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Agitation in Dementia in Australian Residential Aged Care Facilities- Prevalence, Presentation and Systematic Data Coding before and during the COVID-19 Pandemic
No full textBackground: Agitation is one of the most prevalent and distressing neuropsychiatric symptoms associated with dementia, being the third most frequent behavioural disturbance in persons with dementia (PWD). Its occurrence in residential aged care facilities (RACFs), affecting approximately 30% - 70% of residents with dementia, has profound implications not only for resident well-being but also for staff workload, caregiver burden, and the development of evidence-based care policies. Despite its clinical relevance, limited data were available on the precise prevalence and manifestations of agitation in Australian RACFs, particularly during the COVID-19 period with significant systemic stress.Aim: This doctoral research aimed to elucidate the epidemiological landscape of agitation in dementia within Australian RACFs in New South Wales before and during the COVID-19 pandemic, providing insights that could inform future interventions and policy responses. It addressed two primary research questions: 1) What were the prevalence rates and the most common manifestations of dementia-related agitation in Australian RACFs before the onset of COVID-19? and 2) How did these prevalence rates and symptom presentations evolve during the pandemic? By answering these questions, the study sought to identify patterns of change in overall dementia prevalence and the range, frequency, and intensity of agitation behaviours, thereby identifying areas that warrant targeted interventions and resource allocation.Methods: With institutional ethics approval, the study collected de-identified electronic health records (EHRs) of 3,528 care recipients residing in 40 Residential Aged Care Facilities (RACFs) in New South Wales (NSW), Australia, covering the period from 2019 to 2021. Traditional epidemiological methods, such as structured surveys or manual chart reviews, are often time-consuming and may fail to capture contextual detail. To address these limitations, this research employed a rule-based natural language processing (NLP) algorithm to extract agitation symptoms from unstructured EHRs. These free-text records offered real-time, nuanced accounts of resident behaviours, enabling a more detailed and scalable analysis. Compared to standard approaches, the NLP method revealed a broader range and higher frequency of agitation symptoms, capturing subtleties and behavioural patterns. The research design comprised four distinct phases. (1) First, a rigorous data pre-processing stage was undertaken to standardise and further de-identify all records, ensuring compliance with ethical standards for privacy and data protection. (2) Second, a rule-based NLP algorithm was developed and evaluated to detect key indicators of dementia-related agitation within unstructured text. The algorithm’s framework rested on a carefully curated lexicon of agitation-related keywords, synonyms, and contextual phrases, which were iteratively refined through pilot testing and expert validation. (3) Third, symptom extraction was conducted via Python-based scripts that identified and categorized agitation episodes according to thematic clusters, such as physical aggression, verbal disruption, and emotional distress. This systematic grouping allowed for quantitative analyses of symptom frequency, co-occurrence, and temporal trends. (4) Finally, descriptive statistics, Chi-square tests, and paired t-tests were performed using IBM SPSS Statistics (Version 28) to address the core research questions and assess changes over time.Results: The noteworthy findings include that before the pandemic, 44.2% of female residents and 43.9% of male residents had a documented dementia diagnosis. Among this group, agitation was notably high, affecting 78.6% of females and 79.6% of males with dementia. A total of 59 distinct agitation symptoms were identified, indicating a considerable heterogeneity in agitation manifestations. These include 64.5% of physical behaviours, such as resisting care, wandering, pacing, and pushing; 38.5% of verbal disruption, including shouting, complaining and the use of profane language; and 9.3% of emotional distress, e.g., expressions of frustration or anxiety.During the COVID-19 pandemic, an overall decline was observed in the total number of documented agitation symptoms, which dropped from 59 in 2019 to 39 in 2020 (-33.9%) and further to 34 in 2021 (-12.82%) (p The mortality rate among residents with dementia increased significantly in 2020, from 51.66% in 2019 to 64.66% in 2020, before declining to 43.99% in 2021. The first year of the pandemic also witnessed a higher transfer rate of residents with dementia to hospitals, suggesting a potential exacerbation of underlying health conditions or the cumulative toll of pandemic-related disruptions on care delivery. These findings could inform the allocation of clinical resources and care strategies aimed at mitigating adverse health outcomes during future crises.Conclusion: This doctoral research piloted