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In-process 4D reconstruction in robotic additive manufacturing
No full textRobotic additive manufacturing using a cold spray deposition head attached to a robotic arm can deposit material in a solid state with deposition rates in kilogrammes per hour. Under such a high deposition rate, the complicated interplay between the robot's motion, gun standoff distance, spray angle, overlapping, and the interaction of supersonic powder particles with a growing structure could cause overabundance or deficiency of material build-up. Over time, the accumulation of these discrepancies can negatively affect the overall shape and size of the final manufactured object. In-process spatio-temporal 3D reconstruction, also known as 4D reconstruction, could allow for early detection of deviations from the design, thus providing the opportunity to rectify at an early stage, making the process more robust, efficient and productive. However, in-process model reconstruction is challenging due to the dynamic nature of the scene (e.g. sensor and object relative movements), the three-dimensional growth of a time-varying build object, the textureless nature of build surfaces, and its computational complexity. We propose a real-time, in-process 4D reconstruction framework for free-form additive manufacturing processes, such as cold spray that deals with a real-time dynamic and evolving scene built by incremental deposition of materials. In our approach, temporal point clouds from three cameras are acquired and segmented to extract the region of interest (build object). The subsequent multi-temporal and multi-camera registration of the segmented 3D data is addressed by combining geometrically constrained Fiducial marker tracking and plane-based registration without drift accumulation. Finally, the registered point clouds are fused via voxel fusion of growing parts to reconstruct the 3D model of the object with smoothened surfaces. The proposed solution is deployed and verified in a robotic cold spray cell with different test scenarios and shape complexities.</p
Extended RBC phenotype matching reduces the incidence of alloimmunisation in patients with warm autoimmune haemolytic anaemia (wAIHA)
No full textBackground: Warm autoimmune haemolytic anaemia (wAIHA) involves autoantibodies destroying red blood cells, often necessitating transfusions. Alloimmunisation, the formation of antibodies against non-self RBC antigens, complicates future transfusions. This review evaluates whether extended RBC phenotype matching reduces alloimmunisation compared to standard ABO and Rh matching.
Methods: Databases (PubMed, Scopus, Cochrane Library and Google Scholar) were searched for studies (2014–2024) on wAIHA patients comparing basic, partial, and full extended RBC phenotype matching. Eligible data were analysed using a random-effects model to assess alloimmunisation risk reduction. Manual searches were performed using relevant references.
Results: Ten studies, both retrospective and prospective, were included. Basic matching (ABO and Rh) had the highest alloimmunisation rate at 32.8% (95% CI, 13.3%–52.2%; I² = 95.79%, p < 0.001). Partial matching (Rh and Kell) reduced rates to 22.5% (95% CI, 10.4%–34.6%; I² = 49.57%, p = 0.046), while full matching lowered it to 11.6% (95% CI, 4.5%–18.7%; I² = 73.65%, p = 0.001). Despite heterogeneity, results consistently showed extended matching reduced alloimmunisation.
Conclusion: Extended RBC phenotype matching significantly lowers alloimmunisation risk in wAIHA patients, particularly in chronically transfused cases. However, the variability across studies highlights the need for standardised transfusion practices and further research to confirm these results through larger, randomised controlled trials.</p
Getting together without water: Lipid self-assembly in polar non-aqueous solvents
No full textSelf-assembled structures have numerous applications including drug delivery, solubilization, and food science. However, to date investigations into self-assembled structures have been largely limited to water, with some additives. This limits the types of assemblies that can form, as well as the accessible temperature range. Non-aqueous, polar solvents such as ionic liquids and deep eutectic solvents offer alternative self-assembly media that can overcome many of these challenges. These novel solvents can be designed to support specific types of assemblies or to remain stable under more extreme conditions. This review highlights recent advances in the field of self-assembly in polar non-aqueous solvents. Here we quantify the contribution of certain solvent properties such as nanostructure and solvent cohesion to lipid self-assembly. While this field is still relatively new, preliminary design rules are emerging, such as increasing hydrophobic regions leading to decreasing solvent cohesion, with a consequent reduction in lipid phase diversity. Ultimately, this review demonstrates the capacity for solvent control of lipid assemblies while also drawing attention to areas that need further work. With more systematic studies, solvents could be explicitly designed to achieve specific lipid assemblies for use in target applications, such as cargo delivery to particular cell types (e.g. cancerous), or triggered release under desired conditions (e.g. pH for release on wound infection).</p
Bodies Beyond the Skin: Queer and Camp Inquiries of Australian Landscape Photography
No full textPhotography has historically assisted the colonial project through the capture, categorisation, and narrativisation of ecologies as ‘space.’ This practice-led research project investigates how landscape photography has privileged hierarchical masculinist assumptions and seeks to problematise this schema by using ‘queer’ and camp methodologies to ‘betray,’ ‘pervert,’ ‘fail,’ and ultimately ‘unsettle’ existing narratives of Australian landscape via photography.
