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Metal-organic framework-based nanocomposite membrane for formaldehyde adsorption, antibacterial and food packaging
No full textMembranes with outstanding performance fit for increasingly challenging environment are in high demand. ZIF-67/PAN fiber film with polyacrylonitrile (PAN) as the matrix and ZIF-67 nanoparticles as functional material was prepared by solution blow spinning. The phase composition and internal structure characteristics of the membrane were characterized, and its properties toward potential applications were measured. The high surface area and porosity of the membrane exhibited excellent adsorption performance and surface activity, conducive to the adsorption of formaldehyde molecules and PM2.5 particles. The membrane also demonstrated excellent air permeability, thermal dissipation and anti-ultraviolet efficiency, ideally for application in air filtration and food packaging. The effective combination of ZIF-67 and PAN contributed to the antibacterial capability, anti-ultraviolet performance, air filtration, formaldehyde adsorption and degradation, and food packaging. The membrane exhibited robust antibacterial properties with a hypostatic rate against both Staphylococcus aureus and Escherichia coli higher than 99 %. The production process of fiber membrane is facile, highly productive, and the solution blow spinning technology is scalable, indicating that the reported nanocomposite strategy is promising for potential applications in modern human health and industrial fields.</p
Designing for Multiple Stakeholders: Integrating Value Sensitive Design and Multimodal Sensing in Location-Based Services A Mixed Methods Approach for an E-Scooter Case Study
No full textWith the widespread adoption of technology location-based services (LBS) that use curated information based on the real-time location of users or mobile objects have become increasingly common. Notable examples include ride-sharing platforms like Uber, Lyft and Didi, home-sharing platValue sensitive design, location-based services, direct and indirect stakeholders, e-scooter sharing service, mixed-methodforms such as Airbnb and HomeExchange, and location-driven social media platforms like Instagram and Explorest. These platforms combine the features of location-aware systems with the complexities of engaging multiple stakeholders. They involve direct stakeholders, those who directly use the system, and indirect stakeholders, who are affected by the platforms' operations despite not using them directly.Two key characteristics of LBS make their design particularly challenging. First, these platforms inherently interact with physical spaces. Unlike purely digital services, LBS rely on location data and engage with the physical environment, creating shared spaces among stakeholders. This frequently leads to conflicts in stakeholder values, as it can be difficult to anticipate the reaction of indirect stakeholders, understand their concerns, and integrate their values into system design. Second, the effectiveness and reception of LBS vary significantly across different geographic and cultural contexts. The way these platforms are adopted and regulated differs based on local laws, cultural norms and user preferences. As a result, stakeholder values and the associated tensions differ between locations. Human-centred design is a broadly discussed area in human-computer interaction (HCI), that emphasises that effective design stems from a deep understanding of users. Among the various human-centred approaches, value sensitive design (VSD) specifically accounts for both direct and indirect stakeholder values. VSD posits that values emerge from interactions between users and technology. This thesis introduces additional heuristics into the VSD framework to address the unique characteristics of LBS. The applicability and effectiveness of this approach is demonstrated through a case study on e-scooter sharing services in Melbourne, Australia. First, to understand locality-based usage patterns and the features that influence e-scooter sharing services, we conducted a spatial and temporal data analysis. Using real-time e-scooter trip data collected over three months, we examined the factors influencing e-scooter usage by developing machine learning models and buffer analysis techniques. Our multi-resolution modelling approach, which considers different time frames and spatial zones, helped us identify the dynamics and heterogeneity of spatial and temporal features associated with micro-mobility trips. Second, to investigate stakeholder perspectives and values, we adopted a qualitative research approach guided by VSD. Given its ability to account for the values of both direct and indirect stakeholders, VSD provided a suitable framework for our study. To address the two characteristics of LBS described above, we propose Location-Aware Value Sensitive Design (LA-VSD), an extension of the VSD framework introduced through three additional heuristics. The proposed framework guides designers to identify and prioritise stakeholders through local space-sharing scenarios, adapt empirical methods to capture values and tensions in context, and embed values across both digital and physical layers of the service. Through a case study of e-scooter sharing in Melbourne, we demonstrate how LA-VSD enables more grounded, context-aware, and actionable design of LBS. Third, to analyse e-scooter rider behaviours and their interactions with other road users, we conducted a naturalistic study. Multi-modal data was collected from 23 participants navigating a predefined route that included a pedestrian-shared path, a cycle lane, and a roadway. Using bike computers, eye-tracking glasses and cameras we captured data on speed, gaze movements and rider behaviour. Our findings highlight the