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Cultivating whole-heartedness in the academy during a time of COVID : insights from/within an inter-collegial friendship

- Green, Monica, McClam, Sherie

  • Authors: Green, Monica , McClam, Sherie
  • Date: 2023
  • Type: Text , Book chapter
  • Relation: Reflections on Valuing Wellbeing in Higher Education : Reforming Our Acts of Self-care Chapter 9 p. 111-124
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  • Description: This chapter explores how we, Sherie (American) and Monica (Australian), two feminist teacher educators and collaborators, used reflective dialogic exchanges to examine our academic lives during the COVID-19 pandemic in 2020. The underpinning personal and emotional layers of our wholehearted conversations sit within our robust inter-collegial friendship, which offers us critical support and reminders about the importance of self-care/compassion in our navigation of academic complexities and obligations. The chapter is framed by three of Brene Brown’s ‘wholehearted’ provocations or prompts that we used to explore our respective lived COVID-19 experiences within the broader milieu of contemporary academia. The chapter concludes with insights about the ways in which collegial friendships contribute to academic wellbeing and self-care. © 2023 selection and editorial matter, Narelle Lemon.

Cultural landscapes : human impacts on wetlands

- Mills, Keely, Jones, Matthew, Hunt, Laura, Saulnier-Talbot, Emilie, Elias, Deevena, Nankabirwa, Angela, Lejju, Julius, Gell, Peter

  • Authors: Mills, Keely , Jones, Matthew , Hunt, Laura , Saulnier-Talbot, Emilie , Elias, Deevena , Nankabirwa, Angela , Lejju, Julius , Gell, Peter
  • Date: 2023
  • Type: Text , Book chapter
  • Relation: Ramsar Wetlands: Values, Assessment, Management Chapter 10 p. 237-258
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  • Description: Wetlands provide a wealth of ecosystem services to people, including ecological, economic, and socio-cultural benefits. However, more than 30% of freshwater species are threatened with extinction, and freshwater biodiversity is declining faster than that observed in oceans or forests. When it comes to the management of wetlands, it often occurs too late and when ecosystem services to people are at risk of being lost. It is easy to observe and monitor the recent impacts of people on wetland systems, but the changes we see today are a product of hundreds, even thousands of years of direct and indirect human impact. Without a deeper understanding of the long-term context of human impacts on wetland systems, it is impossible to manage the problems they experience (such as changes in hydrology, nutrient loading, acidification, and salinisation). Despite the 20th century being the period in which humans have exerted the greatest impact on wetland systems, it was also the period in which we developed a greater appreciation of wetlands as anthropogenically altered landscapes, and, maybe paradoxically, the benefits that accrue from healthy wetlands. Palaeolimnological approaches allow an understanding of wetland system variability over millennial scales, providing background context for anthropogenically forced change. This palaeo-perspective enables a deeper understanding of the long-term context of human impacts on wetland systems and can provide a fresh perspective when managing impacted systems. © 2023 Elsevier Inc. All rights reserved.

Cyberbullying, mental health, and lesbian, gay, and bisexual youth with disabilities : intersectionalities and environmental risks

- Gates, Trevor, Bills, Kaycee, Bennett, Bindi, Kelly, Brian

  • Authors: Gates, Trevor , Bills, Kaycee , Bennett, Bindi , Kelly, Brian
  • Date: 2023
  • Type: Text , Journal article
  • Relation: Journal of Child and Family Studies Vol. 32, no. 10 (2023), p. 3159-3166
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  • Description: Lesbian, gay, and bisexual youth with disabilities are at risk for being cyberbullied. Additionally, these risks can be compounded by other intersectional factors, such as cultural identity. Youth with multiple marginalized identities are at risk for stress, discrimination, and poor mental health outcomes as a result of bullying. However, research exploring the intersections between risk, sexual identity, and disability is sparse. In this article, we begin to address this gap in a diverse sample of lesbian, gay, and bisexual youth who have reported being cyberbullied in the Youth Risk Behavior Surveillance System. We discuss implications for child and family studies, identifying opportunities for further discussion on risk, mental health, and person-in-environment factors for lesbian, gay, and bisexual youth with disabilities. © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Cytoskeletal plakins in epithelial ovarian cancer

