29,040 research outputs found

    Partially Penetrating Lake-Aquifer Interaction in a Laboratory-scale Tidal Setting

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    Dataset made available per the CC BY 4.0 Creative Commons Attribution 4.0 International license https://creativecommons.org/licenses/by/4.0/Freshwater lakes close to the coast are important ecotones with strong functional dependency on ocean forces. Tides are likely to create dynamic lake-groundwater interactions, which have not been previously assessed for partially penetrating lakes. This study investigates tidal lake-groundwater interaction in a laboratory-scale aquifer cross-section with and without the existence of a partially penetrating lake. The experimental observations were reproduced by numerical models to allow for an in-depth evaluation of the experiments beyond those provided by direct measurements

    Radionuclide and stable elements in flora from Australian arid environments

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    Dataset made available per the CC BY 4.0 Creative Commons Attribution 4.0 International license https://creativecommons.org/licenses/by/4.0/Radiological impact assessments are an important tool for energy and resources industries and government safety regulators to assist in the protection of wildlife diversity, especially native species. Evaluations of radiological impacts to flora in the arid regions of Australia are currently based on international models that use predominately Northern Hemisphere data, with very limited Australian-specific data. This creates a degree of uncertainty in communicating the potential impact of relevant Australian assessments. The project aims to build an improved understanding of radionuclide concentration ratios and radionuclide pathways in arid Australian conditions and are expected to inform assessments in similar environmental conditions elsewhere. The dataset contains measurement of stable elements and radionuclides in soils and plants that were obtained from three regions in South Australia: Flinders Ranges, Pernatty and Roxby Downs region. Access to Australian specific data for use in radiological impact models provide a better understanding and more credible environmental impact assessment process based on more relevant local information

    Decision-Support Modelling viewed through the lens of Model Complexity

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    Ā© Flinders University 2021. Copyright: This work is copyright. Apart from any use permitted under the Copyright Act 1968, no part may be reproduced by any process, nor may any other exclusive rights be exercised, without the permission of Flinders University, GPO Box 2100, Adelaide 5001, South Australia.A report on decision-support for groundwater modelling and management. The authorsā€™ perspectives on decision-support modelling are shown pictorially using a ā€œroadmapā€. This is intended to provide modellers with scientifically-based guidance for selection of a level of structural and parameterisation complexity that is appropriate for the decision-support context in which they are working. It may also assist modelling stakeholders to understand how groundwater modelling can best respond to the decision support imperatives that it is meant to serve

    Digital Education in the College of Humanities, Arts and Social Sciences: Discipline Discussions

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    CC BY-NC-ND Flinders UniversityThe research reported here was undertaken by the Digital Education Working Group (DEWG) to achieve the following four objectives, in line with the CHASS Digital Education Action Plan: 1. To better understand the perspectives on, experiences with and plans for digital education across the College to inform further strategy or changes in the Collegeā€™s approach to digital education. 2. To scope the professional learning and resourcing needs in a systematic and robust way to ensure adequate support is being provided. 3. To gather insights on current discipline-based models of learning and teaching to inform recommendations on the scholarship of teaching, particularly online teaching models. 4. To synthesise current good practice examples. The DEWG research team worked with eight discipline groups across CHASS in 2021: Archaeology, English, Geography, History, Indigenous Studies, Languages, Philosophy, and Screen and Media. This report serves as a high-level synthetic overview of the results of in-depth focus group interviews conducted with staff and makes recommendations about ways forward for digital education, with relevant stakeholders identified at College and University levels. Here, DEWG and the Collegeā€™s executive leadership team hold responsibility for understanding, driving, improving and supporting the digital education strategies in the College. The report summarises key findings across several key areas

