Charles Darwin University

Although the impact of postharvest melatonin (MLT) application in extending the storage life of horticultural produce has been widely studied, its effect in jackfruit remains unknown. This investigation evaluates the influence of MLT dip application (0, 0.05, 0.1, and 0.2 mM) on browning, softening and oxidative stress in cold-stored jackfruit bulbs over a period of 20d. All MLT treatments reduced browning index and oxidative stress, while activities of browning-related enzymes were comparatively lower in the 0.1 mM MLT treatment. Treatment with 0.2 mM MLT maintained elevated levels of antioxidants as compared to control. Higher bulb firmness, total pectin and cellulose content with considerably lower activities of cell wall degrading enzymes were observed in all MLT treatments. In conclusion, MLT (0.1 and 0.2 mM) is an effective treatment for mitigating postharvest browning and oxidative stress in addition to delaying fruit softening and maintaining the antioxidant potential of cold-stored jackfruit bulbs.

This study investigated whether trophy taxidermy specimens of Australia’s largest freshwater fish, Murray cod (Maccullochella peelii), can provide accurate records of historical body size. Taxidermy mounts came mostly from informal collections in hotels from across the Murray–Darling Basin, south-eastern Australia, comprising 20% whole-body and 80% head forms. We compared the morphology of mounts to live Murray cod, collected from the mid–Murray River in 2018, and identified the head morphometrics that most accurately described length and weight of whole mounts and live fish. Eight morphological characters were analysed for 60 whole mounts, 172 head mounts and 51 live fish. We found that inter-orbital distance, inter-nare width and upper jaw length were relatively robust to taxidermy processes and were reliable features for predicting fish total length and total weight. Shrinkage in head morphometrics due to taxidermy was evident, however, and we recommend that this be considered when reconstructing length and weight measures. We discuss how estimated body length and weight from head morphometrics of trophy fish, coupled with analysis of the accompanying remaining tissue and hard parts, opens up opportunities to explore patterns in genetics, life history, movement and trophic ecology of historical fish populations and of past environments.

Students in Timor-Leste face low educational outcomes due to sociopolitical factors rooted in the nation’s colonial history. This study evaluates the academic impact of a low-resource afterschool supplementary tutoring program designed to address learning gaps and improve school outcomes across rural and urban settings. Using instructional design principles, the program employed worksheet-based individualized learning content in a familiar language, supported by personalized feedback. Pre- and post-test scores in mathematics and English were compared over 7 months between an intervention group and a comparison group, with results analyzed using a Welch t test. Findings revealed statistically significant improvements in both subjects, with greater gains in mathematics, suggesting an opportunity to explore alternative methods for English instruction, such as incorporating social interactions to support early learners. The study highlights the importance of community support, tutors’ capabilities, and their residence within local neighborhoods in sustaining the program. These results demonstrate the potential of well-structured afterschool programs to enhance educational outcomes in low-resource contexts, offering a scalable model for similar initiatives in emerging nations.