- Wesley, Tamsin

  • Authors: Wesley, Tamsin
  • Date: 2023
  • Type: Text , Thesis , PhD
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  • Description: The plakin family of cytoskeletal proteins play an important role in cancer progression yet are under-studied in cancer, especially ovarian cancer. These large cytoskeletal proteins have primary roles in the maintenance of cytoskeletal integrity. They are also associated with scaffolds of intermediate filaments and hemidesmosomal adhesion complexes mediating signalling pathways that regulate cellular growth, migration, invasion and differentiation, as well as a stress response. Abnormalities of plakins, and the closely related spectraplakins, result in serious pathologies of skin, striated muscle and nervous tissue. Their prevalence in epithelial cells suggests that plakins may play a role in epithelial ovarian cancer progression and recurrence. This thesis sought to explore the expression of plakin proteins, particularly plectin (PLEC), desmoplakin (DSP), periplakin (PPL) and envoplakin (EVPL) in ovarian cancer progression, comparing surgical stages, historical Silverberg histological grading and current World Health Organisation (WHO) pathological classification of ovarian tumour types. The study also investigated the potential role that the plakin family of proteins may play in regulating cancer cell growth, survival, migration, invasion and drug resistance. It highlights potential relationships between plakins and epithelial-mesenchymal transition (EMT) and relates how these interactions may affect ovarian cancer progression, chemoresistance and ultimately recurrence. This study hypothesises that the molecular changes in the expression of plakins in benign ovarian tumours compared to various grades and stages of ovarian carcinomas, as well as floating cellular aggregates (spheroids) in the peritoneal ascites microenvironment, may contribute to the progression of the disease. It also attempts to understand these crucial changes in plakin expression in response to chemotherapy treatment and relate these findings in the perspective of disease recurrence.
  • Description: Doctor of Philosophy

Data evolution governance for ontology-based digital twin product lifecycle management

- Ren, Zijie, Shi, Jianhua, Imran, Muhammad

  • Authors: Ren, Zijie , Shi, Jianhua , Imran, Muhammad
  • Date: 2023
  • Type: Text , Journal article
  • Relation: IEEE Transactions on Industrial Informatics Vol. 19, no. 2 (2023), p. 1791-1802
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  • Description: Product lifecycle management (PLM) is an effective method for enhancing the market competitiveness of modern manufacturing industries. The digital twin is characterized by a profound integration of physics and information systems, which provides a technical means for integrating multisource information and breaking the time and space barrier of communication at each link of the lifecycle. Currently, however, the application of this technology focuses primarily on the product itself and 'service-oriented' application results. There is a lack of focus on twin data and its internal evolutionary mechanisms separately. In the management of global data resources, the benefits of digital twin technology cannot be fully realized. This article applies ontology technology in an innovative manner to the field of the digital twin to increase the reusability of twin data. Initially, a four-layered ontology-based twin data management architecture is presented. Then, a three-dimensional and three-granularity unified evolution model of full lifecycle twin data is proposed, as well as its ontology model. Then, the service mode of data components at each stage of the lifecycle is defined, a knowledge-sharing plane is established in the digital twin, and a data governance method based on ontology reasoning using data components on the shared plane is proposed. The ICandyBox simulation platform is then used to demonstrate the concept of the proposed method, and future research directions are proposed. © 2005-2012 IEEE.

Data Industry

- Das, Amritam, Kolluri, Ramachandra, Mareels, Iven

  • Authors: Das, Amritam , Kolluri, Ramachandra , Mareels, Iven
  • Date: 2023
  • Type: Text , Book chapter
  • Relation: The impact of automatic control research on industrial innovation : enabling a sustainable future Chapter 2 p. 15-41
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  • Description: Digitization is at the heart of the fourth industrial revolution, Industry 4.0, and/or Society 5.0. The fourth industrial revolution evolved from the work started with control and automation of manufacturing processes in the third industrial revolution, and brings automation to bear on all engineered processes, be it physical, or administrative. Digitization promises to bring objective, evidence-based, decision-making to all aspects of society, at scale, so as to enable us to steer toward a sustainable society. Data centers embody the core information technology that supports this cyberphysical world. Ensuring that this technology (data centers) itself develops in a sustainable manner not only requires careful orchestration of the available compute, storage, and communication resources but also how we manufacture, maintain, and recycle. This chapter focuses on the former, and provides hints toward the latter. The data center story that unfolds presents itself as a microcosmos of the broader sustainability questions affecting our world, and how we can approach them. ©2024 The Institute of Electrical and Electronics Engineers, Inc.