    Probabilistic Contributing Area Analysis: A GMDSI worked example report

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    Copyright Flinders UniversityPREFACE The Groundwater Modelling Decision Support Initiative (GMDSI) is an industry-funded and industry-aligned project focused on improving the role that groundwater modelling plays in supporting environmental management and decision-making. Over the life of the project, it will document a number of examples of decision-support groundwater modelling. These documented worked examples will attempt to demonstrate that by following the scientific method, and by employing modern, computer-based approaches to data assimilation, the uncertainties associated with groundwater model predictions can be both quantified and reduced. With realistic confidence intervals associated with predictions of management interest, the risks associated with different courses of management action can be properly assessed before critical decisions are made. GMDSI worked example reports, one of which you are now reading, are deliberately different from other modelling reports. They do not describe all of the nuances of a particular study site. They do not provide every construction and deployment detail of a particular model. In fact, they are not written for modelling specialists at all. Instead, a GMDSI worked example report is written with a broader audience in mind. Its intention is to convey concepts, rather than to record details of model construction. In doing so, it attempts to raise its readersā€™ awareness of modelling and data-assimilation possibilities that may prove useful in their own groundwater management contexts. The decision-support challenges that are addressed by various GMDSI worked examples include the following: ā€¢ assessing the reliability of a public water supply; ā€¢ protection of a groundwater resource from contamination; ā€¢ estimation of mine dewatering requirements; ā€¢ assessing the environmental impacts of mining; and ā€¢ management of aquifers threatened by salt water intrusion. In all cases the approach is the same. Management-salient model predictions are identified. Ways in which model-based data assimilation can be employed to quantify and reduce the uncertainties associated with these predictions are reported. Model design choices are explained in a way that modellers and non-modellers can understand. The authors of GMDSI worked example reports make no claim that the modelling work which they document cannot be improved. As all modellers know, time and resources available for modelling are always limited. The quality of data on which a model relies is always suspect. Modelling choices are always subjective, and are often made differently with the benefit of hindsight. What we do claim, however, is that the modelling work which we report has attempted to implement the scientific method to address challenges that are typical of those encountered on a day-to-day basis in groundwater management worldwide. As stated above, a worked example report purposefully omits many implementation details of the modelling and data assimilation processes that it describes. Its purpose is to demonstrate what can be done, rather than to explain how it is done. Those who are interested in technical details are referred to GMDSI modelling tutorials. A suite of these tutorials has been developed specifically to assist modellers in implementing workflows such as those that are described herein. We thank and acknowledge our collaborators, and GMDSI project funders, for making these reports possible

    Dying, a normal part of life: what learners see as the one thing they could change in the workplace to more appropriately provide end-of-life care

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    Ā© Flinders University. This work is copyrighted. It may be reproduced in whole or in part for research or training purposes, subject to the inclusion of an acknowledgement of the source. It may not be reproduced for commercial use or sale. Reproduction for purposes other than those indicated above requires written permission from the Research Centre for Palliative Care, Death & Dying. Contact [email protected] for permissions.End-of-Life Essentials (EOLE) is a government funded project which aims to provide free peer-reviewed online education modules and implementation resources on end-of-life care to health professionals in acute hospitals in Australia. 'Dying, A Normal Part of Life' is an educational module featured in the suite of EOLE modules and includes education around the impact of end of life and dying on health care professionals working in acute hospitals, identifying common patterns of trajectories of dying, and discussing the reasons why dying in acute hospitals is often complex for professionals, patients, and families. This White Paper outlines and explores the results of the retrospective data analysis conducted for a two year period, 6th May 2017 to 5th May 2019. A total of 2232 learner statements responding to the free text response question posed at the end of the module: "Tomorrow, the one thing I can change to more appropriately provide end-of-life care isā€¦" were extracted from the EOLE learning platform. The results identified the following themes as nominated practice change areas: Patient-centred care; Communication skills; Humanising healthcare; Recognise and talk about dying; Organisational factors

    End-of-Life Online Health Education Uptake and Usage by Australian Health Professionals: Urban, Rural and Remote Settings

