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Information on how the trophic ecology of predators shapes their movement patterns and space-use is fundamental to understanding ecological processes across organisational levels. Despite this, studies combining spatial and trophic ecology to determine how prey preference and/or resource availability shape space use are lacking in marine predators as these can occur at low density and are often difficult to track over extended periods. Furthermore, many exhibit behavioural variability within species and among closely related, sympatric species adding further complexity. We applied a context-focused, multimethod approach to the understudied great hammerhead shark (Sphyrna mokarran) to test if movement and home ranges relate to prey preference and availability. Movement data from satellite and acoustic telemetry in Queensland, Australia, were combined with stable-isotope analysis, drone surveys, and videos of hunting behaviour. Limited dispersal, and small home ranges in S. mokarran were linked to trophic specialisation on stingray prey. Drone surveys and videos showed predation events on stingrays and demonstrated high, year-round availability of this prey in shallow, inshore habitats, which may allow the majority of S. mokarran to remain resident. This affinity for inshore habitats suggests that critical life-history requirements are performed over local or regional scales, although some larger movements were evident. These results were interpreted in comparison to the well-studied bull shark (Carcharhinus leucas), which showed reliance on pelagic food webs. Carcharhinus leucas had high individual variability in movement, with both large-scale migrations and residency. This could indicate that only some individuals are locally sustained on dynamic, pelagic food webs, while others undergo large-scale excursions over distant habitats. The specialised foraging of S. mokarran indicates they play an apex predator role in shallow, inshore habitats, potentially shaping space-use, and foraging behaviour of batoids. As inshore habitats are disproportionately affected by anthropogenic stressors, S. mokarran's trophic specialisation and limited demographic connectivity may make the species particularly vulnerable to anthropogenic threats. [ABSTRACT FROM AUTHOR]

Information on how the trophic ecology of predators shapes their movement patterns and space-use is fundamental to understanding ecological processes across organisational levels. Despite this, studies combining spatial and trophic ecology to determine how prey preference and/or resource availability shape space use are lacking in marine predators as these can occur at low density and are often difficult to track over extended periods. Furthermore, many exhibit behavioural variability within species and among closely related, sympatric species adding further complexity. We applied a context-focused, multi-method approach to the understudied great hammerhead shark (Sphyrna mokarran) to test if movement and home ranges relate to prey preference and availability. Movement data from satellite and acoustic telemetry in Queensland, Australia, were combined with stable-isotope analysis, drone surveys, and videos of hunting behaviour. Limited dispersal, and small home ranges in S. mokarran were linked to trophic specialisation on stingray prey. Drone surveys and videos showed predation events on stingrays and demonstrated high, year-round availability of this prey in shallow, inshore habitats, which may allow the majority of S. mokarran to remain resident. This affinity for inshore habitats suggests that critical life-history requirements are performed over local or regional scales, although some larger movements were evident. These results were interpreted in comparison to the well-studied bull shark (Carcharhinus leucas), which showed reliance on pelagic food webs. Carcharhinus leucas had high individual variability in movement, with both large-scale migrations and residency. This could indicate that only some individuals are locally sustained on dynamic, pelagic food webs, while others undergo large-scale excursions over distant habitats. The specialised foraging of S. mokarran indicates they play an apex predator role in shallow, inshore habitats, potentially shaping space-use, and foraging behaviour of batoids. As inshore habitats are disproportionately affected by anthropogenic stressors, S. mokarran’s trophic specialisation and limited demographic connectivity may make the species particularly vulnerable to anthropogenic threats. [ABSTRACT FROM AUTHOR]

