Showing items 21 - 40 of 13541

ADMM-based adaptive sampling strategy for nonholonomic mobile robotic sensor networks

- Le, Viet-Anh, Nguyen, Linh, Nghiem, Truong

  • Authors: Le, Viet-Anh , Nguyen, Linh , Nghiem, Truong
  • Date: 2021
  • Type: Text , Journal article
  • Relation: IEEE Sensors Journal Vol. 21, no. 13 (2021), p. 15369-15378
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  • Description: This paper discusses the adaptive sampling problem in a nonholonomic mobile robotic sensor network for efficiently monitoring a spatial field. It is proposed to employ Gaussian process to model a spatial phenomenon and predict it at unmeasured positions, which enables the sampling optimization problem to be formulated by the use of the log determinant of a predicted covariance matrix at next sampling locations. The control, movement and nonholonomic dynamics constraints of the mobile sensors are also considered in the adaptive sampling optimization problem. In order to tackle the nonlinearity and nonconvexity of the objective function in the optimization problem we first exploit the linearized alternating direction method of multipliers (L-ADMM) method that can effectively simplify the objective function, though it is computationally expensive since a nonconvex problem needs to be solved exactly in each iteration. We then propose a novel approach called the successive convexified ADMM (SC-ADMM) that sequentially convexify the nonlinear dynamic constraints so that the original optimization problem can be split into convex subproblems. It is noted that both the L-ADMM algorithm and our SC-ADMM approach can solve the sampling optimization problem in either a centralized or a distributed manner. We validated the proposed approaches in 1000 experiments in a synthetic environment with a real-world dataset, where the obtained results suggest that both the L-ADMM and SC-ADMM techniques can provide good accuracy for the monitoring purpose. However, our proposed SC-ADMM approach computationally outperforms the L-ADMM counterpart, demonstrating its better practicality. © 2001-2012 IEEE.

Advances in the discovery and development of anthelmintics by harnessing natural product scaffolds

- Herath, H. M. P. Dilrukshi, Taki, Aya, Sleebs, Brad, Hofmann, Andreas, Nguyen, Nghi, Preston, Sarah, Davis, Rohan, Jabbar, Abdul, Gasser, Robin

  • Authors: Herath, H. M. P. Dilrukshi , Taki, Aya , Sleebs, Brad , Hofmann, Andreas , Nguyen, Nghi , Preston, Sarah , Davis, Rohan , Jabbar, Abdul , Gasser, Robin
  • Date: 2021
  • Type: Text , Book chapter
  • Relation: Advances in Parasitology p. 203-251
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  • Description: Widespread resistance to currently-used anthelmintics represents a major obstacle to controlling parasitic nematodes of livestock animals. Given the reliance on anthelmintics in many control regimens, there is a need for the continued discovery and development of new nematocides. Enabling such a focus are: (i) the major chemical diversity of natural products; (ii) the availability of curated, drug-like extract-, fraction- and/or compound-libraries from natural sources; (iii) the utility and practicality of well-established whole-worm bioassays for Haemonchus contortus—an important parasitic nematodes of livestock—to screen natural product libraries; and (iv) the availability of advanced chromatographic (HPLC), spectroscopic (NMR) and spectrometric (MS) techniques for bioassay-guided fractionation and structural elucidation. This context provides a sound basis for the identification and characterisation of anthelmintic candidates from natural sources. This chapter provides a background on the importance and impact of helminth infections/diseases, parasite control and aspects of drug discovery, and reviews recent work focused on (i) screening well-defined compound libraries to establish the methods needed for large-scale screening of natural extract libraries; (ii) discovering plant and marine extracts with nematocidal or nematostatic activity, and purifying bioactive compounds and assessing their potential for further development; and (iii) synthesising analogues of selected purified natural compounds for the identification of possible ‘lead’ candidates. The chapter describes some lessons learned from this work and proposes future areas of focus for drug discovery. Collectively, the findings from this recent work show potential for selected natural product scaffolds as candidates for future development. Developing such candidates via future chemical optimisation, efficacy and safety evaluations, broad spectrum activity assessments, and target identification represents an exciting prospect and, if successful, could pave the way to subsequent pre-clinical and clinical evaluations. © 2021 Elsevier Ltd