Background In moderate-to-high malaria transmission regions, the World Health Organization recommends intermittent preventive treatment in pregnancy (IPTp) with sulfadoxine-pyrimethamine (SP) alongside insecticide-treated bed nets to reduce the adverse consequences of pregnancy-associated malaria. Due to high-grade Plasmodium falciparum resistance to SP, novel treatment regimens need to be evaluated for IPTp, but these increase pill burden and treatment days. The present qualitative study assessed the acceptability of IPTp-SP plus dihydroartemisinin-piperaquine (DP) in Papua New Guinea, where IPTp-SP was implemented in 2009. Methods Individual in-depth interviews (IDIs) and focus group discussions were conducted at health facilities where a clinical trial evaluated IPTp-SP plus DP (three-day regimen) versus IPTp-SP plus DP-placebo. IDIs were conducted with: (1) trial participants at different stages of engagement with ANC and IPTp, e.g. first antenatal clinic visit, subsequent antenatal clinic visits and postpartum; (2) local health workers (nurses, community health workers, midwives, health extension officers, doctors); and (3) representatives of district, provincial and national health authorities involved in programming ANC and IPTp. Focus group discussions comprised pregnant women only, including those engaged in the clinical trial and those receiving routine ANC outside of the trial. All interviews were audio recorded and transcribed. Transcripts were analysed using inductive and deductive thematic analysis applying a framework assessing: affective attitude, burden, ethicality, intervention coherence, opportunity costs, perceived effectiveness, and self-efficacy. Results Women expressed positive feelings and attitudes towards SP plus DP/DP-placebo; reported limited side effects; and found the size, number, colour, and taste of study medicines acceptable. Health workers and policymakers were concerned that, compared to SP alone, additional tablets, frequency (three-day regimen), and tablet size might be barriers to acceptability for users outside a non-trial setting. There was a high perceived effectiveness of SP plus DP; most women reported that they did not get malaria or felt sick during pregnancy. Broader healthcare benefits received through trial participation and the involvement of health workers, relatives and community members in the clinical trial enabled antenatal clinic attendance and perceived acceptability of this IPTp regimen. Conclusions In the trial context, IPTp-SP plus DP was acceptable to both users and providers. Healthcare providers were concerned about the realities of acceptability and adherence to SP plus DP outside a clinical trial setting.

Non-technical summary Transdisciplinary sustainability scientists work with many different actors in pursuit of change. In so doing they make choices about why and how to engage with different perspectives in their research. Reflexivity – active individual and collective critical reflection – is considered an important capacity for researchers to address the resulting ethical and practical challenges. We developed a framework for reflexivity as a transformative capacity in sustainability science through a critical systems approach, which helps make any decisions that influence which perspectives are included or excluded in research explicit. We suggest that transdisciplinary sustainability research can become more transformative by nurturing reflexivity. Technical summary Transdisciplinary sustainability science is increasingly applied to study transformative change. Yet, transdisciplinary research involves diverse actors who hold contrasting and sometimes conflicting perspectives and worldviews. Reflexivity is cited as a crucial capacity for navigating the resulting challenges, yet notions of reflexivity are often focused on individual researcher reflections that lack explicit links to the collective transdisciplinary research process and predominant modes of inquiry in the field. This gap presents the risk that reflexivity remains on the periphery of sustainability science and becomes ‘unreflexive’, as crucial dimensions are left unacknowledged. Our objective was to establish a framework for reflexivity as a transformative capacity in sustainability science through a critical systems approach. We developed and refined the framework through a rapid scoping review of literature on transdisciplinarity, transformation, and reflexivity, and reflection on a scenario study in the Red River Basin (US, Canada). The framework characterizes reflexivity as the capacity to nurture a dynamic, embedded, and collective process of self-scrutiny and mutual learning in service of transformative change, which manifests through interacting boundary processes – boundary delineation, interaction, and transformation. The case study reflection suggests how embedding this framework in research can expose boundary processes that block transformation and nurture more reflexive and transformative research. Social media summary Transdisciplinary sustainability research may become more transformative by nurturing reflexivity as a dynamic, embedded, and collective learning process.

Rheumatic heart disease remains prevalent in some regions of Australia and New Zealand. Echocardiography is the gold standard for detection and diagnosis using the 2023 World Heart Federation guidelines. The guidelines describe specific features of mitral and aortic valve morphology and define pathological regurgitation associated with RHD. The aim of this education piece was to assist cardiac sonographers and reporting specialists in the accurate detection, diagnosis, and classification of RHD findings. We present the echocardiographic features of RHD as defined by the 2023 WHF guidelines, including a poster summarising the individual criteria for diagnosis.