Data-driven multi-resolution probabilistic energy and reserve bidding of wind power

- Hosseini, Seyyed, Toubeau, Jean-Francois, De Greve, Zacharie, Wang, Yi, Amjady, Nima, Vallee, Francois

  • Authors: Hosseini, Seyyed , Toubeau, Jean-Francois , De Greve, Zacharie , Wang, Yi , Amjady, Nima , Vallee, Francois
  • Date: 2023
  • Type: Text , Journal article
  • Relation: IEEE transactions on power systems Vol. 38, no. 1 (2023), p. 1-1
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  • Description: The current wind farm control schemes qualify wind power producers (WPPs) to provide balancing services in complement to energy in modern electricity markets. In this context, WPPs are responsible for real-time deviations in both energy and reserve market floors, which are settled at different time scales. WPPs should adjust their output to cope with fast wind variations, which are critical in the balancing stage. In this paper, we devise a reliable high-temporal-resolution day-ahead bidding framework for WPPs considering the ultra-short-term wind stochasticity. To that end, the model for the bidding strategy is enriched with a probabilistic constraint controlling the confidence level on reserve bids to enhance the reliability of the offered capacity. Additionally, an original Auxiliary Classifier Wasserstein Generative Adversarial Network (ACWGAN) is proposed to generate high-temporal-resolution wind speed scenarios to be embedded into the bidding framework. The numerical results firstly confirm the superiority of the proposed ACWGAN over the other GAN-based alternatives. Then, the effectiveness of the proposed data-driven method over its single-resolution counterpart and other scenario representation methods is verified regarding the minimization of the negative impact of wind variability on WPPs' profit and reliability of offered reserve bids.

Data-efficient graph learning meets ethical challenges

- Tang, Tao

Dating in the dark : vulnerable narcissism predicts inauthentic self-presentation in online dating

- Willis, Megan, Oliver, Eliza, March, Evita

  • Authors: Willis, Megan , Oliver, Eliza , March, Evita
  • Date: 2023
  • Type: Text , Journal article
  • Relation: Telematics and Informatics Vol. 81, no. (2023), p.
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  • Description: The current study investigated whether Dark Triad traits (vulnerable and grandiose narcissism, primary and secondary psychopathy, and Machiavellianism views and tactics) predicted inauthentic self-presentation whilst dating online, and whether those who reported engaging in antisocial dating behaviours were higher on Dark Triad traits, and more likely to self-present inauthentically in online dating. Online daters (N = 313) were recruited via Prolific and completed measures to assess Dark Triad traits, inauthenticity, and antisocial dating behaviours (i.e., ghosting and breadcrumbing). Vulnerable narcissism was a significant predictor of online dating inauthentic self-presentation. No other Dark Triad traits emerged as significant predictors. Online dating inauthentic self-presentation was significantly higher for those who had breadcrumbed someone. Those who had ghosted someone had significantly greater vulnerable narcissism and secondary psychopathy, and those who had breadcrumbed someone had significantly greater vulnerable narcissism and Machiavellianism views than those who had not. As previous research has demonstrated that individuals high on vulnerable narcissism are more likely to perpetrate intimate partner violence, online daters should consider evidence of inauthenticity to be ‘red flags’ for potential harm as interactions continue. Especially given the current study demonstrated those who had previously ghosted and breadcrumbed were higher on vulnerable narcissism. © 2023 Elsevier Ltd

Deep learning-based digital image forgery detection using transfer learning

- Qazi, Emad, Zia, Tanveer, Imran, Muhammad, Faheem, Muhammad

  • Authors: Qazi, Emad , Zia, Tanveer , Imran, Muhammad , Faheem, Muhammad
  • Date: 2023
  • Type: Text , Journal article
  • Relation: Intelligent Automation and Soft Computing Vol. 38, no. 3 (2023), p. 225-240
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  • Description: Deep learning is considered one of the most efficient and reliable methods through which the legitimacy of a digital image can be verified. In the current cyber world where deepfakes have shaken the global community, confirming the legitimacy of a digital image is of great importance. With the advancements made in deep learning techniques, now we can efficiently train and develop state-of-the-art digital image forensic models. The most traditional and widely used method by researchers is convolution neural networks (CNN) for verification of image authenticity but it consumes a considerable number of resources and requires a large dataset for training. Therefore, in this study, a transfer learning based deep learning technique for image forgery detection is proposed. The proposed methodology consists of three modules namely; preprocessing module, convolutional module, and the classification module. By using our proposed technique, the training time is drastically reduced by utilizing the pre-trained weights. The performance of the proposed technique is evaluated by using benchmark datasets, i.e., BOW and BOSSBase that detect five forensic types which include JPEG compression, contrast enhancement (CE), median filtering (MF), additive Gaussian noise, and resampling. We evaluated the performance of our proposed technique by conducting various experiments and case scenarios and achieved an accuracy of 99.92%. The results show the superiority of the proposed system. © 2023, Tech Science Press. All rights reserved.

