Search

We developed a high-resolution machine learning based surrogate model to identify a robust land-use future for Australia which meets multiple UN Sustainable Development Goals. We compared machine learning models with different architectures to pick the best performing model considering the data type, accuracy metrics, ability to handle uncertainty and computational overhead requirement. The surrogate model, called ML-LUTO Spatial, was trained on the Land-Use Trade-Offs (version 1.0) model of Australian agricultural land system sustainability. Using the surrogate model, we generated projections of land-use futures at 1.1 km resolution with 95% classification accuracy, and which far surpassed the computational benchmarks of the original model. This efficiency enabled the generation of numerous SDG-compliant (SDGs 2, 6, 7, 13, 15) future land-use maps on a standard laptop, a task previously dependent upon high-performance computing clusters. Combining these projections, we derived a single, robust land-use future and quantified the uncertainty. Our findings indicate that while agricultural land-use remains dominant in all Australian regions, extensive carbon plantings were identified in Queensland and environmental plantings played a role across the study area, reflecting a growing urgency for offsetting greenhouse gas emissions and the restoration of ecosystems to support biodiversity across Australia to meet the 2050 Sustainable Development Goals., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The significant increase in hazardous waste generation in Australia has led to the discussion over the incorporation of artificial intelligence into the hazardous waste management system. Recent studies explored the potential applications of artificial intelligence in various processes of managing waste. However, no study has examined the use of text mining in the hazardous waste management sector for the purpose of informing policymakers. This study developed a living review framework which applied supervised text classification and text mining techniques to extract knowledge using the domain literature data between 2022 and 2023. The framework employed statistical classification models trained using iterative training and the best model XGBoost achieved an F1 score of 0.87. Using a small set of 126 manually labelled global articles, XGBoost automatically predicted the labels of 678 Australian articles with high confidence. Then, keyword extraction and unsupervised topic modelling with Latent Dirichlet Allocation (LDA) were performed. Results indicated that there were 2 main research themes in Australian literature: (1) the key waste streams and (2) the resource recovery and recycling of waste. The implication of this framework would benefit the policymakers, researchers, and hazardous waste management organisations by serving as a real time guideline of the current key waste streams and research themes in the literature which allow robust knowledge to be applied to waste management and highlight where the gap in research remains., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Understanding perceptions of indigenous people toward natural disasters is essential in social and environmental research to facilitate further studies in investigating the impacts of the events, as well as in examining the adaptive strategies and having implications for policymakers and relevant institutional bodies. We took this essential feature to study the perceptions of local people toward the two common natural disasters: flash floods and landslides. We selected the case study in three communes (An Binh, An Thinh, and Dai Son) in Van Yen district, Yen Bai province in Vietnam. This is because flash floods and landslides are two frequent natural disasters that highly adversely affect these areas where major poor ethnic minority communities reside. We conducted six Focus Group Discussions (FGDs) and household surveys (405 households) in 2016. The results showed that a decline in productivity, a decrease in income, more hard-working conditions, and an increase in daily expenses were the most observed impacts of these natural disasters in the communes. The analysis also revealed that almost 45% of farmers perceived an increasing trend in the frequency and impacts of flash floods and landslides over the past 15 years. A Multinomial Logit (MNL) model was used to analyze the determinants of farmers' awareness of flash floods and landslides, which indicated that farmers' perceptions of flash floods and landslides are associated with socio-economic characteristics, such as gender, agricultural experience, ethnic groups, climate information, and household income conditions. We suggested that local governments should pay more attention to strengthen farmers' awareness to help improve perceptions of local people toward common natural disasters so that they would gain better adaptive capacities and become more sustainable, which are in line with the Sustainable Development Goals., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Accurate delineation of the proximal bronchial tree (PBT) is crucial for appropriate assessment of lung tumor centrality and choice of Stereotactic Ablative Body Radiotherapy (SABR) dose prescription. Here, we investigate variabilities in manual PBT delineation and their potential to influence assessing lesion centrality. A fully automatic, intensity-based tool for PBT contouring and measuring distance to the target is also described. This retrospective analysis included a total of 61 patients treated with lung SABR. A subset of 41 patients was used as a training dataset, containing clinical PBT contour and additional subsequently generated manual contours. The tool was optimized and compared against manual contours in terms of volume, distance to the target and various overlap/similarity metrics. The remaining 20 patients were used as a validation dataset to investigate the dosimetric effects of variations between manual and automatic PBT contours. Considerable interobserver variability was observed, particularly in identifying the superior and inferior borders of the PBT. Automatic PBT contours were comparable to manual contours with average Dice of 0.63 to 0.79 and mean distance to agreement of 1.78 to 3.34 mm. No significant differences in dosimetric parameters were found between automatically and manually generated contours. A moderate negative correlation was found between PBT maximum dose and distance to the lesion (p < 0.05). Variability in manual PBT delineation may result in inconsistent assessment of tumor centrality. Automatic contouring can help standardize clinical practice, support investigations into the link between SABR outcomes and lesion proximity to central airways and the development of predictive toxicity models that incorporate precise measurements of tumor location in relation to high-risk organs., Competing Interests: Declaration of Competing Interest None., (Copyright © 2020 American Association of Medical Dosimetrists. Published by Elsevier Inc. All rights reserved.)