We developed a realist program theory describing factors that affect healthcare professionals’ delivery of guideline-based pain care in rural Australia as part of a realist-informed needs assessment. To our knowledge, this project is the first to apply a realist research approach to conducting a needs assessment. We conducted and analysed realist informed teacher-learner cycle interviews with rural healthcare professionals to inform our program theory. In these interviews, we presented participants with a summary of guideline recommendations for the assessment and management of chronic pain. We asked participants which recommendations they found easy and challenging to implement in their local setting, and discussed why, how, and in what circumstances this was the case. We detail how we analysed interview transcripts retroductively in NVivo and how the authorship team abstracted from the clinical scenarios provided by interviewees to generate theories at a ‘middle level’ of abstraction. Our discussion details lessons learned from the utilised methods with recommendations for how we would adapt these methods in the future.

The clinical diagnosis of dermatophytosis and identification of dermatophytes face challenges due to reliance on culture-based methods. Rapid, cost-effective detection techniques for volatile organic compounds (VOCs) have been developed for other microorganisms, but their application to dermatophytes is limited. This study explores using VOCs as diagnostic markers for dermatophytes. We compared VOC profiles across different dermatophyte taxa using solid-phase microextraction (SPME) and advanced analytical methods: gas chromatography-mass spectrometry (GC–MS) and comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry (GC×GC-TOFMS). We analyzed 47 dermatophyte strains from 15 taxa grown on sheep wool, including clinically significant species. Additionally, we examined phylogenetic relationships among the strains to correlate genetic relatedness with metabolite production. Our results showed that GC×GC-TOFMS offered superior resolution but similar differentiation of VOC profiles compared to GC–MS. VOC spectra allowed reliable distinction of taxonomic units at the species level and below, however, these distinctions showed only a slight correlation with phylogenetic data. We identified pan-dermatophyte and species- or strain-specific VOC profiles, indicating their potential for rapid, non-invasive detection of dermatophyte infections, including epidemic strains. These patterns could enable future taxa-specific identification. Our study highlights the potential of VOCs as tools for dermatophyte taxonomy and diagnosis.

Tobacco-free generation (TFG) policies, also conceptualised as smoke-free or nicotine-free generation in some geographies, envision the elimination of tobacco use initiation by preventing tobacco sales to generations born after a specified birth date. This cohort-based policy approach eventually aims to phase out tobacco use. This paper defines TFG, reviews its international developments and explores the feasibility of the TFG policy approach in India, considering the country’s federal governance structure with health as a state responsibility, within a national policy framework. Our review suggests that the concept of TFG aligns well with existing tobacco control measures in India, such as the Cigarette and Other Tobacco Products Act (COTPA), the National Tobacco Control Programme, Tobacco-free Educational Institutes and innovations such as tobacco vendor licensing and various tobacco-free campaigns. Amending section 6(a) of COTPA to replace the current prohibition of sale to and by those below 18 years of age with a specific section on TFG would be an effective approach to ensure policy coherence. Supporting grassroots movements countrywide at the state and/or substate level may activate the process within the Ministry of Health and Family Welfare, Government of India to table this proposal as an amendment in Section 6 of COTPA for the Parliament to adopt.

The identification and early treatment of retinal disease can help to prevent loss of vision. Early diagnosis allows a greater range of treatment options and results in better outcomes. Optical coherence tomography (OCT) is a technology used by ophthalmologists to detect and diagnose certain eye conditions. In this paper, human retinal OCT images are classified into four classes using deep learning. Several image preprocessing techniques are employed to enhance the image quality. An augmentation technique, called generative adversarial network (GAN), is utilized in the Drusen and DME classes to address data imbalance issues, resulting in a total of 130,649 images. A lightweight optimized compact convolutional transformers (OCCT) model is developed by conducting an ablation study on the initial CCT model for categorizing retinal conditions. The proposed OCCT model is compared with two transformer-based models: vision Transformer (ViT) and Swin Transformer. The models are trained and evaluated with 32 × 32 sized images of the GAN-generated enhanced dataset. Additionally, eight transfer learning models are presented with the same input images to compare their performance with the OCCT model. The proposed model’s stability is assessed by decreasing the number of training images and evaluating the performance. The OCCT model’s accuracy is 97.09%, and it outperforms the two transformer models. The result further indicates that the OCCT model sustains its performance, even if the number of images is reduced.