Adverse shocks, household expenditure and child marriage : evidence from India and Vietnam

- Trinh, Truong-Anh, Zhang, Quanda

  • Authors: Trinh, Truong-Anh , Zhang, Quanda
  • Date: 2021
  • Type: Text , Journal article
  • Relation: Empirical Economics Vol. 61, no. 3 (2021), p. 1617-1639
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  • Description: Child marriage is associated with negative outcomes in regard to education, health and economic empowerment in later life. While the consequences of child marriage have been studied extensively, there has been limited discussion on the drivers of child marriage. This paper examines the impact of adverse shocks on child marriage. We use a sample of 886 girls between 12 and 18 years of age from India and Vietnam involved in the Young Lives project. The potential endogeneity problem is addressed by using rainfall deviation as the instrument. We find that in Vietnam, where bride price payment is a common practice in the event of expenditure reduction resulting from adverse shocks, a household may consider marrying off their daughter as a possible coping strategy. In contrast, in India where dowry payments are common, shocks may reduce the probability of child marriage, possibly, because a girl’s family is unable to meet the dowry requirements. These findings are robust to alternative ways of measuring child marriage, expenditure and rainfall deviation. We recommend that policies designed to reduce child marriage are considered in the context of cultural and social norms. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature.

After work? Understanding older women’s portfolio life transitions

- Taylor, Philip, Earl, Catherine, Brooke, Elizabeth, McLoughlin, Christopher

  • Authors: Taylor, Philip , Earl, Catherine , Brooke, Elizabeth , McLoughlin, Christopher
  • Date: 2021
  • Type: Text , Book chapter
  • Relation: Retiring women : work and post work transitions Chapter 7 p. 111-119
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  • Description: Chapter 7 reports qualitative interviews with older women about the pursuit of an active, fulfilling and productive retirement, and the mechanisms that promote these outcomes. Contrary to notions of the blended lifecycle, analysis reveals a stark division between paid work and retirement for many women at the same time as an ongoing commitment to socially valued and productive albeit unpaid activities that form a portfolio career. Furthermore , analysis reveals an increased sense of autonomy and control over decision making among retired women that contrasts with their experiences of paid employment.

Aggregate subgradient method for nonsmooth DC optimization

- Bagirov, Adil, Taheri, Sona, Joki, Kaisa, Karmitsa, Napsu, Mäkelä, Marko

  • Authors: Bagirov, Adil , Taheri, Sona , Joki, Kaisa , Karmitsa, Napsu , Mäkelä, Marko
  • Date: 2021
  • Type: Text , Journal article
  • Relation: Optimization Letters Vol. 15, no. 1 (2021), p. 83-96
  • Relation: http://purl.org/au-research/grants/arc/DP190100580
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  • Description: The aggregate subgradient method is developed for solving unconstrained nonsmooth difference of convex (DC) optimization problems. The proposed method shares some similarities with both the subgradient and the bundle methods. Aggregate subgradients are defined as a convex combination of subgradients computed at null steps between two serious steps. At each iteration search directions are found using only two subgradients: the aggregate subgradient and a subgradient computed at the current null step. It is proved that the proposed method converges to a critical point of the DC optimization problem and also that the number of null steps between two serious steps is finite. The new method is tested using some academic test problems and compared with several other nonsmooth DC optimization solvers. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature.

Agile ageing – A modifiable vital sign to mitigate the risk of falls in older adults?

- Ogilvie, Madeleine, Wallen, Matthew, Talpey, Scott

  • Authors: Ogilvie, Madeleine , Wallen, Matthew , Talpey, Scott
  • Date: 2021
  • Type: Text , Journal article
  • Relation: Medical Hypotheses Vol. 148, no. (2021), p.
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  • Description: Falls prevention in older adults is a targeted priority because a fall can lead to disability, institutionalisation and presents a signficant financial burden. Falls are multifactoral in nature however, impairments in both physical and cognitive functioning have been linked to their occurrence. Currently, testing and exercise training for falls prevention focuses on physical qualities such as balance and strength. Agility is a unique physical quality that couples an individuals perceptual cognitive ability with the ability to produce a quick and accurate movement. Agility is relatively well understood in a sporting context however, its application to falls prevention has been minimal. Because a fall may occur while an individual is perceiving information from the dynamic environment around them while attempting to execute a rapid and accurate movement it is hypothesised that concepts and methods used to assess and train agility in athlete populations can be use to improve practices related to the screening and training to mitigate the risk of a fall in an older adult. © 2021