Deep outdated fact detection in knowledge graphs

- Tu, Huiling, Yu, Shuo, Saikrishna, Vidya, Xia, Feng, Verspoor, Karin

  • Authors: Tu, Huiling , Yu, Shuo , Saikrishna, Vidya , Xia, Feng , Verspoor, Karin
  • Date: 2023
  • Type: Text , Conference paper
  • Relation: 23rd IEEE International Conference on Data Mining Workshops, ICDMW 2023, Shanghai, China, 1-4 December 2023, 23rd IEEE International Conference on Data Mining Workshops Proceedings p. 1443-1452
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  • Description: Knowledge graphs (KGs) have garnered significant attention for their vast potential across diverse domains. However, the issue of outdated facts poses a challenge to KGs, affecting their overall quality as real-world information evolves. Existing solutions for outdated fact detection often rely on manual recognition. In response, this paper presents DEAN (Deep outdatEd fAct detectioN), a novel deep learning-based framework designed to identify outdated facts within KGs. DEAN distinguishes itself by capturing implicit structural information among facts through comprehensive modeling of both entities and relations. To effectively uncover latent out-of-date information, DEAN employs a contrastive approach based on a pre-defined Relations-to-Nodes (R2N) graph, weighted by the number of entities. Experimental results demonstrate the effectiveness and superiority of DEAN over state-of-the-art baseline methods. © 2023 IEEE.

Design of energy storage for frequency stability in low-inertia power grid

- Akram, Umer, Mithulananthan, N, Shah, Rakibuzzaman, Alzahrani, Saeed

  • Authors: Akram, Umer , Mithulananthan, N , Shah, Rakibuzzaman , Alzahrani, Saeed
  • Date: 2023
  • Type: Text , Journal article
  • Relation: IEEE Systems Journal Vol. 17, no. 3 (2023), p. 4763-4774
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  • Description: Short-term frequency instability is one of the major concerns in power systems with high percentage of converter-interfaced renewable energy sources. Energy storage system (ESS) has proven to be a viable solution for the problem of short-term frequency instability by fast frequency response (FFR). However, the appropriate location, size, and operating strategy of ESS are the main challenges for FFR. Power injection at some buses in large grids may lead to angular separation and instability. In addition, oversizing ESS could lead to huge investments without appropriate returns and under sizing may jeopardizes grid stability. Capacity estimation of ESS for FFR considering the suitable location and overall deployment strategies are missing in the current literature for large power grids. Hence, this research proposes a technique to place and size ESS for better FFR in power grids. The proposed technique consists of two steps. In the first step, a methodology based on frequency dynamic signature (FDS) is developed to identify the most suitable location. In the second step, the required capacity of the ESS is estimated based on a step reduction iterative algorithm (SRIA). SRIA and FDS consider the complete dynamics of power system components that affect the frequency dynamics of the system. The proposed methodology is thoroughly verified for various operating conditions in IEEE 39-bus using DIgSILENT PowerFactory. © 2007-2012 IEEE.

Detection and explanation of anomalies in healthcare data

- Samariya, Durgesh, Ma, Jiangang, Aryal, Sunil, Zhao, Xiaohui

  • Authors: Samariya, Durgesh , Ma, Jiangang , Aryal, Sunil , Zhao, Xiaohui
  • Date: 2023
  • Type: Text , Journal article
  • Relation: Health Information Science and Systems Vol. 11, no. 1 (2023), p. 20-20
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  • Description: The growth of databases in the healthcare domain opens multiple doors for machine learning and artificial intelligence technology. Many medical devices are available in the medical field however, medical errors remain a severe challenge. Different algorithms are developed to identify and solve medical errors, such as detecting anomalous readings, anomalous health conditions of a patient, etc. However, they fail to answer why those entries are considered an anomaly. This research gap leads to an outlying aspect mining problem. The problem of outlying aspect mining aims to discover the set of features (a.k.a subspace) in which the given data point is dramatically different than others. In this paper, we present a framework that detects anomalies in healthcare data and then provides an explanation of anomalies. This paper aims to effectively and efficiently detect anomalies and explain why they are considered anomalies by detecting outlying aspects. First, we re-introduced four anomaly detection techniques and outlying aspect mining algorithms. Then, we evaluate the performance of anomaly detection techniques and choose the best anomaly detection algorithm. Later, we detect the top k anomaly as a query and detect their outlying aspect. Lastly, we evaluate their performance on 16 real-world healthcare datasets. The experimental results show that the latest isolation-based outlying aspect mining measure, SiNNE, has outstanding performance on this task and has promising results.