Natural hybridisation among rare or endangered species and stable congenerics is increasingly topical for the conservation of species‐level diversity under anthropogenic impacts. Evidence for beneficial genes being introgressed into or selected for in hybrids raises concurrent questions about its evolutionary significance. In Darwin's tree finches on the island of Floreana (Galapagos Islands, Ecuador), the Critically Endangered medium tree finch (Camarhynchus pauper) undergoes introgression with the stable small tree finch (Camarhynchus parvulus), and hybrids regularly backcross with C. parvulus. Earlier studies in 2005–2013 documented an increase in the frequency of Camarhynchus hybridisation on Floreana using field‐based and microsatellite data. With single nucleotide polymorphism (SNP) data from the same Floreana tree finches sampled in 2005 and 2013 (n = 95), we examine genome‐wide divergence across parental and hybrid birds and evidence for selection in hybrids. We found that just 18% of previously assigned hybrid birds based on microsatellites could be assigned to hybrids using SNPs. Over half of the previously assigned hybrids (63%) were reassigned to C. parvulus, though parental species showed concordance with prior assignments. Of 4869 private alleles found in hybrid birds, 348 were at a high frequency (≥ 0.30) that exceeded their parental species of origin 89%–96% of the time. For private alleles detected in both years (N = 536) between 11%–76% of alleles underwent a frequency increase and 13%–61% a frequency decrease between 2005 and 2013, which was sensitive to sampling effort. We identified 28 private alleles that were candidates under selection via local PCA and outlier tests. Alleles were annotated to genes associated with inflammation, immunity, brain function and development. We provide evidence that introgression among a critically endangered and stable species of Darwin's tree finch across years may aid in the retention of adaptive alleles and genetic diversity in birds threatened with extinction.

This study presents a novel privacy-preserving self-supervised (SSL) framework for COVID-19 classification from lung CT scans, utilizing federated learning (FL) enhanced with Paillier homomorphic encryption (PHE) to prevent third-party attacks during training. The FL-SSL based framework employs two publicly available lung CT scan datasets which are considered as labeled and an unlabeled dataset. The unlabeled dataset is split into three subsets which are assumed to be collected from three hospitals. Training is done using the Bootstrap Your Own Latent (BYOL) contrastive learning SSL framework with a VGG19 encoder followed by attention CNN blocks (VGG19 + attention CNN). The input datasets are processed by selecting the largest lung portion of each lung CT scan using an automated selection approach and a 64 × 64 input size is utilized to reduce computational complexity. Healthcare privacy issues are addressed by collaborative training across decentralized datasets and secure aggregation with PHE, underscoring the effectiveness of this approach. Three subsets of the dataset are used to train the local BYOL model, which together optimizes the central encoder. The labeled dataset is employed to train the central encoder (updated VGG19 + attention CNN), resulting in an accuracy of 97.19%, a precision of 97.43%, and a recall of 98.18%. The reliability of the framework’s performance is demonstrated through statistical analysis and five-fold cross-validation. The efficacy of the proposed framework is further showcased by showing its performance on three distinct modality datasets: skin cancer, breast cancer, and chest X-rays. In conclusion, this study offers a promising solution for accurate diagnosis of chest X-rays, preserving privacy and overcoming the challenges of dataset scarcity and computational complexity.

Great progress in cytotaxonomic research during the last decades indicated an importance of relationships between morphological features, geographical distribution of plants, and chromosome counts. This study is aimed to fill the gaps in our knowledge on Bolboschoenus chromosome numbers related to morphological differentiation of plants and their distribution worldwide. We counted gametophytic chromosome numbers in meiotic phase of plants, collected from localities worldwide during the period 1980-2013, and cultivated in an experimental garden in Průhonice. The chromosome numbers of seven species (Bolboschoenus affinis, B. caldwellii, B. grandispicus, B. medianus, B. novae-angliae, B. robustus and B. schmidii) were counted for the first time. All the studied Bolboschoenus taxa were divided into groups according to chromosome numbers, which were found to correspond to morphotypes formerly described. We have improved the taxonomic classification of some species. The relationship between chromosome counts and morphotypes appeared to be identical within some continents, and may indicate parallel evolution within the genus.