If photography and visual representations of the land are complicit in reinforcing and reproducing colonial systems, then how can practitioners work their way out of this entanglement? Can photography—a colonising practice—be used to unsettle narratives and visual representations of the Australian landscape through a practice of queering? To address these questions, this research project presents a constellation of creative and written works that were conceived through generative cycles of making, research, and reflection through queer praxis.
In this project I interrogate settler visions of ‘nature’ and employ the concept of ‘queering’ as a methodology for unsettling the formulations of the Australian landscape through a range of photographic practices, including photobooks, video, sculpture, and installation. Additionally, I explore camp strategies of humour, parody, and appropriation to highlight current insufficiencies in the representation of landscape photography, as well as to formulate unusual ways to engage the body. By performing landscape photography within an expanded practice, this dissertation argues how photography slips into multiple disciplines, making it a suitable vector for complex concepts such as the ‘Australian landscape’ and the myths we have attached to it through its various representations. Through an expansive range of image-based creative works, this practice-led PhD contributes to the field of photography through its coalescence of queer and decolonial theory alongside landscape and photography studies to instigate experimental ways of seeing and conceptualising ‘nature’ and ‘landscape.’</p
Development of 2D Material Conformal Coating Technology for Advanced Photonics Devices
No full textIntegrating 2D materials with optoelectronic devices offers significant potential due to
their exceptional properties and biocompatibility, paving the way for advanced optical
fibre sensors. Graphene and its derivatives, mainly graphene oxide (GO) and reduced
graphene oxide (rGO), stand out for their superior characteristics and scalability.
Additionally, MXene materials offer exceptional electrical conductivity, high mechanical
strength, and excellent chemical stability.Integrating MXene and GO coatings with
optoelectronic devices still faces challenges such as achieving uniform, high-quality
coatings on various substrates, managing material stability over time, and addressing
issues with scalability for large-scale production. Achieving strong adhesion and
compatibility across various device architectures remains challenging. This thesis
addresses these issues by optimising GO-Poly (diallyldimethylammonium chloride)
(PDDA) and MXene-PDDA coating processes and incorporating artificial intelligence (AI)
into fibre Bragg grating (FBG) fabrication. AI-driven automation and femtosecond laser
precision enhance FBG fabrication quality and reliability, promising advancements in
telecommunications, energy storage, and intelligent materials. Additionally, this thesis
explores the integration of GO conformal coating with FBG, laying the groundwork for
future advancements in combining GO coatings with FBG fabrication techniques. The
aim is to further enhance sensing performance, improve the durability and stability of
sensors under diverse environmental conditions, and enable more precise real-time
detection. Moreover, this research aims to simplify fabrication while preserving high
sensitivity, thereby broadening the range of applications and enhancing the
effectiveness and versatility of sensor technologies across various industries.
This doctoral thesis is structured into four main parts:
1 Development and characterization of GO coating technology: the research
optimises GO-PDDA self-assembly processes to enhance coating quality and scalability
on diverse substrates, including fibres and plastics. GO coatings are characterised by
mechanical strength and thermal stability, which are crucial for improving FBG
performance. This research introduces an optimised GO-PDDA self-assembly process
that significantly enhances the surface smoothness of GO coatings, with 3D
profilometer analysis revealing a 73% improvement in the flatness of 120nm GO films
prepared using an ultrasonic bath. These advancements result in superior mechanical
strength and thermal stability, which are essential for enhancing the performance of
FBGs.