AI and IoT-Enabled smart exoskeleton system for rehabilitation of paralyzed people in connected communities

- Jacob, Sunil, Alagirisamy, Mukil, Xi, Chen, Balasubramanian, Venki, Srinivasan, Ram

  • Authors: Jacob, Sunil , Alagirisamy, Mukil , Xi, Chen , Balasubramanian, Venki , Srinivasan, Ram
  • Date: 2021
  • Type: Text , Journal article
  • Relation: IEEE Access Vol. 9, no. (2021), p. 80340-80350
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  • Description: In recent years, the number of cases of spinal cord injuries, stroke and other nervous impairments have led to an increase in the number of paralyzed patients worldwide. Rehabilitation that can aid and enhance the lives of such patients is the need of the hour. Exoskeletons have been found as one of the popular means of rehabilitation. The existing exoskeletons use techniques that impose limitations on adaptability, instant response and continuous control. Also most of them are expensive, bulky, and requires high level of training. To overcome all the above limitations, this paper introduces an Artificial Intelligence (AI) powered Smart and light weight Exoskeleton System (AI-IoT-SES) which receives data from various sensors, classifies them intelligently and generates the desired commands via Internet of Things (IoT) for rendering rehabilitation and support with the help of caretakers for paralyzed patients in smart and connected communities. In the proposed system, the signals collected from the exoskeleton sensors are processed using AI-assisted navigation module, and helps the caretakers in guiding, communicating and controlling the movements of the exoskeleton integrated to the patients. The navigation module uses AI and IoT enabled Simultaneous Localization and Mapping (SLAM). The casualties of a paralyzed person are reduced by commissioning the IoT platform to exchange data from the intelligent sensors with the remote location of the caretaker to monitor the real time movement and navigation of the exoskeleton. The automated exoskeleton detects and take decisions on navigation thereby improving the life conditions of such patients. The experimental results simulated using MATLAB shows that the proposed system is the ideal method for rendering rehabilitation and support for paralyzed patients in smart communities. © 2013 IEEE. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Venki Balasubramanian” is provided in this record**

An AI-enabled lightweight data fusion and load optimization approach for internet of things

- Jan, Mian, Zakarya, Muhammad, Khan, Muhammad, Mastorakis, Spyridon, Balasubramanian, Venki

  • Authors: Jan, Mian , Zakarya, Muhammad , Khan, Muhammad , Mastorakis, Spyridon , Balasubramanian, Venki
  • Date: 2021
  • Type: Text , Journal article
  • Relation: Future Generation Computer Systems Vol. 122, no. (2021), p. 40-51
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  • Description: In the densely populated Internet of Things (IoT) applications, sensing range of the nodes might overlap frequently. In these applications, the nodes gather highly correlated and redundant data in their vicinity. Processing these data depletes the energy of nodes and their upstream transmission towards remote datacentres, in the fog infrastructure, may result in an unbalanced load at the network gateways and edge servers. Due to heterogeneity of edge servers, few of them might be overwhelmed while others may remain less-utilized. As a result, time-critical and delay-sensitive applications may experience excessive delays, packet loss, and degradation in their Quality of Service (QoS). To ensure QoS of IoT applications, in this paper, we eliminate correlation in the gathered data via a lightweight data fusion approach. The buffer of each node is partitioned into strata that broadcast only non-correlated data to edge servers via the network gateways. Furthermore, we propose a dynamic service migration technique to reconfigure the load across various edge servers. We assume this as an optimization problem and use two meta-heuristic algorithms, along with a migration approach, to maintain an optimal Gateway-Edge configuration in the network. These algorithms monitor the load at each server, and once it surpasses a threshold value (which is dynamically computed with a simple machine learning method), an exhaustive search is performed for an optimal and balanced periodic reconfiguration. The experimental results of our approach justify its efficiency for large-scale and densely populated IoT applications. © 2021 Elsevier B.V. *Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Venki Balasubramanian” is provided in this record**.