Anthropogenic perturbations have substantially altered riverine carbon cycling worldwide, exerting influences on dissolved carbon dioxide (CO2) and methane (CH4) dynamics at multiple levels. However, the magnitude and role of anthropogenic activities in modulating carbon emissions across entire river networks, as well as the influence of climatic controls, remain largely unresolved. Here, we explore the controlling factors of riverine CO2 and CH4 dynamics across 62 subtropical, monsoon‐influenced streams and rivers through basin‐wide seasonal measurements. We found that land use and aquatic metabolism played significant roles in regulating the spatial and temporal patterns of both gases. Increased nutrient levels and organic matter contributed to higher partial pressure of CO2 (pCO2) and CH4 (pCH4). Dissolved oxygen, stable carbon isotope of dissolved inorganic carbon, the proportion of impervious surface, catchment slope, and river width were the major predictors for pCO2. For pCH4, the major predictors were Chlorophyll a and water temperature, which influence organic matter availability and methanogenesis. Seasonal variations in pCO2 and pCH4 were strongly modulated by hydroclimatic conditions, with temperature markedly regulating river ecosystem metabolism. These findings highlight the likelihood of significant changes in riverine carbon emissions as climate changes and land use patterns evolve, thereby profoundly affecting the global carbon cycle.

Global environmental change’s impact on local realities, which is getting more worrying daily, sparks awareness of the importance of risk reduction, adaptation, and preparedness in the communities, especially children and adolescents vulnerable to disasters and climate change. West Timor of East Nusa Tenggara Province is one of the areas that is at risk of climate change and disaster in Indonesia. This study aim to evaluate the knowledge, awareness, and preparedness for disasters and climate change in children living in climate-risk and disaster years. The data were then analyzed using thematic analysis techniques. Based on the study’s results, there are two main themes, namely (1) understanding related to disaster risk and climate change and (2) scientific attitudes possessed by students. Identifying the level of understanding and extent of critical thinking ability of children and adolescents that can inform policymakers and advocates to empower children to cope with future disaster risks.

Accurate prediction of multi-step ahead inflow in advance plays a crucial role in enhancing the management of dam reservoirs. To address this, there is a growing emphasis on utilizing artificial intelligence (AI) and novel techniques to achieve high-accuracy predictions. Rather than relying on time series models as Autoregressive Integrated Moving Average and individual AI models such as the Feed Forward Neural Network (FFNN), Adaptive Neuro-Fuzzy Inference Systems (ANFIS), and Support Vector Regression (SVR). The goal of this study was to predict the inflow to the Alavian dam’s reservoir located in the north-west of Iran, in multi-step ahead using an ensemble of several AI models. The input data included inflow to the dam’s reservoir, temperature, evaporation, rainfall and snow cover of the basin from 1997 to 2022. To this aim first, time series models and AI-based models of FFNN, ANFIS and SVR were individually used to predict the multi-step ahead inflows. Then, to improve the modeling performance, the AI-based models were ensembled through simple linear averaging, weighted linear averaging and non-linear averaging. Findings suggested that employment of ensemble was more accurate than the individual models, especially the non-linear technique of artificial neural ensemble. Based on the obtained results, SVR outperformed other individual models and uncertainty associated with SVR based on Coverage Width-Based Criterion measure declined down to 62%. The ensemble of individual models could decline the uncertainty of modeling down to 83%. Thus, by increasing the lag time in prediction of inflow and associated uncertainty, the ensemble technique could decrease the uncertainty better than SVR.