Development and validation of the feminist social identity scale

- Poll, Alex, Critchley, Christine

  • Authors: Poll, Alex , Critchley, Christine
  • Date: 2023
  • Type: Text , Journal article
  • Relation: Current psychology Vol. 42, no. 15 (2023), p. 12614-12629
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  • Description: Feminist identity is a multidimensional construct, associated with significant physical and psychological outcomes. Despite this, it has previously been largely conceptualised and measured as unidimensional. To address this limitation, we developed a multidimensional measure of feminist identity using the framework of social identity theory. A total of 1493 respondents (81.8% women, 16.6% men, 1.5% other genders) aged between 18 and 75 years ( M= 31.55, SD =11.37) completed an online survey. Following Confirmatory Factor Analysis, expert evaluation ( N = 21), and testing of the model in a separate sample ( N = 504), the Feminist Social Identity Scale (FSIS) was created. The FSIS is comprised of 36-items which measure feminist identity across 12 subscales and has excellent internal consistency, test-retest reliability, and validity indices. Latent Class Analysis revealed that the FSIS successfully distinguishes between different levels of feminist identity. The FSIS will aid future researchers to examine feminist identity as a multidimensional construct, avoiding the limitations of single construct measures.

Development of a novel behavioral sleep medicine education workshop designed to increase trainee psychologists’ knowledge and skills in insomnia management

- Meaklim, Hailey, Rehm, Imogen, Junge, Moira, Monfries, Melissa, Kennedy, Gerard, Bucks, Romola, Meltzer, Lisa, Jackson, Melinda

  • Authors: Meaklim, Hailey , Rehm, Imogen , Junge, Moira , Monfries, Melissa , Kennedy, Gerard , Bucks, Romola , Meltzer, Lisa , Jackson, Melinda
  • Date: 2023
  • Type: Text , Journal article
  • Relation: Behavioral Sleep Medicine Vol. 21, no. 6 (2023), p. 787-801
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  • Description: Objectives: Despite the clear influence of poor sleep on mental health, sleep education has been neglected in psychology training programs. Here, we develop a novel behavioral sleep medicine (BSM) education workshop, the Sleep Psychology Workshop, designed for integration within graduate psychology programs. We also examined the potential efficacy and acceptability of the workshop to upskill trainee psychologists in sleep and insomnia management. Methods: The Sleep Psychology Workshop was developed using a modified Delphi Method. Eleven trainee psychologists completing their Master of Psychology degrees (90% female, 24.4 ± 1.6 years old) attended the workshop, delivered as three, two-hour lectures (total of six hours). Sleep knowledge, attitudes, and practice assessments were completed pre-and post-intervention using the GradPsyKAPS Questionnaire. A focus group and 6-month follow-up survey captured feedback and qualitative data. Results: Trainees’ sleep knowledge quiz scores (% correct) increased from 60% to 79% pre- to post-workshop (p =.002). Trainees’ self-efficacy to use common sleep-related assessment instruments and empirically supported interventions to manage sleep disturbances increased, along with their confidence to manage insomnia (all p < .02). Participant feedback was positive, with 91% of trainees rating the workshop as “excellent” and qualitative data highlighting trainees developing practical skills in BSM. Six months post-intervention, 100% of trainees endorsed routinely asking their clients about sleep, with 82% reporting improvements in their own sleep. Conclusions: The Sleep Psychology Workshop is a potentially effective and acceptable introductory BSM education program for trainee psychologists, ready for integration within the graduate psychology curriculum. © 2023 Taylor & Francis Group, LLC.