novel, data-driven methodologies, particularly rule-based NLP and machine learning pipelines, to characterise the prevalence and changing patterns of dementia-related agitation in RACFs. By analysing free-text nursing notes, the project addresses long-standing methodological gaps, and offers a scalable approach for ongoing surveillance of neuropsychiatric symptoms of dementia. The results supported prior international findings that approximately 30 to 35% of PWD exhibit agitation in RACFs while also identifying specific symptom categories that increased in prevalence during the pandemic. These insights have important implications for clinical practice, as RACFs, clinicians, and policymakers can use the findings to develop targeted interventions tailored to the most prevalent or distressing behaviours. Moreover, they highlight the necessity of proactive planning and resource allocation to manage agitation effectively, particularly during periods of high risk, such as pandemics.Future research should extend these longitudinal observations beyond the pandemic period, exploring whether altered agitation patterns persist over time or revert to baseline levels. Studies should also investigate the interplay between staffing levels, care strategies, and environmental modifications in mitigating agitation severity.</p
Exploring Facial Expression Recognition using Complex Emotional Stimuli
No full textFacial expressions are a powerful tool used to communicate social and emotional signals to an observer. Accurately decoding these signals enables the receiver to understand the situation and respond appropriately. An appropriate behavioural response leads to positive interpersonal communication and social cohesion. However, if a receiver fails to accurately recognise the signal they may respond in an inappropriate manner, which can lead to socially awkward or potentially dangerous interactions.Emotion recognition research is critical to understanding the cognitive processes involved in expression recognition as well as the role of facial expressions in social cognition. However, there is a significant lack of empirical research that explores expression recognition beyond the basic emotions – happy, sad, fear, anger, surprise, and disgust. Little is known about how humans perceive and recognise complex expressions that are important to more nuanced social interactions. To address these gaps in knowledge, this thesis focused on facial expressions of compound emotions. A compound emotion is a type of complex emotion that is comprised of multiple basic emotions and is signalled using a combination of physical characteristics from each expression.</p
Application of Wire-arc Directed Energy Deposition Process in the Al-Zn-Mg-Cu-Sc-Zr Alloys
No full textWire-arc directed energy Deposition (WA-DED) process is a combination of arc and wire feeding additive manufacturing technology including either the gas tungsten arc (GTA) or the gas metal arc (GMA) process. And this technology has been applied in the aerospace manufacturing industry to reduce the time of product development and “buy-to-fly” ratios. In recent years, many researchers and scientists have begun to apply WA-DED technology to manufacture different aluminum alloy components.The high-strength Al-Zn-Mg-Cu (7xxxx series) aluminum alloy is called as a non-weldable aluminum alloy due to their high susceptibility of hot cracking during the welding process. Traditional processing technologies, such as casting, also face many challenges such as poor casting performance and extremely high buy-to-fly ratio during the manufacturing process of large-scale Al-Zn-Mg-Cu high-strength aerospace structural parts. Therefore, the feasibility of Al-Zn-Mg-Cu aluminum alloys in WA-DED applications is very necessary to be verified. However, the existing Al-Zn-Mg-Cu aluminum alloy filler wires are not suitable for WADED process due to their high susceptibility to hot cracks, which is the major challenge for 7xxxx series aluminum alloy applied in WA-DED.In this thesis, a novel Al-Zn-Mg-Cu-Sc-Zr aluminum alloy wire with ultra-high strength and excellent hot-crack resistance has been successfully prepared by optimizing the composition of Al-Zn-Mg-Cu alloying elements and adding appropriate amounts of inoculants Sc and Zr elements during the smelting process. And then, the thin-wall components without any hot cracks were successfully fabricated by using cold metal transfer (CMT) process. Several key steps including smelting process, wire process, deposition parameters, heat treatment processes were shown in this study. The microstructure and precipitated second phases under the as-deposited and different heat-treated conditions were discussed in detail. The average ultimate tensile strength (UTS), yield strength (YS) and elongation of the T6 heat-treated sample were measured to be 618 ± 4 MPa, 542 ± 6 MPa and 5.7%, respectively. The outstanding tensile strength successfully exceeded 600MPa.However, WA-DED technology is based on the fusion welding process, and porosity defects are inevitable during the manufacturing process of WA-DED aluminum alloys due to the significant difference in the solubility of hydrogen in the liquid