Objectives. Bayesian mapping is an effective spatiotemporal approach to identify high-risk geographic areas for diseases and has not been used to identify oral cancer hotspots in Australia previously. This retrospective disease mapping study was undertaken to identify the oral cancer trends and patterns within the Queensland state in Australia. Methods. This study included data obtained from Queensland state Cancer Registry from 1982 to 2018. Domains mapped included the oral cancer incidence and mortality in Queensland (QLD). Local government areas (LGAs) and suburbs were utilized as geographical units for the estimation using Bayesian mapping approach. Results. Of the 78 LGAs, 21 showed high-oral cancer incidence as measured using higher median smoothed incidence risk (SIR), above the state average. Specifically, nine LGAs within predominantly rural areas had SIR above 100% of the state average. Of these, only one LGA (Mount Isa City) had a median smoothed SIR and 95% CI of 2.61 (2.14–3.15) which was constantly above 100% of the state average. Furthermore, mortality risk estimated using smoothed mortality risk (SMR), were significantly higher than the state average in 31 LGAs. Seventeen LGAs had a median SMR above 100% of the state average while three LGAs had the highest overall, 3- and 5-year mortality risks. Considering the 95% credible interval which is indicative of the uncertainty around the estimates, three LGAs had the highest overall mortality risks—Yarrabah Aboriginal Shire (3.80 (2.16–6.39)), Cook Shire (3.37 (2.21–5.06)), and Mount Isa City (3.04 (2.40–3.80)). Conclusion. Bayesian disease mapping approach identified multiple incidence and mortality hotspots within regional areas of the Queensland. Findings from our study can aid in designing targeted public health screening and interventions for primary prevention of oral cancer in regional and remote communities. [ABSTRACT FROM AUTHOR]

Background: Achieving health equity has been identified as a major challenge, both internationally and within Australia. Inequalities in cancer outcomes are well documented, and must be quantified before they can be addressed. One method of portraying geographical variation in data uses maps. Recently we have produced thematic maps showing the geographical variation in cancer incidence and survival across Queensland, Australia. This article documents the decisions and rationale used in producing these maps, with the aim to assist others in producing chronic disease atlases. Methods: Bayesian hierarchical models were used to produce the estimates. Justification for the cancers chosen, geographical areas used, modelling method, outcome measures mapped, production of the adjacency matrix, assessment of convergence, sensitivity analyses performed and determination of significant geographical variation is provided. Conclusions: Although careful consideration of many issues is required, chronic disease atlases are a useful tool for assessing and quantifying geographical inequalities. In addition they help focus research efforts to investigate why the observed inequalities exist, which in turn inform advocacy, policy, support and education programs designed to reduce these inequalities. [ABSTRACT FROM AUTHOR]

Background: There has been a decline in the stroke incidence across high income countries but such knowledge exists at Country or State rather than areal unit level such local government area (LGA). In this disease mapping study, we evaluate if there are local hot spots or temporal trends in TIA rate. Such knowledge will be of help in planning healthcare service delivery across regions. Methods: Linked hospital discharge data (Victorian Admitted Episodes Dataset or VAED) was used to collect TIA (defined by ICD-10-AM codes G450-G459) cases from 2001 to 2011. The State of Victoria is the second most populous state in Australia, with a population of 6.7 million and can be divided into 79 administrative units or LGA. The data is anonymized and contains residence of the patient in terms of LGA but not exact location. The date of the TIA event when the patient is admitted to hospital is provided in the dataset. The number of TIAs per year was aggregated for each LGA. Standardized TIA ratios were calculated by dividing actual over expected cases for each LGA per year. We used Integrated Nested Laplace Approximation (INLA) to perform spatial and spatiotemporal regression, adjusting for hypertension, sex and population, age (≥60), and socio-economic status (SES) decile within the LGA. The final model was chosen based on the lowest the Deviance Information Criterion (DIC) and Watanabe-Akaike information criteria (WAIC). Results: Choropleth maps showed a higher standardized TIA ratios in North-West rural region. Compared to the baselinemodel (DIC 13,159, WAIC 13,261), adding in a spatial random effect significantly improved the model (DIC 6,463, WAIC 6,667). However, adding a temporal component did not lead to a significant improvement (DIC 6,483, WAIC 6,707). Conclusion: Our finding suggests a statically significant spatial component to TIA rate over regional areas but no temporal changes or yearly trends. We propose that such exploratory method should be followed by evaluation of reasons for regional variations and which in turn can identify opportunities in primary prevention of stroke, and stroke care. [ABSTRACT FROM AUTHOR]