Development of scaled boundary finite element method for geotechnical and mining engineering

- Wijesinghe, Dakshith

  • Authors: Wijesinghe, Dakshith
  • Date: 2023
  • Type: Text , Thesis , PhD
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  • Description: Numerical methods are a mature field of research and have become an increasingly important tool in mining and geotechnical engineering design practices. Although the advantages of numerical methods in aiding the analysis and solving practical engineering problems have been widely accepted and recognised, there is still a gap for further improvements. One such area is the challenge to consider the complexities of geology and the lack of stratigraphic information in the numerical model. Failure to include geological complexities may lead to overestimating the analysis parameters, such as the safety factor. These difficulties mainly manifest in the form of complex mesh generation due to the need to integrate spatial variable material parameters, capturing complex geological features, requirement of additional meshing algorithms, high human involvement, and long processing time. The scaled boundary finite element method (SBFEM) is a semi-analytical method that has potential to address these types of problems. This thesis focuses on developing the SBFEM to address these challenges so that complex geotechnical and mining engineering can be better modelled. Optimisation problems in geotechnical and mining engineering are also considered by developing a combined SBFEM-genetic algorithm framework for the design and rehabilitation of slopes. To begin with, an image-based mesh generation procedure is developed to automatically integrate the spatially variable material parameters into a computational mesh. The procedure allows the input of large data sets of geological and geometrical information in image format, and the mapping procedure enables the concatenation of any number of material parameters into a single computational mesh. The scaled boundary finite element formulation is used to discretise the governing equations of elasto-plasticity considering a Mohr-Coulomb failure criterion, which is common in soils. A shear strength reduction technique is implemented to analyse the stability of slopes in the form of an output Factor of Safety. The developed method is shown to allow routine changes in the operation of the slopes to consider geometric changes, such as backfilling, excavation and updates to geological sublets, by simply editing the digital image inputs. To extend the SBFEM to more complex geotechnical and mining engineering applications, a formulation that considers the coupled effect of pore pressure and nonlinear deformation of the soil is developed. The image-based mesh generation procedure is incorporated to integrate the geological complexities, which include heterogeneity of strate and phreatic surfaces. The developed technique is applied to study complex case studies of a tailings dam embankment construction and a coal slope rehabilitation project with a construction period. The research also considers geometric optimisation problems within the context of geotechnical and mining engineering applications. Geometric optimisation of slopes such as those in open cut mines is important to reduce the overhead operational cost involved in construction, excavation and rehabilitation backfilling, while ensuring stability at an acceptable level. This is achieved by developing a unified platform combining genetic algorithm (GA) with scaled boundary finite element formulations and image-based meshing procedures. Since the image-based mesh generation procedure is an automatic process, it enables automation of the optimisation, which is an iterative proceeding. The capabilities of this technique are demonstrated by optimising the geometric parameters of complex slopes for given safety factors and rehabilitation geometries for given safety factors during a given construction period. The image-based SBFEM analysis platform is further developed to consider geological uncertainty, such as stratigraphic interfaces and phreatic surface fluctuations, so that their effect on slope stability can be studied. The Brownian bridge statistic technique is integrated into the pre-processing module to produce these instances reflecting the ranii dom fluctuations between two intervals and generate possible geological and hydrological cross-sections. This allows unknown geological stratigraphic interface fluctuation due to a lack of sublet information to be considered. The scaled boundary finite element formulations developed in the earlier parts of this thesis are used to discretise each generated profile and analysis probabilistically. Since the mesh generation method is fully automatic, this probabilistic analysis procedure enables to analyse of a large number of possible variations and their effect on geotechnical structures with limited human intervention. Few parametric studies were conducted on slopes to study the impact of stratigraphic and phreatic surface fluctuation on the probability of failure. Finally, the hydraulic fracture commonly seen in geotechnical and mining engineering applications is considered. The phase field has the potential to model complex fracture mechanisms including crack nucleation, branching and coalescence. However, it requires a very fine mesh in order to accurately regularise the energy resulting from the creation of new crack faces. This leads to longer processing time and high computational requirements. Moreover, fracture propagation modelling with phase field models requires equilibrium iterations and hence repetitive calculation of element matrices. This research develops a scaled boundary finite element formulation with phase field model to address hydraulic fracture problems in fully-saturated poro-elastic media. Adaptive meshing refinement based on quadtree meshes is applied. This restricts the fine mesh requirement to only the regions where damage is present and avoids the need for a very fine mesh throughout the structure. Further, leveraging from the unique number of patterns in a hierarchical mesh, an appropriate scaling technique is applied to transform the relevant matrices and vectors to the physical cell in the mesh. This avoids the need for repetitive calculations during the equilibrium iterations. These features increase the efficiency of fracture modelling while reducing the computational requirement. The benchmark problems and complex fracture network problems are provided to highlight the advantage of the method.
  • Description: Doctor of Philosophy

Diatom index of Galela Lake, Halmahera, Indonesia in relation to human activities