unique challenges faced by e-scooter riders. These challenges include the difficulty in keeping pace with faster-moving cyclists and motor vehicles when the speed of shared e-scooters is capped, the risks associated with using hand signals for turning, and the limited acceptance of e-scooters by other road users in mixed-use spaces. These insights underscore the need for infrastructure design that aligns with user behaviour and for targeted safety measures that enhance the integration of e-scooters into different urban environments. Finally, recognising the challenges of notifying other road users about an e-scooter’s presence in shared spaces, we designed audio and visual alerts in a participatory design workshop. We then evaluated these alerts in an outdoor setting using a Wizard of Oz (WoZ) study which collected video recordings, eye movement data, and self-reported survey responses from pedestrians and cyclists exposed to the different types of alert. Findings from self-reported ratings indicate that voice and bell alerts have statistically significant higher ratings in visibility, safety, communication and acceptance than continuous sound and flashing lights. Cyclists found these alerts more distracting than pedestrians. Based on these insights, we provide design recommendations for future e-scooter alert systems. In summary, this thesis makes several contributions toward the inclusive design of location-based services. We propose Location-Aware Value Sensitive Design, an extended framework that adds three heuristics tailored to the distinctive characteristics of LBS. Using the e-scooter sharing service as a use case, we demonstrate the applicability and value of these heuristics through a series of empirical studies involving multiple stakeholders. Additionally, we created and then made publicly available datasets capturing real-world e-scooter dynamics, including rider behaviour and interactions with other road users, to support future research in micro-mobility modelling. Overall, we believe this research will provide a significant contribution to multi-stakeholder-centred design that accommodates both direct and indirect stakeholder perspectives.</p
Nanodiamond Modification of Kevlar Fabric to Enhance Surface Activity and Eliminate PFAS
No full textAramid fibers such as Kevlar are frequently used in protective applications due to their mechanical strength and thermal stability. However, the low surface reactivity of aramid has limited its functional modifications, particularly for enhancing water resistance, an increasingly important requirement in protective textiles. This study presents a surface functionalization approach that imparts durable hydrophobicity to Kevlar fabric. Polyacrylic acid (PAA) was used as a coupling agent to improve the adhesion of nanodiamonds (ND), including detonation (DND) and hydroxylated forms (ND‐OH), to the fiber surface. Subsequent treatment with n‐dodecyl tri‐methoxy silane generated a robust hydrophobic finish. The PAA‐DND‐silane system exhibited the highest water contact angle and retained its performance after repeated washing and abrasion cycles. The enhancement in hydrophobicity was attributed to nanostructured roughness promoting a Cassie‐Baxter wetting regime. Crucially, the modification did not compromise the fabric's flexibility, although it reduced the air permeability 50%. This scalable strategy offers a pathway to multifunctional aramid textiles that meet the stringent demands of modern protective gear.</p
Lives and Works (sic)
No full textResearch background. Lives and Works (sic) was exhibited at BLINDSIDE, Melbourne, 30 April–24 May 2025 (opening 1 May). It presented printed editions by Adam Cruickshank who then invited Abbra Kotlarczyk, Am Stuart, Benjamin Woods, Carolyn Craig, Darcey Bella Arnold, Xingyu Echo Li, Joseph Grigely, Mitchel Cumming, Peter Tyndall, Scott Mitchell, Stuart Geddes, Zenobia Ahmed and Dennis Grauel to contribute further material, all prepared, printed and constructed by Cruickshank. Gallery text frames the project as extending “the notion of the solo show into an always-already collaborative experience.” The exhibition was approved as a solo presentation; Cruickshank then deliberately reframed it as a curatorial project that seeks to ‘diffuse authorship’.Research contribution. The project operationalised reading and distribution as methods. Tear-off pads were designed to circulate beyond the gallery: visitors could remove pages, making dissemination – rather than accumulation – the formal exhibition logic. A concise curatorial score linked discrete editions while preserving each contributor’s specificity; by the exhibition's conclusion, most of it had been removed. The project advances publishing‑as‑method by showing how authorship, circulation and value can be reconfigured through a tactic of diffused authorship and through the positioning of distribution as the main method of interaction with the work.Research significance. BLINDSIDE is a long‑running artist‑run initiative established in 2004 in the Nicholas Building. Exhibitions are selected through a competitive annual open call, with proposals reviewed by the Artistic Directors and it provides paid opportunities, in this case an artist fee was paid. Presentation within this peer‑led program situates the project in a recognised, competitive context within Melbourne’s art ecology, with public documentation providing accessible evidence of process and outcomes.</p
Solving the 3D Multi-Objective Dynamic AUV Path Planning Problem Based on the Improved Morphin-Altruistic NSGAII Algorithm