Traditional GO coating methods often need help with consistent quality and limited
scalability when applied to different materials. The improved GO-PDDA self-assembly
process addresses these issues by achieving a more uniform and robust coating. This
enhancement effectively resolves problems related to surface roughness and
performance variability across diverse substrates, thereby ensuring excellent reliability
and effectiveness of FBGs in a wide range of applications. The scalability of this coating
process is demonstrated by its successful application to diverse substrates, including
optical fibres and plastics, while maintaining high-quality coating performance.
2 Development and characterization of MXene coating technology: this thesis
investigates MXene-PDDA self-assembly films, focusing on their properties, such as
enhanced electrical conductivity and mechanical strength, which are crucial for
improving FBG applications in energy storage and advanced sensing technologies.
Additionally, I explore the nonlinear optical absorption (NOA) properties of 2D layered
MXene films integrated onto Si₃N₄ waveguides. This research advances the development
of MXene-PDDA self-assembly films by focusing on their exceptional electrical
conductivity and mechanical strength. Additionally, the study explores the NOA
properties of 2D layered MXene films integrated onto Si₃N₄ waveguides, providing
insights into their effectiveness in photonic applications.
3 Fabrication and characterization of FBGs: the thesis highlights femtosecond laser
direct writing as a significant advancement in FBG fabrication. It offers precise control
over grating parameters and enables customised designs for various optical fibre
applications. It demonstrates the technique's versatility by exploring different functional
forms like uniform, tilt, gaussian, sinc, and sine functions.
This research advances femtosecond laser direct writing for fabricating FBGs, offering
exceptional precision in grating parameter control. The technique customizes FBG
designs using different functional forms, such as uniform, tilt, gaussian, sinc, and sine
functions, allowing for tailored optical properties for specific applications. Unlike
conventional methods, which struggle with precise control and customization, this
approach provides a more flexible and accurate solution for FBG production. Based on
the systematic investigation of these apodization functions, the sinc function provides
the most significant improvement in Side-Lobe Suppression Ratio (SLSR), with an
enhancement of 16 dB compared to the uniform FBG. The tilt and gaussian functions also
show substantial improvements of 14.57 dB and 14 dB, respectively. These
improvements in SLSR lead to better signal quality and higher sensitivity, particularly
when different coating materials are applied. This research demonstrates that choosing
the right apodization function not only enhances grating performance but also
significantly improves the sensitivity of FBGs, making them more effective in optical
sensing applications.
4 AI-enhanced FBG fabrication: This research introduces an advanced AI model
integrated into FBG fabrication systems, which automates fibre core recognition and
positioning. This innovation significantly improves the accuracy and efficiency of FBG
manufacturing by enabling precise alignment and automated adjustments.
Traditional FBG fabrication techniques often struggle with manual adjustments and
alignment, leading to inconsistencies and inefficiencies. For example, expert manual
alignment requires 1 to 2 minutes per adjustment, while the AI-powered system reduces
the alignment time to 40-50 seconds. The adoption of AI technology addresses these
challenges by automating critical aspects of the process, resulting in more accurate and
consistent fabrication. This approach enhances the quality of FBGs and increases
production speed and reliability.
In conclusion, this doctoral thesis significantly advances the fields of GO and MXene
coating technologies, FBG fabrication, and AI-enhanced manufacturing. By optimizing
GO-PDDA and MXene-PDDA self-assembly processes, the research improves coating
quality and scalability, while enhancing mechanical strength, thermal stability, and
electrical conductivity. Additionally, the thesis explores the integration of GO conformal
coating with FBG, establishing a foundation for future developments that aim to enhance
sensing performance. This includes improving the durability and stability of sensors in
various environmental conditions and enabling more precise real-time detection.