Thanks to sequencing technology, modern molecular bioscience datasets are often compositions of counts, e.g. counts of amplicons, mRNAs, etc. While there is growing appreciation that compositional data need special analysis and interpretation, less well understood is the discrete nature of these count compositions (or, as we call them, lattice compositions) and the impact this has on statistical analysis, particularly log-ratio analysis (LRA) of pairwise association. While LRA methods are scale-invariant, count compositional data are not; consequently, the conclusions we draw from LRA of lattice compositions depend on the scale of counts involved. We know that additive variation affects the relative abundance of small counts more than large counts; here we show that additive (quantization) variation comes from the discrete nature of count data itself, as well as (biological) variation in the system under study and (technical) variation from measurement and analysis processes. Variation due to quantization is inevitable, but its impact on conclusions depends on the underlying scale and distribution of counts. We illustrate the different distributions of real molecular bioscience data from different experimental settings to show why it is vital to understand the distributional characteristics of count data before applying and drawing conclusions from compositional data analysis methods., (© The Author(s) 2019. Published by Oxford University Press on behalf of NAR Genomics and Bioinformatics.)

Objective: This study examined the potential acceptability of wearable devices (e.g., smart headbands, wristbands, and watches) aimed at treating mental health disorders, relative to conventional approaches., Methods: A questionnaire assessed perceptions of wearable and nonwearable treatments, along with demographic and psychological information. Respondents (N = 427) were adults from a community sample (M age  = 44.6, SD age  = 15.3) which included current (30.2%) and former (53.9%) mental health help-seekers., Results: Perceived effectiveness of wearables was a strong predictor of interest in using them as adjuncts to talk therapies, or as an alternative to self-help options (e.g., smartphone applications). Devices were more appealing to those with negative evaluations of psychological therapy and less experience in help-seeking., Conclusions: Interest in using wearable devices was strong, particularly when devices were seen as effective. Clients with negative attitudes to conventional therapies may be more responsive to using wearable devices as a less directive treatment approach., (© 2020 Wiley Periodicals, Inc.)

Microbial communities in subsurface coal seams are responsible for the conversion of coal organic matter to methane. This process has important implications for both energy production and our understanding of global carbon cycling. Despite the environmental and economic importance of this process, little is known about which components of the heterogeneous coal organic matter are biodegradable under methanogenic conditions. Similarly, little is known about which taxa in coal seams carry out the initial stages of coal organics degradation. To identify the biodegradable components of coal and the microorganisms responsible for their breakdown, a subbituminous coal was fractionated into a number of chemical compound classes which were used as the sole carbon source for growth by a coal seam microbial community. This study identifies 65 microbial taxa able to proliferate on specific coal fractions and demonstrates a surprising level of substrate specificity among members of this coal-degrading microbial consortia. Additionally, coal kerogen, the solvent-insoluble organic component of coal often considered recalcitrant to microbial degradation, appeared to be readily converted to methane by microbial degradation. These findings challenge our understanding of coal organic matter catabolism and provide insights into the catabolic roles of individual coal seam bacteria., (© FEMS 2019.)