and solid phases of aluminum alloys. Meanwhile, there are also lack of fusion (LOF) defects and severe grain boundary segregation during the solidification process. All these defects will seriously affect the mechanical properties of WA-DED aluminum alloys, especially the fatigue property which is always considered as the final criterion for the engineering application of a new material. In order to effectively address pore defects, LOF defects as well as solve the grain boundary segregation issue in WA-DED aluminum alloys, an innovative hybrid WA-DED + interlayer friction stir processing (FSP) method was applied to successfully fabricate thick-walled Al-Zn-Mg-Cu-Sc-Zr aluminum alloy component with enhanced strength-ductility and fatigue properties. The porosity defects caused by the WA-DED process were effectively addressed in the FSP effective zone, and the original continuous grain boundary eutectic structures were broken up and dispersed along the grain boundaries. The grains were also further refined with an average size of about 1.1 ± 0.2 μm in the stirring zone (SZ). After T6 heat treatment. The manufactured alloy achieves isotropy in mechanical properties, with a tensile strength and elongation of 645 ± 8 MPa and 12.6 ± 0.5%, respectively. The fatigue performance is significantly improved to 250 MPa. This method provides a feasible approach for eliminating defects and achieving isotropy in aluminum alloys during the additive manufacturing process.</p
“I’m getting it!”: how parents describe change following attendance at mindfulness-enhanced behavioural parent training
No full textObjective: Many parents feel overwhelmed and seek professional assistance in response to their child’s behaviours. Mindfulness-enhanced parenting programs offer an increasingly popular alternative to the traditional gold standard behavioural parent training (BPT). This study explored parents’ descriptions of change following attendance at a mindfulness-enhanced behavioural parent training group program (MeBPT). Our aim was to examine how mindfulness and behavioural components are featured in parents’ change narratives. Method: Utilising a nested sampling design, semi-structured interviews were conducted with parents (n = 9) of 3–12-year-old children, who attended the program 6 months earlier. Transcripts were analysed using reflexive thematic analysis. Identified themes were triangulated with qualitative comments from the broader sample of post-group parent evaluations (n = 266) and relevant theory. Results: Four themes characterised parents’ change narratives: noticing the struggle, being a mindful parent, trying to implement behavioural strategies, and the importance of the relationship. Parents integrated both mindfulness and behavioural principles in their change narratives, varied in which components were most highly valued, and reported mixed success in applying behavioural parenting strategies. Themes supported the construct validity of existing mindful parenting models and measures. Conclusions: Integrating mindfulness components within BPT programs appears to be valued by parents and may represent the next evolution in parenting interventions.</p
Fibrinogen-binding M-related proteins facilitate the recruitment of plasminogen by <i>Streptococcus pyogenes</i>
No full textGroup A Streptococcus (GAS) M-related proteins (Mrp) are dimeric α-helical coiled-coil cell-wall-attached proteins. During infection, Mrp recruit human fibrinogen (Fg) to the bacterial surface, enhancing phagocytosis resistance and promoting growth in human blood. However, Mrp exhibit a high degree of sequence diversity, clustering into four evolutionarily distinct groups. It is currently unknown whether this diversity affects the host–pathogen interactions mediated by Mrp. In this study, nine Mrp sequences from the four major evolutionary groups were selected to examine the effect of sequence diversity on protein–protein interactions with Fg. Negative staining transmission electron microscopy confirmed that Mrp are fibrillar proteins measuring between 45.4 and 47.3 nm in length, and mass photometry confirmed the ability of Mrp to form dimers. Surface plasmon resonance was used to evaluate the affinity of each Mrp for Fg. All Mrp studied bound to Fg via Fragment D (FgD) with nanomolar affinity. Previous studies have linked the acquisition of plasminogen (Plg) by GAS Fg-binding M proteins to tissue destruction and excessive stimulation of the human inflammatory response during infection. Our findings show that Mrp provide an alternative mechanism for Plg recruitment, as Plg binding by Mrp was significantly enhanced following pre-incubation with Fg. These data suggest that Mrp play an important role in GAS host–pathogen interactions. However, further studies are necessary to investigate the relevance of these findings in vivo.</p
Specialised Software and Protocols Enabling Patient Specific Treatment Using Microbeam Radiation Therapy