An efficient approach for SIMO systems using adaptive fuzzy hierarchical sliding mode control

- Van Nguyen, Thien, Le, Hai, Tran, Hoang, Nguyen, Duc, Nguyen, Minh, Nguyen, Linh

  • Authors: Van Nguyen, Thien , Le, Hai , Tran, Hoang , Nguyen, Duc , Nguyen, Minh , Nguyen, Linh
  • Date: 2021
  • Type: Text , Conference paper , Conference Paper
  • Relation: 2021 IEEE International Conference on Autonomous Robot Systems and Competitions, ICARSC 2021 p. 85-90
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  • Description: The paper addresses the problem of efficiently controlling a class of single input multiple output (SIMO) under-Actuated robotic systems such as a two dimensional inverted pendulum cart or a two dimensional overhead crane. It is first proposed to employ the hierarchical sliding mode control approach to design a control law, which guarantees stability and anti-swing of the vehicle when it is driven on a predefined trajectory. More importantly, the unknown and uncertain parameters of the system caused by its actuator nonlinearity and external disturbances are adaptively estimated and inferred by the proposed fuzzy logic mechanism, which results in the efficient operation of the SIMO under-Actuated system in real time. The proposed algorithm was then implemented in the synthetic environment, where the obtained results demonstrate its effectiveness. © 2021 IEEE.

An efficient hybrid system for anomaly detection in social networks

- Rahman, Md Shafiur, Halder, Sajal, Uddin, Ashraf, Acharjee, Uzzal

  • Authors: Rahman, Md Shafiur , Halder, Sajal , Uddin, Ashraf , Acharjee, Uzzal
  • Date: 2021
  • Type: Text , Journal article
  • Relation: Cybersecurity Vol. 4, no. 1 (2021), p.
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  • Description: Anomaly detection has been an essential and dynamic research area in the data mining. A wide range of applications including different social medias have adopted different state-of-the-art methods to identify anomaly for ensuring user’s security and privacy. The social network refers to a forum used by different groups of people to express their thoughts, communicate with each other, and share the content needed. This social networks also facilitate abnormal activities, spread fake news, rumours, misinformation, unsolicited messages, and propaganda post malicious links. Therefore, detection of abnormalities is one of the important data analysis activities for the identification of normal or abnormal users on the social networks. In this paper, we have developed a hybrid anomaly detection method named DT-SVMNB that cascades several machine learning algorithms including decision tree (C5.0), Support Vector Machine (SVM) and Naïve Bayesian classifier (NBC) for classifying normal and abnormal users in social networks. We have extracted a list of unique features derived from users’ profile and contents. Using two kinds of dataset with the selected features, the proposed machine learning model called DT-SVMNB is trained. Our model classifies users as depressed one or suicidal one in the social network. We have conducted an experiment of our model using synthetic and real datasets from social network. The performance analysis demonstrates around 98% accuracy which proves the effectiveness and efficiency of our proposed system. © 2021, The Author(s).

An empirical analysis of sediment export dynamics from a constructed landform in the wet tropics

- Yavari, Shahla, McIntyre, Neil, Baumgartl, Thomas

  • Authors: Yavari, Shahla , McIntyre, Neil , Baumgartl, Thomas
  • Date: 2021
  • Type: Text , Journal article
  • Relation: Water (Switzerland) Vol. 13, no. 8 (2021), p.
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  • Description: Although plot-scale erosion experiments are numerous, there are few studies on constructed landforms. This limits the understanding of their long-term stability, which is especially important for planning mined land rehabilitation. The objective of this study was to gain insight into the erosion processes in a 30 × 30 m trial plot on a mine waste rock dump in tropical northern Australia. The relationships between rainfall, runoff and suspended and bedload sediment export were assessed at annual, seasonal, inter-event and intra-event timescales. During a five-year study period, 231 rainfall– runoff–sediment export events were examined. The measured bedload and suspended sediments (mainly represented in nephelometric turbidity units (NTU)) showed the dominance of the wet season and heavy rainfall events. The bedload dominated the total mass, although the annual bedload diminished by approximately 75% over the five years, with greater flow energy required over time to mobilise the same bedload. The suspended load was more sustained, though it also exhibited an exhaustion process, with equal rainfall and runoff volumes and intensities, leading to lower NTU values over time. Intra-event NTU dynamics, including runoff-NTU time lags and hysteretic behaviours, were somewhat random from one event to the next, indicating the influence of the antecedent distribution of mobilisable sediments. The value of the results for supporting predictive modelling is discussed. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