- Soeprobowati, Tri, Saraswati, Tyas, Jumari, Jumari, Sari, Kenanga, Gell, Peter

  • Authors: Soeprobowati, Tri , Saraswati, Tyas , Jumari, Jumari , Sari, Kenanga , Gell, Peter
  • Date: 2023
  • Type: Text , Journal article
  • Relation: International Journal of Environmental Science and Technology Vol. 20, no. 7 (2023), p. 7707-7722
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  • Description: Diatoms, silicious microalgae, have been used successfully as bioindicators of water quality assessment in aquatic ecosystems. Diatoms have a degree of tolerance to the water quality and some diatoms are a good indicator for several water quality variables. Diatom indices have been developed to assess river water quality, mostly in Europe. This study aims to apply diatom indices developed in Europe for the tropical lake of Galela adjacent to residential areas influenced by human activities. Galela Lake is one of the biggest lakes in Halmahera Utara, Indonesia with its main functions being domestic water supply, irrigation, fisheries, and tourism. Human activities have impacted the area around the lake. The 90-cm and 85-cm long sediment cores were collected using a piston corer from Site 1 and 2, respectively. Sediment samples were sliced every 5 cm, separated from sediment by adding HCl and H2O2. The diatom valves were identified under a microscope with 1,000 × magnification. The water quality status of each layer was inferred with diatom indices performed using OMNIDIA software version 6.0. Forty-nine and 63 diatoms species were identified from Site 1 and Site 2, respectively. The number of species and diversity of diatoms was higher in the lower layers than those in the upper layers. The preserved diatom assemblages reflect past physical and chemical water quality. Generic Diatom Index and Specific Pollution Sensitivity Index provided the best evidence for change in Galela Lake—they integrated 70–100% of the diatom taxa from the sediment core samples. © 2022, The Author(s) under exclusive licence to Iranian Society of Environmentalists (IRSEN) and Science and Research Branch, Islamic Azad University.

Digital data and practice change: the impact of innovative web portals on user knowledge building and decision-making processes

- Murphy, Angela, Ollerenshaw, Alison

  • Authors: Murphy, Angela , Ollerenshaw, Alison
  • Date: 2023
  • Type: Text , Journal article
  • Relation: Online Information Review Vol. 47, no. 4 (2023), p. 732-748
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  • Description: Purpose: The impact of innovative web portals on users, from access to application, is gaining interest as the global call for increased data availability gains momentum. This study reports on the perceptions of portal end users about usage and access to digital data across a range of fields of practice. Design/methodology/approach: Data were collected and analysed from interviews (n = 132) and email feedback (n = 235) from end users of interoperable spatial knowledge web portals. Findings: Data reveal that users attribute importance to ease of access and applicability, and to confidence and trust in data. The acquisition of data assists with reducing knowledge silos, facilitates knowledge sharing and decision-making. Digital data portals enable the building of stronger collaborations between different groups of individuals and communities leading to improved outcomes and more positive developments across varied discipline and practice areas. Practical implications: Recommendations for developing online portals to optimise knowledge transfer and associated benefits, for users, are offered. Originality/value: By collecting extensive qualitative data drawn from the experiences of end users of digital data portals, this paper provides new insights, thereby addressing a knowledge gap in the published literature about the use of technology uptake and the application of online data for practice and industry benefit. © 2022, Emerald Publishing Limited.

Distributed formation trajectory planning for multi-vehicle systems

- Nguyen, Binh, Nghiem, Truong, Nguyen, Linh, Nguyen, Tung, La, Hung, Sookhak, Mehdi, Nguyen, Thang

  • Authors: Nguyen, Binh , Nghiem, Truong , Nguyen, Linh , Nguyen, Tung , La, Hung , Sookhak, Mehdi , Nguyen, Thang
  • Date: 2023
  • Type: Text , Conference paper
  • Relation: 2023 American Control Conference, ACC 2023 Vol. 2023-May, p. 1325-1330
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  • Description: This paper addresses the problem of distributed formation trajectory planning for multi-vehicle systems with collision avoidance among vehicles. Unlike some previous distributed formation trajectory planning methods, our proposed approach offers great flexibility in handling computational tasks for each vehicle when the global formation of all the vehicles changes. It affords the system the ability to adapt to the computational capabilities of the vehicles. Furthermore, global formation constraints can be handled at any selected vehicles. Thus, any formation change can be effectively updated without recomputing all local formations at all the vehicles. To guarantee the above features, we first formulate a dynamic consensus-based optimization problem to achieve desired formations while guaranteeing collision avoidance among vehicles. Then, the optimization problem is effectively solved by ADMM-based or alternating projection-based algorithms, which are also presented. Theoretical analysis is provided not only to ensure the convergence of our method but also to show that the proposed algorithm can surely be implemented in a fully distributed manner. The effectiveness of the proposed method is illustrated by a numerical example of a 9-vehicle system. © 2023 American Automatic Control Council.