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    This work is copyrighted. It may be reproduced in whole or in part for research or training purposes, subject to the inclusion of an acknowledgement of the source. It may not be reproduced for commercial use or sale. Reproduction for purposes other than those indicated above requires written permission from the Flinders University Research Centre for Palliative Care, Death & Dying. Contact [email protected] for permissions.Access to skilled end-of-life care is particularly important for those who live in rural and remote areas in Australia given the high levels of chronic disease and higher mortality rates. However, health professionals in rural and remote areas do not always receive adequate training to provide this care due to lack of accessible education. End-of-Life Essentials (EOLE) is a government funded education project which aims to provide free peer-reviewed online education modules and implementation resources on end-of-life care to health professionals in acute hospitals in Australia. In order to understand the uptake and usage of the EOLE education modules, learnersā€™ geographical locations and module completion data from the first year of the program were analysed according to remoteness category. This White Paper outlines and explores the results of the retrospective data analysis conducted in June 2018. Data from learners who registered in the first year of the EOLE program was were extracted, and 4224 learners were included for data analysis. Study findings show that there is a good reach of EOLE to health professionals living in remote and very remote areas. As learners from very remote areas showed the highest proportion of module completion, it suggests the potential benefit of this important online education in providing accessible continuing end-of-life care education for health professionals residing in the most remote parts of Australia

    Relationships of eHealth Literacy to Socio-Demographic Characteristics and Engagement in Online Learning: A Quantitative Study

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    Ā© Flinders University. This work is copyrighted. It may be reproduced in whole or in part for research or training purposes, subject to the inclusion of an acknowledgement of the source. It may not be reproduced for commercial use or sale. Reproduction for purposes other than those indicated above requires written permission from the Research Centre for Palliative Care, Death & Dying.Over the next two decades, population growth, chronic disease progression and an ageing population will see a growing number of people confront the difficulties that often accompany coming to the end of oneā€™s life. Online palliative care resources can provide valuable information to individuals, families, carers, and others. In order to be effective, however, such resources need to be readily found, understood, and applied by consumers. eHealth literacy ā€“ the ability to find, understand, and apply online health resources ā€“ is becoming increasingly important in palliative care. While the body of literature pertaining to the way health information is provided to the community is growing, little is currently known about predictors of eHealth literacy in the context of death and dying, or how eHealth literacy is related to engagement with online health resources. This White Paper reports on a study undertaken to examine relationships between eHealth literacy and sociodemographic and personal characteristics within a sample enrolled in an online course about death and dying. The Study on which this White Paper reports used a convenience sample of students who were participating in a MOOC (massive open online course) about death and dying

    Rapid Data Assimilation Using an Appropriately Complex Model: a GMDSI worked example report

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    The Groundwater Modelling Decision Support Initiative (GMDSI) is an industry-funded and industry-aligned project focused on improving the role that groundwater modelling plays in supporting environmental management and decision-making. This GMDSI report addresses a number of related issues. They include: appropriate model complexity; appropriate parameterisation complexity; efficient model-based assimilation of information-rich data; and linear analysis. The focus of modelling work that is reported herein is BHPā€™s Orebody 31 (OB31) situated in the Pilbara region of Western Australia. The environs of this mine have been the focus of a number of generations of modelling, some of which is described in the present report. Mining of OB31 commenced in 2016; however data collection and modelling took place for a number of years prior to that

    Behavioural and heart rate responses to stressors in two populations of Little Penguins that differ in levels of human disturbance and predation risk

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    Dataset made available according to CC BY 4.0 Creative Commons Attribution 4.0 International license https://creativecommons.org/licenses/by/4.0/Dataset for report. Species that are constantly exposed to disturbances, such as human disturbance or nonā€lethal contacts with predators or conspecifics, can experience chronic stress. Within a species range, variation in the frequency and predictability of such disturbances can lead to population differences in stress response. Here, we investigated the stress response of Little Penguins Eudyptula minor to an introduced predator and a conspecific at two South Australian colonies that differed in habitat, conspecifics density, levels of human disturbance and predation risk (high, low). We used playback experiments of Cat Felis catus or Little Penguin calls and recorded the behaviour and physiological (heart rate) response of adults in relation to playback type (Cat, Penguin) as well as habitat characteristics (habitat type, nest type, nest visibility) and number of conspecifics present. Our results showed that individuals from the high disturbance colony (also living in a mixed habitat with fewer neighbours) exhibited higher vigilance and heart rate responses than individuals from the low disturbance colony (living in a closed habitat with a high number of neighbours). Our results highlight that guidelines for managing Penguin species cannot be generalised across populations and need to be colonyā€specific
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