An evaluation methodology for interactive reinforcement learning with simulated users

- Bignold, Adam, Cruz, Francisco, Dazeley, Richard, Vamplew, Peter, Foale, Cameron

  • Authors: Bignold, Adam , Cruz, Francisco , Dazeley, Richard , Vamplew, Peter , Foale, Cameron
  • Date: 2021
  • Type: Text , Journal article
  • Relation: Biomimetics Vol. 6, no. 1 (2021), p. 1-15
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  • Description: Interactive reinforcement learning methods utilise an external information source to evaluate decisions and accelerate learning. Previous work has shown that human advice could significantly improve learning agents’ performance. When evaluating reinforcement learning algorithms, it is common to repeat experiments as parameters are altered or to gain a sufficient sample size. In this regard, to require human interaction every time an experiment is restarted is undesirable, particularly when the expense in doing so can be considerable. Additionally, reusing the same people for the experiment introduces bias, as they will learn the behaviour of the agent and the dynamics of the environment. This paper presents a methodology for evaluating interactive reinforcement learning agents by employing simulated users. Simulated users allow human knowledge, bias, and interaction to be simulated. The use of simulated users allows the development and testing of reinforcement learning agents, and can provide indicative results of agent performance under defined human constraints. While simulated users are no replacement for actual humans, they do offer an affordable and fast alternative for evaluative assisted agents. We introduce a method for performing a preliminary evaluation utilising simulated users to show how performance changes depending on the type of user assisting the agent. Moreover, we describe how human interaction may be simulated, and present an experiment illustrating the applicability of simulating users in evaluating agent performance when assisted by different types of trainers. Experimental results show that the use of this methodology allows for greater insight into the performance of interactive reinforcement learning agents when advised by different users. The use of simulated users with varying characteristics allows for evaluation of the impact of those characteristics on the behaviour of the learning agent. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

An Exploratory Study on the Employers' Perceptions of ICT Graduate work-readiness

- Faisal, Nadia, Chadhar, Mehmood, Goriss-Hunter, Anitra, Stranieri, Andrew

  • Authors: Faisal, Nadia , Chadhar, Mehmood , Goriss-Hunter, Anitra , Stranieri, Andrew
  • Date: 2021
  • Type: Text , Conference paper
  • Relation: Pacific Asia Conference on Information Systems (PACIS 2021) 12th to 14th July 2021
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  • Description: Drawing on information gathered from scoping interviews with graduate recruiters and industry experts in Australia, this study extends our understanding of how employers, rather than researchers, describe the desired work-ready skills for graduate/entry level roles in the Australian information and communication technology (ICT) industry. Contrary to the developing literature on work-readiness, the findings showed that the skills which contribute to work-readiness should not be limited to field-specific knowledge, skills and cognitive skills, but that they should be extended to include affective skills or personal attributes and behaviors, such as selfefficacy, willingness to learn, disposition, tolerance and integrity. Results have practical implications for developing academic programs aimed at enhancing cognitive and affective skills among IT graduates for employment potential and successful transition into work.