No full textCancer is the leading cause of premature death in 57 countries, including Australia. Radiotherapy plays an essential role in modern cancer treatment, with more than half of all patients diagnosed with cancer receiving radiotherapy as part of their treatment.Continued improvements in radiotherapy over the past 40 years have seen the five year survival rate in Australia increase from 48% to 71%. However, this improvement has not been realised uniformly in all types of cancer. For example, cancers of the brain have proven particularly difficult to treat, with survival rates increasing only marginally from 21% to 22% in the past 30 years. The maximum tolerable dose to healthy tissue limits the ability to deliver a therapeutic dose of radiation to the certain tumours, such as brain tumours.Research has demonstrated the potential to preserve healthy tissue in deep-seated tumours, without impacting tumour control probability, by utilising high-dose rates and spatially fractionated radiation fields. Firstly, radiation therapy delivered at very high dose rates (≥ 40 Gy/s) has been shown to increase the radiation tolerance of healthy tissue. This is a phenomenon known as the ‘FLASH’ effect. In addition, spatial fractionation of the treatment field has also been shown to preserve healthy tissue. To preserve spatial fractionation on the micron scale, and mitigate the effect of motion in biological samples, it is necessary to deliver the treatment at a high-dose rate. The combination of high-dose rates and spatial fractionation on the micron scale is known as Microbeam Radiation Therapy (MRT). With its excellent healthy tissue sparing properties, MRT has great potential for application of the treatment of cancers previously thought to be untreatable.MRT is in the pre-clinical development phase, only possible at the small number of specialist facilities, called synchrotrons, that are capable of producing radiation fields with the specific beam properties needed for effective delivery of MRT. Limited access to these facilities impedes progress. Additionally, there are many medical physics challenges that need to be addressed to ensure the delivery of safe and accurate MRT treatment. In particular, further work is needed to develop treatment planning capabilities, along with specialised dosimetry and quality assurance protocols. Only then will sufficient solutions be in place to provide confidence in treatment delivery.This thesis adopts a holistic, patient-centred approach to these pre-treatment planning processes. A patient specific imaging protocol, applicable for pre-clinical and clinical trials of MRT, is developed. Optimisation of patient imaging is a critical precursor to clinical trials. It is necessary for accurate tumour identification and contouring, to inform dose simulations, and to enable accurate patient alignment prior to treatment.In addition, a new software package, DoseMRT has been developed and validated for use in synchrotron generatedMRT. DoseMRT addresses many of the limitations of current treatment planning systems for MRT. The system enables simulation of treatment plans using individualised Computed Tomography (CT) datasets with customised beam geometry, contouring of the target volume and calculating dose volume histograms. DoseMRT utilises an industry gold standard software toolkit (Geant4) and the Monte Carlo Method to simulate synchrotron radiation production and dose deposition in complex heterogeneous phantoms with the ability to perform absolute dose calculations. Finally, DoseMRT is validated against experimental dosimetry, with a high degree of accuracy, and its capability to perform absolute dosimetry without the need for experimental calibration is explored. The system overcomes many of the key limitations of currently available treatment planning systems, and has been instrumental in the continued development of MRT.These advancements in the pre-treatment patient planning process supports continued progress toward harnessing the therapeutic potential of MRT.</p
Structural performance of inter-module connections in cold-formed steel structures
No full textVarious inter-module connections have been studied recently to enhance the constructability and performance of steel-framed modular buildings. Although these connections provide benefits, they do not fully leverage the potential advantages of modular construction, such as quick assembly and reusability. Moreover, designers usually face extra challenges in connecting modules when they are subjected to high loads because of their small thickness, issues of weldability, requirements for reusability and local buckling.This research developed three innovative and sustainable connections between shear walls in cold-formed steel modular construction. A series of 62 full-scale experimental tests have been conducted using square hollow sections (SHS) to examine connection capacity and failure mechanism. FEA numerical investigations have also been carried out by analysing 14 models using ABAQUS. It was found that the proposed connections achieve strength requirements to withstand wind lateral loads in mid-rise buildings. They also proved to possess important characteristics like ease of installation, temporary stability during construction, reusability and having a pleasant appearance.</p
Enhancing new graduate nurses and midwives person-centredness during the COVID-19 pandemic: The influence of a person-centred model of clinical supervision