Anthropogenic activities, such as mining and agriculture, have resulted in many freshwater systems having elevated concentrations of copper. Despite the prevalence of this contamination, and the vital ecological function of prokaryotes, just three studies have investigated prokaryote community responses to copper concentration in freshwater sediments. To address this, the current study investigated these communities in outdoor mesocosms spiked with varying copper concentrations. We profiled the prokaryotic communities at the taxonomic level, using next-generation high-throughput sequencing techniques, as well as their function, using baiting with leaf analogues, and Biolog Ecoplates for community-level physiological profiling. Sediments containing just 46 mg kg -1 of copper, had distinctly different microbial communities compared with controls, as determined by both DNA and RNA 16S ribosomal RNA gene (rRNA) profiling. In addition to this, sediment communities displayed a greatly reduced utilisation of carbon substrates under elevated copper, while the communities recruited onto leaf analogues were also disparate from those of control ponds. Given the vital role of prokaryotes in ecosystem processes, including carbon cycling, these changes are potentially of great ecological relevance, and are seen to occur well below the 'low risk' sediment quality guideline values (SQGV) used by regulatory bodies internationally., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

We provided the first scientific record of Melanagromyza sojae (Zehntner, 1900), through molecular characterization of partial mtDNA COI gene, that confirms the occurrence of this pest in Paraguay. Previously reported in Brazil, an outbreak of larvae of M. sojae known as the soybean stem fly (SSF) that belongs to the family Agromyzidae, was also noted in soybean fields from the Canindeyú, Alto Paraná and Itapúa Departments in Paraguay. This pest is highly polyphagous, attacking various host plant species from the family Fabaceae, such as soybean and other beans. The implications of SSF detection in Paraguay are discussed in relation to the current soybean cultivation practices from this agriculturally important South American region, including Brazil.

Objective This study aimed to evaluate users' acceptance of a teledentistry model utilizing a smartphone camera used for dental caries screening and to identify a number of areas for improvement of the system. Methods A store-and-forward telemedicine platform "Remote-I" was developed to assist in the screening of oral diseases using an image acquisition Android app operated by 17 teledental assistants. A total of 485 images (five images per case) were directly transmitted from the Android app to the server. A panel of five dental practitioners (graders) assessed the images and reported their diagnosis. A user acceptance survey was sent to the graders and smartphone users following completion of the screening program. Results Of the 22 surveys sent out, 20 (91%) were completed. Generally, users showed optimism towards the use of the teledentistry system, and strongly positively assessed items on content and service quality. The majority of graders took less than 15 min to read the images while phone users took 5-10 min to complete the dental photography using the Android app. This study identified a number of factors that are essential for improving the current system, such as optimization of smartphone camera features, the format of the server, and the orientation of images and using oral retractors during photography. Conclusions Users appear to be generally satisfied with the proposed teledentistry model. However, they have specific concerns to address, many of which could be resolved through more effective training, coordination between sites and upgrading the current system.

This study investigates the mortality effect of primary and secondary PM2.5 related to ship exhaust in the Sydney greater metropolitan region of Australia. A detailed inventory of ship exhaust emissions was used to model a) the 2010/11 concentration of ship-related PM2.5 across the region, and b) the reduction in PM2.5 concentration that would occur if ships used distillate fuel with a 0.1% sulfur content at berth or within 300 km of Sydney. The annual loss of life attributable to 2010/11 levels of ship-related PM2.5 and the improvement in survival associated with use of low-sulfur fuel were estimated from the modelled concentrations. In 2010/11, approximately 1.9% of the region-wide annual average population weighted-mean concentration of all natural and human-made PM2.5 was attributable to ship exhaust, and up to 9.4% at suburbs close to ports. An estimated 220 years of life were lost by people who died in 2010/11 as a result of ship exhaust-related exposure (95% CIβ: 140-290, where CIβ is the uncertainty in the concentration-response coefficient only). Use of 0.1% sulfur fuel at berth would reduce the population weighted-mean concentration of PM2.5 related to ship exhaust by 25% and result in a gain of 390 life-years over a twenty year period (95% CIβ: 260-520). Use of 0.1% sulfur fuel within 300 km of Sydney would reduce the concentration by 56% and result in a gain of 920 life-years over twenty years (95% CIβ: 600-1200). Ship exhaust is an important source of human exposure to PM2.5 in the Sydney greater metropolitan region. This assessment supports intervention to reduce ship emissions in the GMR. Local strategies to limit the sulfur content of fuel would reduce exposure and will become increasingly beneficial as the shipping industry expands. A requirement for use of 0.1% sulfur fuel by ships within 300 km of Sydney would provide more than twice the mortality benefit of a requirement for ships to use 0.1% sulfur fuel at berth., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