An improved memetic approach for protein structure prediction incorporating maximal hydrophobic core estimation concept

- Nazmul, Rumana, Chetty, Madhu, Chowdhury, Ahsan

  • Authors: Nazmul, Rumana , Chetty, Madhu , Chowdhury, Ahsan
  • Date: 2021
  • Type: Text , Journal article
  • Relation: Knowledge-Based Systems Vol. 219, no. (2021), p. 104395
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  • Description: Protein Structure Prediction (PSP) from the primary amino acid sequence, even using a simplified Hydrophobic-Polar (HP) lattice model, continues to be extremely challenging. Finding an optimal conformation, even for a small sequence, by any of the currently known evolutionary approaches is computationally extensive and time consuming. Although Memetic Algorithms (MAs) have shown success in finding the optimal solution for PSP, no significant work on the incorporation of domain or problem specific knowledge into the search process to significantly improve their performance is reported. In this paper, we present an approach to incorporate such knowledge into the initial population to enhance the effectiveness of MA for PSP. The domain knowledge we propose to use is based on the concept of maximal ‘core’ formation by exploiting the fundamental property of the H residues to be at the core of the minimum energy optimal protein structure. A generic technique is proposed for estimating the maximal Hydrophobic core (H-core) in a protein sequence for 2D Square, 3D Cubic and a more complex and realistic 3D FCC (Face Centered Cubic) lattice models. Subsequently, the knowledge of this estimated core is incorporated in an MA. The experiments conducted using HP benchmark sequences for 2D Square, 3D Cubic and 3D FCC lattice models show that the proposed MA with the new core-based population initialization technique has superior performance to the existing methods in terms of convergence speed as well as minimal energy. © 2018 Elsevier B.V.

An Investigation of alternative factor models of Impulsivity using the UPPS-P

- Teese, Robert, Willie, Christopher, Jago, Andrew, Gill, Peter

  • Authors: Teese, Robert , Willie, Christopher , Jago, Andrew , Gill, Peter
  • Date: 2021
  • Type: Text , Journal article
  • Relation: Journal of Personality Assessment Vol. 103, no. 3 (2021), p. 324-331
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  • Description: The UPPS-P measures impulsivity as a five-factor construct (lack of premeditation, lack of perseverance, positive urgency, negative urgency and sensation seeking). Drawing on a number of theoretical considerations and alternative conceptions of impulsivity, the current study used confirmatory factor analysis (N = 1635) and multiple regression to evaluate and test alternative models comprising three, five, and a hierarchical model containing latent factors. The five factor and hierarchical models were shown to be valid and of near identical fit, whereas the three-factor model fit the data poorly. The current findings suggest that both the five factor and hierarchical models are useful applications of the UPPS-P. Depending on the purpose of future research, both models demonstrate utility in both risk assessment and treatment development. Multiple regression analysis revealed that positive urgency predicted problem gambling, which supports the predictive utility of impulsivity as a five-factor construct. While the latent factors of the hierarchical model are consistent with emerging theory, those using the UPPS-P should not overlook the unique contributions of the five factors. As the current study found meaningful predictive distinctions between positive and negative urgency, utilizing all five factors may increase measurement sensitivity and predictive utility. © 2020 Taylor & Francis Group, LLC.

