attended chiropractic (n = 528, 2.2%, median of 8 times) or only osteopathy (n = 296, 1.3%, median of 10 times), while 1,750 (7.5%) attended for care with more than one type of physical therapy (median of 31 times). Most Australian workers with workers' compensation time loss claims for LBP attend physiotherapy at least once during their claims. State of claim is the strongest predictor of which physical therapy profession they attend, possibly due to regional availability. Workers who see a physiotherapist have significantly more attendances. Future research should explore the relationship between these patterns of care and claimant outcomes, including work disability duration.

Temperature extremes nip invasive macrophyte Cabomba caroliniana A. Gray in the bud: potential geographic distributions and risk assessment based on future climate change and anthropogenic influences.

Cabomba caroliniana A. Gray, an ornamental submerged plant indigenous to tropical America, has been introduced to numerous countries in Europe, Asia, and Oceania, impacting native aquatic ecosystems. Given this species is a popular aquarium plant and widely traded, there is a high risk of introduction and invasion into other environments. In the current study the potential global geographic distribution of C. caroliniana was predicted under the effects of climate change and human influence in an optimised MaxEnt model. The model used rigorously screened occurrence records of C. caroliniana from hydro informatic datasets and 20 associated influencing factors. The findings indicate that temperature and human-mediated activities significantly influenced the distribution of C. caroliniana. At present, C. caroliniana covers an area of approximately 1531×104 km2 of appropriate habitat, especially in the south-eastern parts of South, central and North America, Southeast Asia, eastern Australia, and most of Europe. The suitable regions are anticipated to expand under future climate scenarios; however, the dynamics of the changes vary between different extents of climate change. For example, C. caroliniana is expected to expand to higher latitudes, following global temperature increases under SSP1-2.6 and SSP2-4.5 scenarios, however, intolerance to temperature extremes may mediate invasion at higher latitudes under future extreme climate scenarios, e.g., SSP5-8.5. Owing to the severe impacts its invasion causes, early warning and stringent border quarantine processes are required to guard against the introduction of C. caroliniana especially in the invasion hotspots such as, Peru, Italy, and South Korea.

The emotional terrain of foster and kinship carers’ relationships with parents of children in care: Carers’ perspectives

Children in foster and kinship care have a right to relationships with their parents. The United Nations Convention on the Rights of the Child (UNCRC) asserts children’s right to contact with their parents and families during periods of separation, except where this is proven not to be in the child’s best interests. Foster and kinship carers can play a pivotal role in children’s opportunities for, and experiences of, connection to parents and other family. Yet, the relationship between carers and parents is often characterised by ambivalence and tensions. Emerging research suggests that training and support to carers can help them to navigate their own and children’s relationships with their families. However, such support is not routinely available, and the evidence-base for supporting carers to manage complex relationships with parents is not well-developed. In this paper, we report on a study with 113 foster and kinship carers in Queensland (Australia). We explore carers’ perceptions of the emotional aspects of their relationships with parents. A novel feature of our study is our exploration of carers’ perceptions of affiliative and threat-based emotions in their relationships with birth parents. We report that carers experience a wide spectrum of emotions in their relationships with parents, some of which strengthen these relationships while others create distance. We find also that carers receive little, if any, formal support in building relationships with parents and for supporting children’s opportunities for, and experiences of family contact. Aboriginal and Torres Strait Islander carers report being unsupported in meeting their cultural obligations in developing relationships with children’s parents and families. We discuss the implications for formal support to improve carers capacities to build and maintain their own, and children’s, relationships with parents.

Developing Vis–NIR libraries to predict cation exchange capacity (CEC) and pH in Australian sugarcane soil