This paper proposes a novel data driven framework for detecting topology transitions in a distribution network. The framework analyzes data from phasor measurement units (PMUs) and relies on the fact that changes in network topology results in changes in the structure and admittance of the network. Using voltage and current phasors recorded by PMUs, the proposed method approximates network parameters using an ensemble-based deep learning model and thus, it does not require any knowledge of network parameters and load models. Using the prediction error of the proposed model, a connectivity matrix which shows the status of switches is constructed. In contrast to other methods, this proposed framework does not require a library of voltage and current transients associated with possible network transitions. It can also detect simultaneous switching actions and is robust to noise and load variations. The model yields a lower error detection rate, and its performance is validated using a modified version of the IEEE 33 bus network and a real feeder located in Queensland, Australia, under full and partial observability conditions. The proposed model has also been compared with another data driven method in terms of inference time and error detection rates. [ABSTRACT FROM AUTHOR]

This article focuses on the issue of scaled tracking consensus for discrete-time second-order multiagent systems under random packet dropouts, where the cases with a static leader and a dynamic leader are considered, respectively. The scaled tracking consensus means that all agents reach a consensus value determined by the leader but with different scales, and the phenomenon of packet dropout on each communication link is described as a Bernoulli variable independent of other communication links. By virtue of random environment-based scaled consensus algorithms, it is shown how to reconstruct the original system into augmented error systems with random coefficient matrices. With the kind assistance of substochastic matrix and super-stochastic matrix, sufficient conditions for the cases with a static leader and a dynamic leader are derived, respectively. Moreover, computer simulations are performed to demonstrate the dynamics of network agents under random packet dropouts. [ABSTRACT FROM AUTHOR]

Background: Public health policies and recommendations aim to be informed by the best available evidence. Evidence underpinning e-cigarettes policy recommendations has been necessarily limited due to the novelty of the technology and the lack of long-term epidemiological studies and trials. Some public health bodies have actively encouraged e-cigarette use whilst others have raised concerns over introducing new health risks and renormalising tobacco smoking. Using citation network analysis we investigated the author conflicts of interest and study funding statements within sources of evidence used by public health bodies when making recommendations about e-cigarette policy. Methods: We conducted citation network analysis of public health recommendation documents across four purposively selected diverse jurisdictions: WHO, UK, Australia, and USA. We extracted all citations from 15 public health recommendation documents, with more detailed data collected for influential citations (used in 3+ recommendation documents). We analysed the relationships between the sources of evidence used across jurisdictions using block modelling to determine if similar groups of documents were used across different jurisdictions. We assessed the frequency and nature of conflicts of interest. Results: 1700 unique citations were included across the 15 public health recommendation documents, with zero to 923 citations per document (median = 63, IQR = 7.5–132). The evidence base underpinning public health recommendations did not systematically differ across jurisdictions. Of the 1700 citations included, the majority were journal articles (n = 1179). Across 1081 journal articles published between 1998–2018, 200 declared a conflict of interest, 288 contained no mention of conflicts of interest, and 593 declared none. Conflicts of interest were reported with tobacco (3%; n = 37 journal articles of 1081), e-cigarette (7%; n = 72), and pharmaceutical companies (12%; n = 127), with such conflicts present even in the most recent years. There were 53 influential citations, the most common study type was basic science research without human subjects (e.g. examination of aerosols and e-liquids) (n = 18) followed by systematic review (n = 10); with randomised control trial being least common (n = 4). Network analysis identified clusters of highly-cited articles with a higher prevalence of conflicts of interest. Conclusion: Public health bodies across different jurisdictions drew upon similar sources of evidence, despite articulating different policy approaches to e-cigarettes. The evidence drawn upon, including the most influential evidence, contained substantial conflicts of interest (including relationships with e-cigarette and tobacco industries). Processes to explicitly manage conflicts of interest arising from the underlying evidence base may be required when developing public health recommendations. [ABSTRACT FROM AUTHOR]