An investigative study of burnout among university nurse academics in Australia

- Singh, Charanjit

  • Authors: Singh, Charanjit
  • Date: 2021
  • Type: Text , Thesis , PhD
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  • Description: The overall aims of this study were to investigate the prevalence, extent and explore the experiences of Nurse Academics in Australia in relation to job satisfaction and burnout. Over the last three decades, university teaching has become increasingly challenging and stressful; this has affected the quality of life of academics. This is evidenced by the rapidly changing working conditions and stress experienced globally among university academics Consequently, the relationship between academics and their workplace are very demanding, more stressed, followed by lack of resources and eventually leading to burnout. Burnout is defined as a psychological syndrome emerging as a prolonged response to chronic interpersonal stressors on the job. Since, the move of nurse education into the university sector in Australia in the mid 1980’s, the stress and demands placed upon Nursing Academics has risen and intensified dramatically. Although the literature is replete about the work experiences among university academics very little research has been carried out to investigate the prevalence and explore the experiences among nurse academics, particularly within Australia (Bittner, & Bechtel, 2017) in relation to occupational stress and burnout. This research study utilized a mixed methods design, specifically, the sequential explanatory model A two phased approach was utilized. In phase one 234 nurse academics completed the survey comprised of the MBI, MSQ and demographics. In phase two, 19 participants were interviewed. The conceptual framework that underpins this study is influenced by the Job- Demands Resource Model (J-DR Model). In phase one, participants were drawn from a cross section from novice to experienced academics. 50% of participants reported low levels of burnout, whilst the other 50% reported either moderate or high levels of burnout. Out of these 50% who experienced burnout about 20% of respondents experienced a high-level of burnout. Similarly, 50% of the participants experienced low levels of job satisfaction and this correlated significantly with high levels of the total burnout scores (r = -0.56). Within the qualitative component, the main themes included a lack of work life balance, incivility towards staff, increasing workloads, challenging students, lack of recognition, negative workplace culture, lack of awareness of the importance of political astuteness, and lack of leadership skills and difficulty with retention of newly appointed staff. Many participants also expressed being threatened, felling intimidated, and unfairly treated coupled with facing personalities who were driven by power struggles. Overall, there appeared to be a sense of powerlessness, that participants were relatively powerless and unable to change their lot. Although personal resilience provided a buffering effect for some of the participants and acted as a protective factor against stress and burnout it is not well understood. This research study contributes to the ongoing body of work on the experiences of nurse academics globally and gives a further insight and understanding of the personal experiences of occupational stress and burnout among Australian nurse academics. However, a few potential limitations to this study should be noted. The study sample was only selected from within Australian universities which may limit the global generalisation of the findings and it was undertaken at an only one time point. Occupational stress leading to burnout is still considered an important factor and predictor of job satisfaction and intention to leave among Australian nurse academics. Effective mentoring and leadership styles that promote a nurturing work environment, a sense of belonging, being valued, heard, and recognised, are areas of priority. Strategies and policies should be revised for greater inclusiveness, academic freedom, institutional autonomy, and a better work-life balance. Further work is needed that examines the specific types of support systems that nurse leaders could initiate to reduce job stress leading to burnout. Ongoing evaluation is crucial to ensure the appropriateness, efficacy, and effectiveness of the support systems. The findings have important global implications in terms of recruitment and retention of nurse academic.
  • Description: Doctor of Philosophy

Anabolic androgenic steroids : the shortcut to the wrong way

- Grace, Fergal

  • Authors: Grace, Fergal
  • Date: 2021
  • Type: Text , Book chapter
  • Relation: The Dynamics of Modern Rugby p. 74-83
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  • Description: The introduction of structured professionalism into all aspects of the game requires the aspirational rugby union player to possess high levels of muscle power and aerobic fitness. Anti-doping regulators became wise to these practices by adding so-called masking agents to the list of prohibited substances which is updated annually and published online. Research into the prevalence of doping of any kind in elite sport has not been conducted to date. It is quite surprising, given it is such a regular topic of debate. Yet, it is unlikely for a currently active athlete to reveal that they are doping and findings from population studies or regional samples cannot be applied to elite athletes. Randomized reporting technique is a method of protecting anonymity of the interviewee and more reliable than traditional questionnaires. Although rarely used, this shows distinct promise to estimate intentional doping in elite athletics. There have been some extraordinary advancements in gene therapy for the prevention and treatment of disease. © 2021 Taylor & Francis.

Analytical and numerical approaches to evaluate the effect of time-dependent and time-independent soil characteristics on the stability of deep excavations

- Ghadrdan, Mohsen

  • Authors: Ghadrdan, Mohsen
  • Date: 2021
  • Type: Text , Thesis , PhD
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  • Description: Excavating the ground for different purposes, such as extracting valuable materials or undertaking urban construction, may cause concerns regarding the stability of the formed slopes, which can affect the environment, the economy, and human lives. Slope stability analysis in large-scale and deep excavations such as open-pit mines is challenging due to uncertainties regarding varying material parameters, complex field conditions and lack of or insufficient data such as pore water pressure distribution, in-situ stress conditions, and discontinuities. Despite different advanced analytical and numerical slope stability techniques having been developed, slope stability analysis may produce unreliable conclusions due to these uncertainties and challenges. This study’s objective is to investigate the effect of different factors associated with slope stability through a case study of the Yallourn brown coal open pit mine in Australia. In this study, the two most common slope stability methods—the Limit Equilibrium Method (LEM) and the Finite Element Method (FEM)—were employed. A comprehensive study was conducted to determine how the generation and dissipation of Negative Excess Pore-Water Pressure (NEPWP) affect slope stability assessments. Additionally, due to the complex geological stratigraphy of the site, different scenarios for geological layering were defined and investigated for the slope stability analyses. Moreover, the sensitivity of the slope stability assessment to not only different material characteristics but also different formulations and assumptions of LEM and FEM are presented.
  • Description: Doctor of Philosophy