In sugarcane growing areas of Queensland Australia, management of soil condition requires information about soil chemical properties (i.e., cation exchange capacity [CEC], and pH), because they are used to make fertiliser recommendations. While laboratory analysis is cost prohibitive the development of visible near–infrared (Vis–NIR) spectroscopy libraries might be useful. The aims of this study was to compare: i) linear (i.e., Partial least squares regression [PLSR]) and machine learning (i.e., Cubist, Random Forest [RF] and Support vector machine [SVM]) algorithms in terms of their calibration strength (i.e., coefficient of determination (R2); ii) depth-specific (i.e., topsoil [0 – 0.3 m], subsurface [0.3 – 0.6 m], subsoil [0.6 – 0.9 m] and deep subsoil [0.9 – 1.2 m]) and multi-depth libraries; iii) prediction R2, agreement (Lin’s concordance correlation coefficient [LCCC]) and accuracy (ratio of performance to interquartile [RPIQ]); and iv) minimum number of calibration sample locations (i.e., n = 400, 350, …, 50). For depth-specific calibration for CEC, strong calibration R2 was achieved for the subsurface (i.e., RF [0.95], Cubist [0.93], PLSR [0.88] and SVM [0.81]), and for pH, the largest R2 was for deep subsoil (i.e., RF [0.91], followed by PLSR [0.80], Cubist [0.79] and SVM [0.56]), with subsurface, and deep subsoil similar, with topsoil R2 smaller. In terms of model prediction of depth-specific, Cubist was superior to PLSR, RF and SVM for CEC, and PLSR was the best for pH. For example, agreement for topsoil CEC was substantial for Cubist (0.80) and PLSR (0.80), but moderate for RF (0.69) and poor for SVM (0.59). For subsurface (0.9), subsoil (0.91) and deep subsoil (0.92), the agreements were perfect for CEC using Cubist. In terms of multi-depth calibration for CEC it was strong for RF (R2 = 0.94), Cubist (0.92), PLSR (0.81) and SVM (0.72), but for prediction agreement, Cubist (LCCC = 0.92) was perfect, with PLSR (0.85), RF (0.84) and SVM (0.83) substantial. This was also the case for pH (0.84) substantial. However, there are efficiencies in developing a multi-depth calibration. Moreover, the minimum number of calibration sample sites required was 300 (i.e., 1,200 samples) (1.78 sites/ha). The results have implications for using a Vis–NIR library to replace traditional soil laboratory analysis and for fertiliser recommendations for sugarcane soil.

Downscaled numerical weather predictions can improve forecasts of sugarcane irrigation indices

Efficient irrigation reduces energy and water costs, increases profit margins and delivers better environmental outcomes. Whilst many growers rely on weather forecasts to make decisions, few studies have sought to incorporate weather forecast uncertainty into the optimisation of irrigation management or to evaluate weather forecasts through the lens of irrigation indices. Therefore, in this study, we seek to generate and evaluate ensemble forecasts of irrigation indices produced by coupling numerical weather prediction (NWP) forecasts with a biophysical process model (APSIM). We investigate a case study application for sugarcane in northeastern Australia. As a first step, three and a half years of forecasts from the Australian Bureau of Meteorology’s ACCESS-G3 model are statistically post-processed to generate 7-day forecasts that are downscaled and calibrated to local climate zones. In addition, the forecast post-processor converts the deterministic forecasts into an ensemble, thus quantifying forecast uncertainty. The generated forecasts are then used as forcing for the APSIM crop model to produce ensemble forecasts of soil water deficit (SWD), crop water use (CWU) and crop stress (Stress) for a simulated sugarcane crop. Through cross-validation, the post-processed weather forecasts demonstrate improved forecast accuracy compared to naive climatology and raw NWP forecasts for daily rainfall, maximum and minimum temperature and solar radiation; with the added benefit of providing a reliable uncertainty estimate. Improvement to an even greater degree is observed for the derived irrigation indices, particularly CWU and Stress, for which the forecasts are also reliable. The developed irrigation indices based on NWP can be used directly for decision making or, alternatively, may be used further in machine learning for optimisation of irrigation schedules in conjunction with other remotely sensed variables.

Investigating the impact of critical thinking instruction on writing performance: A multilevel modelling analysis of relative gain data in the Australian national assessment program

Critical thinking is an international educational and economic priority, as are writing and effective communication skills. Little is known, however, about how these skills interact or whether instruction in one skillset has transferable benefits to the other. Given declining performance in writing skills in the Australian context, evidence that critical thinking instruction improves students’ writing performance should be of interest to policy makers and school leaders. In this quasi-experimental retrospective cohort study, we utilised multilevel modelling to examine the effects of direct online critical thinking instruction on writing performance by Queensland state school students as measured by results from the Australian standardised testing scheme (NAPLAN) assessing writing structure, grammar, and spelling. Receiving critical thinking instruction correlated with significantly higher relative gains in academic performance across literacy domains and year levels compared to a comparable numeracy instruction control. We argue that these findings indicate a transfer of cognitive skills developed through critical thinking instruction to literacy domains and discuss the potential mechanisms underlying these effects. We summarily hypothesise that improving students’ ability to identify, analyse, construct, and evaluate arguments empowers them to navigate the cognitive and metacognitive demands of academic writing with greater ease, leading to improved outcomes in standardised test settings and on writing tasks more generally.