No full textPerson-centred healthcare is a shared expectation of healthcare organisations and healthcare professionals. However, achieving this in everyday practice has been challenging. Reasons for this include the need for healthcare staff to understand the meaning of person-centredness and then apply it to practice, a need to develop cultures that value and support person-centredness for care givers, care receivers and their significant others (named person-centred practice), and the recent pandemic.Person-centredness should be embedded into every strategy at every level of the healthcare system. The Person-centred Practice Framework (McCance & McCormack, 2021) provides a structure to support the operationalisation of person-centredness in practice. The framework helps develop a shared language and understanding between the macro level and those caring at the clinical interface. It supports the understanding of the enablers and barriers to support person-centred practice.Reflection is promoted as a key attribute of a person-centred practitioner and an expectation of nurses and midwives by regulatory bodies. Clinical supervision, as a reflective process, is proposed to enhance person-centred care, yet it lacks empirical evidence. Considering these factors, this study aimed to develop, deliver and evaluate a person-centred model of clinical supervision (named C.A.R.E.) to enhance the person-centredness of new graduate nurses and midwives (graduates) during the COVID-19 lockdown.</p
Competing axes of power in the global plastics treaty: Understanding the politics of progress and setbacks in negotiating a high-ambition agreement
No full textHeadlines in December 2024 proclaimed the “collapse” and “failure” of United Nations plastics treaty negotiations in Busan, South Korea. This is, however, an overly simplistic and pessimistic portrayal. Progress on less contentious issues was made, and the meeting was adjourned with a commitment to continue negotiating in 2025 on the basis of the “Chair’s text.” Significantly, at the closing plenary, a majority of states voiced support for a “high-ambition” treaty covering the full life cycle of plastics, drawing clear red lines on the necessity of legally binding measures to phase out hazardous plastics, regulate chemicals in plastics, and finance just transitions. Delegates from developing countries such as Rwanda, Panama, and Mexico were especially steadfast in demanding an “ambitious” treaty to end plastic pollution, including in marine ecosystems. Yet there were also setbacks, as multiple, intersecting axes of pro-plastics power – comprising loose alliances of petrostates and business interests profiting from rising plastics production – sought to thwart high-ambition obligations. Industry actors lobbied against stringent commitments and endeavored to narrow the treaty’s scope to downstream waste management. Petrostates such as Russia and Saudi Arabia, meanwhile, stalled discussions and bracketed high-ambition text. Divisions between developing and developed countries also emerged over the appropriate financing mechanism. Despite this turbulence, achieving a strong treaty remains possible. But this will require strengthening the high-ambition axis of power, enhancing transparency and accountability, and ensuring the meaningful inclusion of rights holders, local communities, and civil society.</p
Estimating the parameters of ocean wave spectra using Bayesian methods
No full textWind-generated ocean waves are a natural occurrence, transforming wind energy into waves on the sea surface. The spectral density function of these waves describes the distribution of wave energy across different frequencies. Estimating parameters such as wave height, peak frequency, and bandwidth is crucial due to the varied nature of these parameters influenced by location, time, and weather conditions. Parametric and nonparametric techniques have been utilised for estimation, with the Joint North Sea Wave Project (JONSWAP) model being widely employed as a parametric form.Bayesian computational methods can be used to estimate highly non-linear and non-Gaussian wave models by employing the Markov chain Monte Carlo (MCMC) method. However, to date, there is no available Bayesian approach to fit ocean wave models that provide full uncertainty quantification. By applying Bayesian methods to estimate ocean wave spectra parameters, we can improve the accuracy and reliability of wave predictions and enable better decision-making in offshore engineering, coastal management, and maritime operations. The main contributions of this thesis are:Efficient Bayesian inference using the Hamiltonian Monte Carlo (HMC) is proposed for estimating Pierson-Moskowitz (PM) and JONSWAP models,A novel mixture of ocean wave spectra model is proposed to fit multi-modal ocean wave spectra,The uncertainty for significant wave height (Hs) is taken into account.To validate the effectiveness and accuracy of our methods and wave models, we employ prior predictive checks and Simulation-Based Calibration (SBC). We apply our proposed method to real data from ocean wave buoys in New Zealand and Western Australia.</p