The relationship between metapopulation stability and connectivity has long been investigated in ecology, however, most of these studies are focused on theoretical species and habitat networks, having limited ability to capture the complexity of real‐world metapopulations. Network analysis became more important in modeling connectivity, but it is still uncertain which network metrics are reliable predictors of persistence. Here we quantify the impact of connectivity and larval life history on marine metapopulation persistence across the complex seascape of southeast Australia. Our work coupled network‐based approaches and eigenanalysis to efficiently estimate metapopulation‐wide persistence and the subpopulation contributions. Larval dispersal models were used to quantify species‐specific metapopulation connectivity for five important fisheries species, each summarized as a migration matrix. Eigenanalysis helped to reveal metapopulation persistence and determine the importance of node‐level network properties. Across metapopulations, the number of local outgoing connections was found to have the largest impact on metapopulation persistence, implying these hub subpopulations may be the most influential in real‐world metapopulations. Results also suggest the length of the pre‐competency period may be the most influential parameter on metapopulation persistence. Finally, we identified two major hot spots of local connectivity in southeast Australia, each contributing strongly to multispecies persistence. Managers and ecologists would benefit by employing similar approaches in making more efficient and more ecologically informed decisions and focusing more on local connectivity patterns and larval competency characteristics to better understand and protect real‐world metapopulation persistence. Practically this could mean developing more marine protected areas at shorter distances and supporting collaborative research into the early life histories of the species of interest. [ABSTRACT FROM AUTHOR]

Compared with traditional models, semi-random epidemic network models may be more reasonable to describe the real dynamics of many epidemics. In this paper, we first investigate the optimal control problem (OCP) of semi-random epidemic networks. By using the Pontryagin’s minimum principle, we obtain the optimal control strategy aimed to minimize the total epidemic incidence and control cost. We then define a centrality index which can measure average control strength of the optimal control. Based on this index, the OCP is converted into a static OCP (SOCP), whose solution is utilized to design a nonidentical constant control (NCC). NCC is suboptimal as it is optimal on a subset of the whole control set, and is determined by only the network’s clustering coefficient and initial condition. We finally propose an effective targeted constant quarantine control by using this centrality index. The results uncover the relationship between the optimal control and the network’s topological structure, provide a convenient method to determine suboptimal control, and present a strategy for targeted constant control. This paper can help to design effective control strategies for more general epidemic networks in the real world. [ABSTRACT FROM AUTHOR]

Background: Children's early development plays a vital role for maintaining healthy lives and influences future outcomes. It is also heavily affected by community factors which vary geographically. Direct methods do not provide a comprehensive picture of this variation, especially for areas with sparse populations and low data coverage. In the context of Australia, the Australian Early Development Census (AEDC) provides a measure of early child development upon school entry. There are two primary aims of this study: (i) provide improved prevalence estimates of children who are considered as developmentally vulnerable in regions across Australia; (ii) ascertain how social-economic disadvantage partly explains the spatial variation. Methods: We used Bayesian spatial hierarchical models with the Socio-economic Indexes for Areas (SEIFA) as a covariate to provide improved estimates of all 335 SA3 regions in Australia. The study included 308,953 children involved in the 2018 AEDC where 21.7% of them were considered to be developmentally vulnerable in at least one domain. There are five domains of developmental vulnerability—physical health and wellbeing; social competence; emotional maturity; language and cognitive skills; and communication and general knowledge. Results: There are significant improvements in estimation of the prevalence of developmental vulnerability through incorporating the socio-economic disadvantage in an area. These improvements persist in all five domains—the largest improvements occurred in the Language and Cognitive Skills domain. In addition, our results reveal that there is an important geographical dimension to developmental vulnerability in Australia. Conclusion: Sparsely populated areas in sample surveys lead to unreliable direct estimates of the relatively small prevalence of child vulnerability. Bayesian spatial modelling can account for the spatial patterns in childhood vulnerability while including the impact of socio-economic disadvantage on geographic variation. Further investigation, using a broader range of covariates, could shed more light on explaining this spatial variation. [ABSTRACT FROM AUTHOR]

The latent friend recommendation in online social media is interesting, yet challenging, because the user-item ratings and the user–user relationships are both sparse. In this paper, we propose a new dual implicit mining-based latent friend recommendation model that simultaneously considers the implicit interest topics of users and the implicit link relationships between the users in the local topic cliques. Specifically, we first propose an algorithm called all reviews from a user and all tags from their corresponding items to learn the implicit interest topics of the users and their corresponding topic weights, then compute the user interest topic similarity using a symmetric Jensen–Shannon divergence. After that, we adopt the proposed weighted local random walk with restart algorithm to analyze the implicit link relationships between the users in the local topic cliques and calculate the weighted link relationship similarity between the users. Combining the user interest topic similarity with the weighted link relationship similarity in a unified way, we get the final latent friend recommendation list. The experiments on real-world datasets demonstrate that the proposed method outperforms the state-of-the-art latent friend recommendation methods under four different types of evaluation metrics. [ABSTRACT FROM AUTHOR]