ANC–BNC titrations and geochemical modeling for characterizing calcareous and siliceous mining waste

- Drapeau, Clémentine, Delolme, Cécile, Vézin, Clément, Blanc, Denise, Baumgartl, Thomas

  • Authors: Drapeau, Clémentine , Delolme, Cécile , Vézin, Clément , Blanc, Denise , Baumgartl, Thomas
  • Date: 2021
  • Type: Text , Journal article
  • Relation: Minerals Vol. 11, no. 3 (2021), p. 1-16
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  • Description: Pyrite and calcite are mineral phases that play a major role in acid and neutral mine drainage processes. However, the prediction of acid mine drainage (AMD) or contaminated neutral drainage (CND) requires knowledge of the mineral composition of mining waste and the related potential for element release. This paper studies the combination of acid–base neutralizing capacity (ANC–BNC) with geochemical modeling for the characterization of mining waste and prediction of AMD and CND. The proposed approach is validated with three synthetic mineral assemblages: (1) siliceous sand with pyrite only, representing mining waste responsible for AMD, (2) siliceous sand with calcite and pyrite, representing calcareous waste responsible for CND, and (3) siliceous sand with calcite only, simulating calcareous matrices without any pyrite. The geochemical modeling approach using PHREEQC software was used to model pH evolution and main element release as a function of the added amount of acid or base over the entire pH range: 1 < pH < 13. For calcareous matrices (sand with calcite), the results are typical of a carbonated environment, the geochemistry of which is well known. For matrices containing pyrite, the results identify different pH values favoring the dissolution of pyrite: pH = 2 in a pyrite-only environment and pH = 6 where pyrite coexists with calcite. The neutral conditions can be explained by the buffering capacity of calcite, which allows iron oxyhy-droxide precipitation. Major element release is then related to the dissolution and precipitation of the mineral assemblages. The geochemical modeling allows the prediction of element speciation in the solid and liquid phases. Our findings clearly prove the potential of combined ANC–BNC experiments along with geochemical modeling for the characterization of mining waste and the assessment of risk of AMD and CND. © 2020 by the authors. *Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Thomas Baumgartl” is provided in this record**

ANSWER : generating information dissemination network on campus

- Qing, Qing, Guo, Teng, Zhang, Dongyu, Xia, Feng

  • Authors: Qing, Qing , Guo, Teng , Zhang, Dongyu , Xia, Feng
  • Date: 2021
  • Type: Text , Conference paper
  • Relation: 32nd Australasian Database Conference, ADC 2021 Vol. 12610 LNCS, p. 74-86
  • Full Text: false
  • Reviewed:
  • Description: Information dissemination matters, both on an individual and group level. For college students who are physically and mentally immature, they are more sensitive and susceptible to unnormal information like rumors. However, current researches focus on large-scale online message sharing networks like Facebook and Twitter, rather than profile the information dissemination on campus, which fail to provide any references for daily campus management. Against this background, we propose a framework to generate the information dissemination network on campus, named ANSWER (cAmpus iNformation diSsemination netWork gEneRation), based on multimodal data including behavior data, appearance data, and psychological data. The construction of the ANSWER is listed as four steps. First, we use a convolutional autoencoder to extract the students’ facial features. Second, we process the behavior data to construct a friendship network. Third, heterogeneous information is embedded in the low-dimensional vector space by using network representation learning to obtain embedding vectors. Fourth, we use the deep learning model to predict. The experiment results show that ANSWER outperforms other methods in multiple feature fusion and prediction of information dissemination relationship performance. © 2021, Springer Nature Switzerland AG.