Furthermore, the research seeks to simplify fabrication processes without sacrificing
sensitivity, thereby broadening the range of applications and providing more effective,
versatile sensor technologies for multiple industries. The versatility of femtosecond laser
direct writing in FBG fabrication is also highlighted, allowing for precise control over
grating designs tailored for diverse optical applications. Finally, integrating AI into FBG
fabrication systems transforms production by automating fibre core recognition and
positioning, leading to enhanced accuracy and efficiency.</p
A Study of Seating Suspension System Vibration Isolation Using a Hybrid Method of an Artificial Neural Network and Response Surface Modelling
No full textA reliable prediction model can greatly contribute to the research of car seating system vibration control. The novelty of this paper lies in the development of a hybrid method of an artificial neural network (ANN) and response surface methodology (RSM) to predict the peak seat-to-head transmissibility ratio of a seating suspension system and to evaluate its ride comfort for different seat design parameters. Additionally, this method can remove the experimental design of the RSM model. In this paper, four seat design parameters are selected as input parameters and arranged using the central composite design method. The peak transmissibility ratio from seat to head at 4 Hz is chosen as the response target output value. To illustrate this hybrid method, the response target output value of the peak transmissibility ratio is calculated from the frequency response of a five-degrees-of-freedom (5-DOF) lumped-parameter biodynamic seating suspension model. The input design parameters and the response target output values are used to train an ANN to establish the relationship between the seat design parameters and the peak transmissibility ratio. At the same time, the input design parameters and the response target output values predicted by the ANN are used to develop the relationship between the seat design parameters and the peak transmissibility ratio using the response surface method and linear regression models. The hybrid of the ANN and response surface methods makes the planning or design of experiments not essential. The hybrid model of the ANN and response surface method is more accurate and convenient than a linear regression model for the study of seating system vibration isolation.</p
Unraveling the Effects of Cationic Peptides on Vesicle Structures: Insights into Peptide–Membrane Interactions
No full textAntimicrobial resistance is a pressing global health issue, with millions of lives at risk by 2050, necessitating the development of alternatives with broad-spectrum activity against pathogenic microbes. Antimicrobial peptides provide a promising solution by combating microbes, modulating immunity, and reducing resistance development through membrane and intracellular targeting. PuroA, a synthetic peptide derived from the tryptophan-rich domain of puroindoline A, exhibits potent antimicrobial activity against various pathogens, while the rationally designed P1 peptide demonstrates enhanced antimicrobial activity with its specific composition. This paper investigates the concentration-dependent effects of these cationic peptides on distinct types of vesicles representing strong-negative bacterial cell membranes (S-vesicles), weak-negative bacterial cell membranes (W-vesicles), and mammalian cell membranes (M-vesicles). To investigate the interactions between the peptides and vesicles, small-angle neutron scattering experiments were conducted. The cationic peptides, PuroA and P1, interact with S-vesicles through electrostatic interactions, leading to distinct effects. PuroA accumulates on the vesicle surface, increasing Rcore and Rtotal, aligning with the carpet model. P1 disrupts the vesicle structure at higher concentrations, consistent with the detergent model. Neither peptide significantly affects W-vesicles, emphasizing the role of charge. In uncharged M-vesicles, both peptides decrease Rcore and Rtotal and increase tshell, indicating peptide insertion and altered bilayer properties. These findings provide valuable insights into peptide-membrane interactions and their impact on vesicle structures. Furthermore, the implications of these findings extend to the potential development of innovative antimicrobial agents and drug delivery systems that specifically target bacterial and mammalian membranes. This research contributes to the advancement of understanding peptide-membrane interactions and lays the foundation for the design of approaches for targeting membranes in various biomedical applications.</p
Exploring Surgical Patient Engagement A Critical Realist Perspective
No full textAbstract
Our healthcare system is transitioning from disease-centred to patient-centred models, prioritising individual needs, preferences, and values. This shift emphasises the importance of patient engagement for high-quality, responsive care that aligns with the needs and values of the individual. Such engagement not only promotes personalised care but also empowers patients to play an active role in managing their health, leading to improved health outcomes, increased patient satisfaction, and a more sustainable healthcare system.
In perioperative care, active patient engagement promises to enhance recovery experiences. Despite its importance, there is a gap in research focused on surgical patient engagement, indicating a need for enhanced understanding of engagement strategies in this critical area of healthcare.
Underpinned by a critical realism, this thesis explores the perceptions, beliefs, and values of different stakeholders involved in surgical patient engagement. This perspective acknowledges these viewpoints as subjective yet significant interpretations of reality. Despite the potential fallibility of these viewpoints, they are valued as crucial insights into the shared meanings and norms that underpin patient engagement in surgical contexts. It allows for a nuanced exploration of the underlying mechanisms and social dynamics that shape engagement practices, fostering a deeper understanding of how these stakeholders collectively contribute to the patient engagement process, thereby enriching the understanding of its multifaceted nature. A mixed-methods approach is adopted, combining a mixed-methods systematic review from the perspective of patients and qualitative focus groups with clinicians, to provide a comprehensive exploration of patient engagement. This methodology allows for an in-depth exploration capturing both research discourse and clinical insights.