No full textAs ocean exploration delves deeper, autonomous underwater vehicles (AUVs) have become essential tools for ocean missions. Dynamic path planning seeks to find an optimal path for AUVs from a start point to the target while avoiding collisions with moving obstacles. However, current dynamic path planning faces several challenges such as three-dimensional environments and multi-objective problems, resulting in impractical solutions. To address these challenges, this paper proposes improved Morphin-Altruistic Nondominated Sorting Genetic Algorithm II (ANSGAII). More specifically, contributions presented in this paper are as follows: (1) An improved Three-dimension multi-objective path planning model is proposed, which incorporates depth considerations and simultaneously optimises for path length, safety, and smoothness. An enhanced path collision detection mechanism is also designed. (2) The ANSGAII, inspired by altruism in animal populations, is proposed to enhance optimisation efficiency and reduce computational load by transferring update opportunities from the weak to the strong individuals. (3) The best path is selected based on weighted criteria, and the Morphin algorithm is utilised to timely get around dynamic dangers. Experimental results demonstrate that the paths generated by the improved Morphin-ANSGAII algorithm better balance the objectives and effectively help AUVs avoid dynamic obstacles.</p
Integrated Photonic Cavities with High Quality Factors in the Mid-Infrared
No full textThe mid-infrared wavelength range of the electromagnetic spectrum is attracting
a lot of interest due to its high potential for sensing applications, for example breath
analysis in health care or air quality monitoring for environmental applications. However,
currently the devices for the generation of these wavelengths are expensive and
bulky, confining their use to research laboratories. Away to overcome this it to utilize
the photonic integration circuit technology to shrink down the devices to the size
of a finger nail. There are several components necessary to realize such an on-chip
integrated sensing system. One key component is a cavity, which traps light on-chip.
It can be used to build a mid-infrared light source as well as to enhance the sensitivity
of the system. Based on this interest, the goal of the thesis is to develop such cavities
of very high quality in the mid-infrared. The quality of howwell the light is trapped is
expressed by the quality factor. Hence, we want to obtain the first on-chip integrated
cavity with a high quality factor and working over a wide wavelength range in the
mid-infrared.</p
Kalman Filter-Based Epidemiological Model for Post-COVID-19 Era Surveillance and Prediction
No full textIn the post-COVID-19 era, the dynamic spread of COVID-19 poses new challenges to epidemiological modelling, particularly due to the absence of large-scale screening and the growing complexity introduced by immune failure and reinfections. This paper proposes an AEIHD (antibody-acquired, exposed, infected, hospitalised, and deceased) model to analyse and predict COVID-19 transmission dynamics in the post-COVID-19 era. This model removes the susceptible compartment and combines the recovered and vaccinated compartments into an “antibody-acquired” compartment. It also introduces a new hospitalised compartment to monitor severe cases. The model incorporates an antibody-acquired infection rate to account for immune failure. The Extended Kalman Filter based on the AEIHD model is proposed for real-time state and parameter estimation, overcoming the limitations of fixed-parameter approaches and enhancing adaptability to nonlinear dynamics. Simulation studies based on reported data from Australia validate the AEIHD model, demonstrating its capability to accurately capture COVID-19 transmission dynamics with limited statistical information. The proposed approach addresses the key limitations of traditional SIR and SEIR models by integrating hospitalisation data and time-varying parameters, offering a robust framework for monitoring and predicting epidemic behaviours in the post-COVID-19 era. It also provides a valuable tool for public health decision-making and resource allocation to handle rapidly evolving epidemiology.</p
Compact Optical Systems for Biosensing and Computing: From Skin Health Monitoring to Diffractive Neural Networks
No full textSpectroscopy is a powerful analytical technique offering unique capabilities in detecting and differentiating between chemical compositions with high specificity. This versatility relies on light-matter interaction to determine the optical properties of a specific analyte such as absorption, emission or scattering. Based on these properties, the presence, concentration or even molecular structure of target analytes can be determined. Various applications in biosensing, ranging from health monitoring to food safety, have leveraged the specificity of spectroscopy techniques to accurately detect and quantify specific biomolecules. Optical biosensing techniques are widely applied in detecting anomalies in the skin due to its non-invasive nature. Variations in skin pigmentation, redness (erythema), and autofluorescence are valuable indicators of skin health, aiding in the detection of sun overexposure and potentially cancerous lesions. Despite their potential, current techniques are restricted to benchtop technologies, limiting access to only clinicians. Moreover, optical measurements from complex biological environments contain overlapping spectral data that affects accuracy. Machine learning aids in improving detection accuracy, however, existing methods involve acquiring optical signals followed by computer-based processing. This thesis explores a miniaturized all-optical machine learning hardware to streamline optical signal processing and integrates the functionality of benchtop optical detection systems for measuring changes in skin optical properties into a point-of-care (PoC) device. There are three projects centred around the application of narrowband spectroscopy for biosensing, aiming