This study examined the short-term effects of temperature on cardiovascular hospital admissions (CHA) in the largest tropical city in Southern Vietnam. We applied Poisson time-series regression models with Distributed Lag Non-Linear Model (DLNM) to examine the temperature-CHA association while adjusting for seasonal and long-term trends, day of the week, holidays, and humidity. The threshold temperature and added effects of heat waves were also evaluated. The exposure-response curve of temperature-CHA reveals a J-shape relationship with a threshold temperature of 29.6 °C. The delayed effects temperature-CHA lasted for a week (0-5 days). The overall risk of CHA increased 12.9% (RR, 1.129; 95%CI, 0.972-1.311) during heatwave events, which were defined as temperature ≥ the 99th percentile for ≥2 consecutive days. The modification roles of gender and age were inconsistent and non-significant in this study. An additional prevention program that reduces the risk of cardiovascular disease in relation to high temperatures should be developed., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

This Australian benthic data set (BENTHOZ-2015) consists of an expert-annotated set of georeferenced benthic images and associated sensor data, captured by an autonomous underwater vehicle (AUV) around Australia. This type of data is of interest to marine scientists studying benthic habitats and organisms. AUVs collect georeferenced images over an area with consistent illumination and altitude, and make it possible to generate broad scale, photo-realistic 3D maps. Marine scientists then typically spend several minutes on each of thousands of images, labeling substratum type and biota at a subset of points. Labels from four Australian research groups were combined using the CATAMI classification scheme, a hierarchical classification scheme based on taxonomy and morphology for scoring marine imagery. This data set consists of 407,968 expert labeled points from around the Australian coast, with associated images, geolocation and other sensor data. The robotic surveys that collected this data form part of Australia's Integrated Marine Observing System (IMOS) ongoing benthic monitoring program. There is reuse potential in marine science, robotics, and computer vision research.

The Mekong Delta is the most vulnerable region to extreme climate and hydrological conditions however the association between these conditions and children's health has been little studied. We examine the association between annual river flood pulse and paediatric hospital admissions in a Vietnam Mekong Delta city. Daily paediatric hospital admissions (PHA) were collected from the City Paediatric Hospital, and daily river water level (RWL) and meteorological data were retrieved from the Southern Regional Hydro-Meteorological Centre from 2008 to 2011. We evaluated the association between annual river flood pulse (>=90th percentile of RWL) and PHA using the Poisson distributed lag model, controlling for temperature, relative humidity, day of week, seasonal and long-term trends. The seasonal pattern of PHA was examined using harmonic and polynomial regression models. The cumulative risk ratios estimated for a 15-day period following an extreme RWL was 1.26 (95%CI, 1.2-1.38) for all age groups, 1.27 (95%CI, 1.23-1.30) for under five-years and 1.15 (95%CI, 1.07-1.20) for school-aged children, 1.24 (95%CI, 1.21-1.27) for all-causes, 1.18 (95%CI, 1.12-1.21) for communicable infection, 1.66 (95%CI, 1.57-1.74) for respiratory infection and 1.06 (95%CI, 1.01-1.1) for other diseases. The peak PHA risk is in the September-October period corresponding to the highest RWL, and the PHA-RWL association was modified by temperature. An increase in PHA is significantly associated with annual river flood, and the pattern of PHA is seasonally correspondent to the RWL. These findings combined with projected changes in climate conditions suggest important implications of climate change for human health in the Mekong Delta region., (Copyright © 2014 Elsevier Inc. All rights reserved.)

Background: The gut microbiota is central to health and disorders such as inflammatory bowel disease. Differences in microbiota related to geography and ethnicity may hold the key to recent changes in the incidence of microbiota-related disorders., Methods: Gut mucosal microbiota was analyzed in 190 samples from 87 Caucasian and Chinese subjects, from Australia and Hong Kong, comprising 22 patients with Crohn's disease, 30 patients with ulcerative colitis, 29 healthy controls, and 6 healthy relatives of patients with Crohn's disease. Bacterial 16S rRNA microarray and 454 pyrosequencing were performed., Results: The microbiota was diverse in health, regardless of ethnicity or geography (operational taxonomic unit number and Shannon diversity index). Ethnicity and geography, however, did affect microbial composition. Crohn's disease resulted in reduced bacterial diversity, regardless of ethnicity or geography, and was the strongest determinant of composition. In ulcerative colitis, diversity was reduced in Chinese subjects only, suggesting that ethnicity is a determinant of bacterial diversity, whereas composition was determined by disease and ethnicity. Specific phylotypes were different between health and disease. Chinese patients with inflammatory bowel disease more often than healthy Chinese tended to have had a Western diet in childhood, in the East and West., Conclusion: The healthy microbiota is diverse but compositionally affected by geographical and ethnic factors. The microbiota is substantially altered in inflammatory bowel disease, but ethnicity may also play an important role. This may be key to the changing epidemiology in developing countries, and emigrants to the West.