High prevalence of diabetes among young First Nations Peoples with metabolic dysfunction-associated steatotic liver disease: a population-based study in Australia

BackgroundLiver disease is an important contributor to the mortality gap between First Nations Peoples and non-Indigenous Australian adults. Despite a high burden of metabolic comorbidities among First Nations Peoples, data about the epidemiology of metabolic dysfunction-associated steatotic liver disease (MASLD) in this population is scarce.MethodsA retrospective analysis of all adults hospitalized with MASLD or metabolic dysfunction-associated steatohepatitis (MASH) with/without cirrhosis during 2007–2019 in the state of Queensland was performed. Patients were followed from the first admission with MASLD/MASH (identified based on validated algorithms) to decompensated cirrhosis and overall mortality. We explored differences according to Indigenous status using Multivariable Cox regression.Findings439 First Nations Peoples and 7,547 non-Indigenous Australians were followed for a median of 4.6 years (interquartile range 2.7–7.2). Overall, women were overrepresented, but more so in the First Nations cohort (72.7% vs. 57.0%, p < 0.001). First Nations patients were younger, a higher proportion lived in remote and socioeconomic disadvantaged areas, and had higher comorbidity compared to non-Indigenous Australians (all p < 0.001). Diabetes, the most common comorbidity affecting both groups, was overrepresented in First Nations Peoples versus non-Indigenous Australians (43.5% vs. 30.8%, p < 0.001, respectively). Nineteen (4.3%) First Nations Peoples and 332 (4.4%) of non-Indigenous patients progressed to cirrhosis decompensation (9.0% [95%CI 4.5–17.7] vs. 7.7% [95%CI 6.6–8.9; p = 0.956] respectively within 10 years). In multivariable analysis, there was no association between Indigenous status and progression to decompensated cirrhosis (p = 0.759) and survival (p = 0.437).ConclusionsThis study provides the first population-based epidemiological data on MASLD in First Nations Australians. The high prevalence of diabetes (that is associated with advanced fibrosis and liver disease mortality) among young First Nations Peoples with MASLD raises concern about future risk of progressive liver disease in this patient population. These data highlight the importance of early identification of MASLD, and providing culturally appropriate intervention to reduce disease progression in parallel with the management of cardiometabolic comorbidities.

Integrating Artificial Intelligence and UAV-Acquired Multispectral Imagery for the Mapping of Invasive Plant Species in Complex Natural Environments

The proliferation of invasive plant species poses a significant ecological threat, necessitating effective mapping strategies for control and conservation efforts. Existing studies employing unmanned aerial vehicles (UAVs) and multispectral (MS) sensors in complex natural environments have predominantly relied on classical machine learning (ML) models for mapping plant species in natural environments. However, a critical gap exists in the literature regarding the use of deep learning (DL) techniques that integrate MS data and vegetation indices (VIs) with different feature extraction techniques to map invasive species in complex natural environments. This research addresses this gap by focusing on mapping the distribution of the Broad-leaved pepper (BLP) along the coastal strip in the Sunshine Coast region of Southern Queensland in Australia. The methodology employs a dual approach, utilising classical ML models including Random Forest (RF), eXtreme Gradient Boosting (XGBoost), and Support Vector Machine (SVM) in conjunction with the U-Net DL model. This comparative analysis allows for an in-depth evaluation of the performance and effectiveness of both classical ML and advanced DL techniques in mapping the distribution of BLP along the coastal strip. Results indicate that the DL U-Net model outperforms classical ML models, achieving a precision of 83%, recall of 81%, and F1–score of 82% for BLP classification during training and validation. The DL U-Net model attains a precision of 86%, recall of 76%, and F1–score of 81% for BLP classification, along with an Intersection over Union (IoU) of 68% on the separate test dataset not used for training. These findings contribute valuable insights to environmental conservation efforts, emphasising the significance of integrating MS data with DL techniques for the accurate mapping of invasive plant species.