The project aimed to (1) review existing research on how surgical patient engagement is conceptualised and operationalised during the perioperative period; and (2) explore the associated barriers and facilitators from the perspectives of clinicians involved in the perioperative period. The study was structured in two phases.
Phase 1 systematically reviewed the literature on conceptualisations and operationalisations of surgical patient engagement. Searches in MEDLINE, EMBASE, CINAHL, and the Cochrane Library identified English-language studies focusing on surgical patient engagement during the perioperative period. The selection and assessment of studies were done by three reviewers using the Joanna Briggs Institute mixed methods review framework. Data analysis involved reflexive thematic analysis for qualitative studies and qualitisation of quantitative data. A total of 29 studies were included, comprising both qualitative (n=14) and quantitative (n=15) research. Sample sizes ranged from 7 to 1,315 participants. Every study included patient perspectives, some also included other stakeholders, predominantly nurses. Only 11 studies (38%) provided an explicit definition of patient engagement, revealing a conceptual void. Analysis identified four main themes related to operationalisation: provision of information, communication, decision-making, and action-taking, which were interrelated and mutually dependent. The review highlights the nuanced, multifaceted nature of surgical patient engagement. It underscores the need for more theoretically sound and comprehensive research to better understand surgical patient engagement.
Phase 2 consists of qualitative focus groups with surgeons and anaesthetists. Despite initial intentions to include a broader range of medical professionals, recruitment was limited due to logistical and pandemic-related constraints. Purposive sampling was used. Two focus groups were conducted—one in-person and another online. Data analysis followed Braun and Clarke’s thematic analysis framework, emphasising the identification of key themes related to the facilitation and barriers of patient engagement, with an emphasis on reflexivity and transparency to maintain analytical integrity. Participants included 11 healthcare professionals, comprising five surgeons and six anaesthetists with 45.5% (n=5) female and 54.5% (n=6) male. Data resulted in identification of barriers to surgical patient and engagement, and strategies to overcome these barriers. The barriers to patient engagement include 'Patient interest and commitment', 'Time constraints', 'Language barriers and cultural differences', and 'Lack of Trust'. To address these challenges, the clinicians recommended several strategies: adopting a 'Collaborative interdisciplinary approach', 'Provision of information and education', and 'Fostering relationships with interpersonal skills'. This study contributes to a nuanced understanding of surgical patient engagement from the perspectives of healthcare professionals, highlighting both barriers to and opportunities to facilitate engagement.
The findings from both phases of the study suggest a consensus on the conceptualisation of patient engagement, while highlighting interpretative differences. Both phases highlight the importance of providing information and education to patients, the importance of clinicians' communication skills, the necessity of shared decision-making, and patient’s capability for active engagement. Moreover, another key recommendation from focus groups included the role of a surgical coordinator to improve communication and continuity of patient care, underscoring the need for a multidisciplinary approach in perioperative engagement.
This study defines surgical patient engagement as a multi-faceted, dynamic collaboration between patients and clinicians across all surgical phases, aimed at empowering patients to take an active role in their recovery. It proposes a conceptual framework that underscores continuous engagement and the need for responsiveness to feedback and adaptability in engagement strategies, as well as a collaborative interdisciplinary approach that includes patients as key decision-makers. The core elements of the framework include Meeting Needs, Education, Empowerment, and Trust (MEET), which address patient factors, provision of information, fostering patient autonomy, and building a rapport and trust for effective engagement. The framework emphasises interdisciplinary collaboration, personalisation, and technology to improve surgical outcomes and overall care quality by engaging patients in their health journey.
This research acknowledges several limitations: the exclusion of grey literature and non-English publications in the systemic review may have limited the findings, although the review included a diverse international selection. Specific keyword use, focusing solely on major surgeries, and absence of subgroup analyses could limit the breadth and applicability of findings. The focus groups consisted of a small sample size of 11 participants from a single hospital and by not including nurses, due to constraints of the pandemic, leading to uncertainty on data saturation. However, the nurses’ views on patient engagement have been represented in the systematic review. Despite these challenges, the research provides valuable insights into perioperative surgical patient engagement and contributes to the field's theoretical and practical knowledge base.