Distribution of heavy metals in the sediments of the Gippsland Lakes, Victoria, Australia : implications for management

- Trewarn, Adam

  • Authors: Trewarn, Adam
  • Date: 2023
  • Type: Text , Thesis , PhD
  • Full Text: false
  • Description: Sediments are the ultimate repository of most contaminants that enter Australia's waterways; therefore, it is appropriate that regulatory attention addresses the risks posed by sediment contaminants. The release of elevated levels of heavy metals into the environment is a common by-product of our industrialised way of life. This problem continues to increase throughout the industrial age. We are now only beginning to understand the actual long-term burden that must be managed. Globally, estuaries are a critical focal point for civilisation and development. Owing to their strategic location and abundant resources, they have been utilised as trade hubs and industrial centres, and are often subject to intense industrial and urban development. Because estuaries accommodate large volumes of fine-grained sediments, their capacity to trap and absorb metal pollutants qualifies them as important sinks and receptacles for terrestrial, atmospheric, and oceanic metal input. Estuaries also provide important environmental services. Their protective conditions harbour a diverse range of biota, and the biogeochemical processes they accommodate play a key role in nutrient cycling and metal sequestration. However, contamination of estuaries with heavy metals is an ongoing issue, particularly as they bioaccumulate and transfer from sediments to aquatic organisms through the food chain. The Gippsland Lakes catchment has a 150-year history of a range of industrial activities, including gold and other metal mining, large open-cut brown coal mines and associated coalfired power stations, powering much of the state of Victoria, plantation forests and associated timber and paper mills, and extensive agriculture, including intensive dairy. Many of these activities are potential sources of contamination, particularly in bygone times, when environmental awareness and sound practices were less prevalent. The issue of highly elevated levels of heavy metal contaminants present within the Gippsland Lake sediments was first identified over 35 years ago. This comprehensive study looks to re-evaluate the modern surface sediments from across the Gippsland Lakes to determine, (i) If previously identified elevated Hg levels are still present or can be replicated (ii) If there are other metal contaminants that may warrant further attention, (iii) If possible, contamination is current, historical or a prolonged event (iv) If there are any natural or anthropogenic influences affecting metal concentrations within the sediments (v) What is the impact of heavy metal pollution across the Gippsland Lakes? Surficial grab and consolidated core sediment samples were collected over a period between 2015-2018 from thirteen defined locations across the Gippsland Lakes, representing the major geomorphological features of the area (e.g. major river mouths and lakes). Total metal analysis, sediment grain size, and XRF high-resolution core scanning provided insight into the overall distribution and possible risks of bulk and heavy metals present in the Gippsland Lakes sediment. Elevated concentrations of Cr, Ni, As, Cu, and Hg were found throughout the study area, exceeding the lower SQG trigger values across multiple depths and locations. Of the numerous metals initially investigated (Cr, Ni, Cu, As, Cd, Hg, and Pb) within the surface and core sediments, the findings of this study reiterated that the greatest concern was the degree of contamination and distribution of elevated levels of Hg in the western regions of the Gippsland Lakes. In addition, it highlighted the risks associated with elevated levels of Cr, Ni, and Cu. Cr and Ni have been identified at elevated levels throughout most of the western locations, Lake Victoria and Lake King, while isolated Cu is present at Paynesville. Further analysis into the metals and the interactions with the environment has defined three separate influences contributing to the elevated concentrations of heavy metals present across the study area, (i) Natural sources and cycling (Cr, Ni, and As): Concentrations of Cr, Ni, and As are likely a result of natural sources from the surrounding catchment, rather than a specific anthropogenically derived source. (i) Diffuse anthropogenic sources (Hg): The calculated pollution indices showed little to no natural influence on Hg concentrations; therefore, Hg concentrations were deemed highly likely a result of diffuse anthropogenic origin. (ii) Point source (Cu): Concentrations of Cu were generally very low throughout the study, except at a single location in an urbanised area adjacent to a commercial boatyard. This project has provided the most recent and comprehensive assessment of the presence, distribution, and leading influences on heavy metals present in the Gippsland Lakes, forming a strong foundation for informed management of the area into the future.
  • Description: Doctor of Philosophy