Social Housing Contracts: Does Election Result Matter?

This study examines whether election results affect the annual number of social housing contracts in Australia, focusing on the doctrines of public entrepreneurialism and public interventionism associated with political parties. Using panel data analysis of voting rates at electorate level in Queensland State, the study finds that an increase of one standard deviation in the Australian Labor Party’s (ALP) voting rate, compared to the Liberal-National Coalition, corresponds to an increase of 1.07 contracts from the mean value of 21.47. This equates to approximately a 5% increase in the number of social housing contracts managed by Queensland State. The analysis further reveals that the ALP’s voting rate has a disproportionately positive impact on the supply of social housing for indigenous communities. These findings underscore in influencing the provision of social housing and offer insightful implications for policymakers and researchers, suggesting that electoral preferences can serve as a barometer for public demand for social welfare initiatives.

Effectiveness of a universal, school-based, online programme for the prevention of anxiety, depression, and substance misuse among adolescents in Australia: 72-month outcomes from a cluster-randomised controlled trial

The CSC study found that the universal delivery of a school-based, online programme for the prevention of mental health and substance use disorders among adolescents resulted in improvements in mental health and substance use outcomes at 30-month follow-up. We aimed to compare the long-term effects of four interventions-Climate Schools Combined (CSC) mental health and substance use, Climate Schools Substance Use (CSSU) alone, Climate Schools Mental Health (CSMH) alone, and standard health education-on mental health and substance use outcomes among adolescents at 72-month follow-up into early adulthood. This long-term study followed up adolescents from a multicentre, cluster-randomised trial conducted across three states in Australia (New South Wales, Queensland, and Western Australia) enrolled between Sept 1, 2013, and Feb 28, 2014, for up to 72 months after baseline assessment. Adolescents (aged 18-20 years) from the original CSC study who accepted contact at 30-month follow-up and provided informed consent at 60-month follow-up were eligible. The interventions were delivered in school classrooms through an online delivery format and used a mixture of peer cartoon storyboards and classroom activities that were focused on alcohol, cannabis, anxiety, and depression. Participants took part in two web-based assessments at 60-month and 72-month follow-up. Primary outcomes were alcohol use, cannabis use, anxiety, and depression, measured by self-reported surveys and analysed by intention to treat (ie, in all students who were eligible at baseline). This trial is registered with the Australian New Zealand Clinical Trials Registry (ACTRN12613000723785), including the extended follow-up study. Of 6386 students enrolled from 71 schools, 1556 (24·4%) were randomly assigned to education as usual, 1739 (27·2%) to CSSU, 1594 (25·0%) to CSMH, and 1497 (23·4%) to CSC. 311 (22·2%) of 1401 participants in the control group, 394 (26·4%) of 1495 in the CSSU group, 477 (37·%) of 1289 in the CSMH group, and 400 (32·5%) of 1232 in the CSC group completed follow-up at 72 months. Adolescents in the CSC group reported slower year-by-year increases in weekly alcohol use (odds ratio 0·78 [95% CI 0·66-0·92]; p=0·0028) and heavy episodic drinking (0·69 [0·58-0·81]; p<0·0001) than did the control group. However, significant baseline differences between groups for drinking outcomes, and no difference in the predicted probability of weekly or heavy episodic drinking between groups were observed at 72 months. Sensitivity analyses increased uncertainty around estimates. No significant long-term differences were observed in relation to alcohol use disorder, cannabis use, cannabis use disorder, anxiety, or depression. No adverse events were reported during the trial. We found some evidence that a universal online programme for the prevention of anxiety, depression, and substance use delivered in early adolescence is effective in reducing the use and harmful use of alcohol into early adulthood. However, confidence in these findings is reduced due to baseline differences, and we did not see a difference in the predicted probability of drinking between groups at 72-month follow-up. These findings suggest that a universal prevention programme in adolescence is not sufficient to have lasting effects on mental health and substance use disorders in the long term. In addition to baseline differences, substantial attrition warrants caution in interpretation and the latter factor highlights the need for future long-term follow-up studies to invest in strategies to increase engagement. Australian National Health and Medical Research Council.