Portions of the south coast of Western Australia are recognized as environmentally valuable because of high levels of biodiversity, but are at risk due to continued anthropogenic influences, particularly in the form of fragmentation and habitat loss. Corridors of habitat, either continuous or stepping-stone, are deemed to be valuable for the maintenance and increase of biodiversity in the region. Here we apply a series of betweenness centrality analyses to quantify the connectivity in the region. The method we describe here is an extended application of the betweenness centrality measure, which is a measure of spatial connectivity that is applied to fragmented landscapes. The method is used for significant corridors between the Stirling Ranges and the Fitzgerald River National Park to identify a series of locations that are important to the connectivity in this region and thus may provide effective locations for restoration inputs. [ABSTRACT FROM AUTHOR]

Shiga toxin-producing Escherichia coli (STEC) O113:H21 strains are associated with human diarrhea and some strains may cause hemolytic–uremic syndrome (HUS). In Brazil, these strains are commonly found in cattle but, so far, were not isolated from HUS patients. Here, a system biology approach was used to investigate the differential transcriptomic and phenotypic responses of enterocyte-like Caco-2 cells to two STEC O113:H21 strains with similar virulence factor profiles (i.e., expressing stx2, ehxA, epeA, espA, iha, saa, sab, and subA): EH41 (Caco-2/EH41), isolated from a HUS patient in Australia, and Ec472/01 (Caco-2/Ec472), isolated from bovine feces in Brazil, during a 3 h period of bacteria–enterocyte interaction. Gene co-expression network analysis for Caco-2/EH41 revealed a quite abrupt pattern of topological variation along 3 h of enterocyte–bacteria interaction when compared with networks obtained for Caco-2/Ec472. Transcriptional module characterization revealed that EH41 induces inflammatory and apoptotic responses in Caco-2 cells just after the first hour of enterocyte–bacteria interaction, whereas the response to Ec472/01 is associated with cytoskeleton organization at the first hour, followed by the expression of immune response modulators. Scanning electron microscopy showed more intense microvilli destruction in Caco-2 cells exposed to EH41 when compared to those exposed to Ec472/01. Altogether, these results show that EH41 expresses virulence genes, inducing a distinctive host cell response, and is likely associated with severe pathogenicity. [ABSTRACT FROM AUTHOR]

Background: In 2014, a large metropolitan mental health service in Australia developed a senior role (Lead Research Occupational Therapist) to address an identified need for greater research and knowledge translation, and associated capacity building. The aim of this study was to evaluate the impact, in the first 2.5 years, of this role across a range of variables.Methods: Multiple methods were used to gather a comprehensive range of data. Workforce surveys were completed both online and in hard copy in early 2014 (n = 42) and late 2016 (n = 44). Research key performance indicators (academic, research production and cultural) were also identified for measurement over time. The data from these surveys were analysed using descriptive and inductive analysis, and also with social network analysis.Results: This role has demonstrated positive outcomes across a range of variables. There was a medium effect on the quantity of participation in quality assurance and knowledge translation activities by the workforce. Most knowledge translation behaviours were occurring regularly, although several were absent. An improving trend in attitudes towards evidence-based practice was recorded, and perceptions of the knowledge translation role were generally positive. The Lead Research Occupational Therapist moved from the periphery to the centre of the evidence based practice social network. Improved awareness of other clinicians deploying evidence based practice was observed, and the frequency of interaction between clinicians increased. The role has met all key performance indicators, across the academic, research production and cultural domains.Conclusions: The shift in focus of this role from research to knowledge translation has produced tangible outcomes for the occupational therapy workforce. These achievements have had a positive impact on the sustainability of the role, which will be continued for at least another two years. An ongoing challenge is to directly measure the impact of this role on outcomes for people with mental illness and their carers. [ABSTRACT FROM AUTHOR]