This research offers a nuanced understanding of surgical patient engagement and introduces a conceptual framework for systematic operationalisation of surgical patient engagement. It offers insights to guide clinicians and researchers in creating effective patient engagement strategies, particularly during the complex perioperative phase. This framework serves as a foundation for systematic study of patient engagement strategies for researchers, leading to the formulation of evidence-based practices. Clinically, it promotes a more empathetic, responsive, and personalised approach to healthcare, aiming to develop more targeted patient engagement strategies. The focus on continuous engagement, education, empowerment, and trust can enhance surgical care quality, creating a dynamic where patients are well-informed and active in their treatment, thus improving health outcomes and the efficiency of healthcare delivery. These insights not only advance our conceptual understanding but also have practical implications for training healthcare professionals, emphasising patient engagement as a pivotal element of effective health management.</p
A Survey of Advanced Border Gateway Protocol Attack Detection Techniques
No full textThe Internet’s default inter-domain routing system, the Border Gateway Protocol (BGP), remains insecure. Detection techniques are dominated by approaches that involve large numbers of features, parameters, domain-specific tuning, and training, often contributing to an unacceptable computational cost. Efforts to detect anomalous activity in the BGP have been almost exclusively focused on single observable monitoring points and Autonomous Systems (ASs). BGP attacks can exploit and evade these limitations. In this paper, we review and evaluate categories of BGP attacks based on their complexity. Previously identified next-generation BGP detection techniques remain incapable of detecting advanced attacks that exploit single observable detection approaches and those designed to evade public routing monitor infrastructures. Advanced BGP attack detection requires lightweight, rapid capabilities with the capacity to quantify group-level multi-viewpoint interactions, dynamics, and information. We term this approach advanced BGP anomaly detection. This survey evaluates 178 anomaly detection techniques and identifies which are candidates for advanced attack anomaly detection. Preliminary findings from an exploratory investigation of advanced BGP attack candidates are also reported
Improving Learning Outcomes in Modelling Sequence Diagrams Through Scaffolding Approach and Immediate Feedback
No full textSequence diagrams, which visually depict the interaction between objects, are critical components of modern software development. Sequence diagrams enable experienced developers to create more effective and sustainable solutions by detecting and avoiding potential issues during the design stage. However, learning sequence diagrams places a heavy cognitive load on students, who must (i) ensure consistency with class diagrams, (ii) check the validity of dispatched messages, (iii) meet the goals stated in use cases, and (iv) justify their design decisions taking into account qualitative attributes. No attempt appears to have been made to produce a pedagogical framework capable of providing ongoing diagnoses and support for students.
The aim of this thesis is to find novel ways to engage and support diverse incoming students to learn how to model. The first research task is addressed by the proposed rule-based framework, which is able to give immediate feedback by capturing the interdependencies between class and sequence diagrams. The second research task is addressed by tracking the knowledge state and by incorporating the design by contract technique. The design by contract precondition ensures necessary knowledge elements are present at each entity before a message can be dispatched. The third research task is addressed by ensuring the created and submitted sequence diagrams meet use case goals. This is achieved by capturing the postconditions and by incorporating an Artificial Intelligence (AI) planning technique into the framework. The final research task is addressed by providing qualitative feedback and marks based on qualitative metrics, designed to ensure maintainability, reusability and performance. A gamification strategy allowing multiple submissions with the goal of improving design scores, helped to motivate and engage students.
The proposed pedagogical framework was based on a scaffolded approach to reduce the cognitive load on novices by requiring them to focus only on one aspect at each intermediate stage. A mixed methods design including qualitative and quantitative data was used to evaluate the proposed approach. The approach was validated by conducting experiments across different cohorts of students studying software engineering courses. Experimental results were collected through pre- and post-tests, survey results, expert interviews and data recorded by the tool. These sources revealed that the novel pedagogical framework substantially improved learning outcomes. The greatest improvement was noted among stragglers, who were the main target group of this thesis. The proposed framework is suitable for large classes and online teaching because the feedback and marks are automatically generated. The framework can also be adapted to other areas where diverse students face cognitive overload