to develop advanced optical diagnostics for widespread use. The first project includes the development of a PoC device to detect changes in skin after continuous sun exposure. Prolonged and frequent excessive UV exposure elevates the risk of developing skin cancer. The signs of excessive UVA and UVB exposure are indicated by changes in skin pigmentation and erythema. A miniaturized optical sensor was developed to detect small changes in pigmentation and erythema based on four wavelengths: 405 nm, 572 nm, 650 nm and 700 nm. Monte Carlo simulations were performed to study the light penetration depth into skin tissue relative to wavelength and the source-to-detector distance. These results were used to design the placement of the micro-LED and photodiode to measure different chromophores in the skin. The device response and sensitivity were validated using phantom skins developed to mimic the optical properties of different skin phototypes. The device achieved a minimum detection of 5% change in pigmentation across all phototypes and detected erythema changes in lighter skin tones, using a signal-to-noise ratio threshold of 2. This initial prototype enables the transition from benchtop skin colorimetry measurements to a PoC device. The potential application of this work can be extended to monitoring the conditions of chronic skin diseases and wound health monitoring. The second project focuses on non-invasive monitoring of skin lesions based on skin autofluorescence for early skin cancer detection. One of the indicators between a benign and malignant skin lesion is the reduction in autofluorescence intensity in the latter. Neovascularization and epithelium thickening contribute to the reduction in autofluorescence for malignant lesions. In this work, an optical sensor based on SMD micro-LEDs and RGB photodiodes were developed to measure the changes in autofluorescence at skin lesions relative to healthy skin. Building upon the optical skin phantom developed in the second project, Alexa Fluor 350 and Alexa Fluor 594 were integrated to mimic the autofluorescence of skin. The device successfully detected subtle changes in autofluorescence associated with pigmentation and erythema. By integrating autofluorescence and reflectance measurements, it effectively distinguished pigmentation-related changes from erythema across all phototypes, achieving a signal-to-noise ratio of 3.8. This work can potentially be used to monitor changes in skin lesions quantitatively at home to track the development of skin lesions over time, assisting physicians to make informed decisions before performing a skin biopsy. The third project relates to developing broadband diffractive neural networks (DNNs) for visible wavelength classification. DNNs are a type of optical machine learning hardware that modulates optical inputs based on diffraction to provide an inference. In this work, models were trained in the simulation to classify three wavelength pairs comprised of 561 nm, 671 nm, and 785 nm. Within the simulation, the input to the DNNs were point spread functions of two different wavelengths modelled after a microscope objective. These input fields were modulated by the diffractive layers toward the target detector for classification. After the training, these models were fabricated into single and two-layer DNNs using direct laser writing to achieve sub-micron features. The highest classification accuracy observed was over 90% for the model classifying 561 and 785 nm. This work demonstrated the ability of 3D-printed DNNs to classify different wavelengths at the speed of light, enabling potential integration with PoC devices to screen the presence of target analytes based on optical extinction bands at specific wavelengths.</p
Safe: Outdoor Participation by CALD women: research findings summary
No full textOutdoor participation in Victoria provides significant recreational, health, and economic benefits. Yet the scope and impact of the outdoor industry are not well understood, especially for CALD communities. Furthermore, the diverse terminology and academic disciplines associated with the outdoors suggest a fragmented understanding of outdoor experiences. In this report, outdoor participation has been holistically defined as including both structured activities as organized by a body or organization (e.g., professionally organized wilderness expeditions, guided adventure tourism experiences, and educator-led camping trips) as well as unstructured activities stemming from participants’ intrinsic motivation (e.g., personal hiking and camping, impromptu nature expeditions, community-organized nature walks, and informal outdoor gatherings). This report provides an overview of the benefits of the outdoors as well as factors that shape CALD women’s outdoor participation. Drawing on the findings, 10 multi-level recommendations have been proposed to build more inclusive outdoor spaces.</p
Enacting Pluriversal Design Education: The Importance of Positionality and Intersectionality in Practice
No full textApproaches to tertiary design education in Australia have predominantly drawn on pedagogies and practices from the Global North, often promoting a singularly view, understanding, and accepted aesthetic of design. This “universal” or homogenized understanding has often been at the expense of local identities and traditions, which have often been erased or flattened, leading to narrow representations and ways of being a designer. As dialogues and conceptions of design are shifting to include more decolonial and pluriversal perspectives from many localities around the world, design education is contributing to more diverse systems of practice, critical examinations of design history, and ways of designing.We seek to build on dialogues in Design Issues in support of critical pedagogy where students and educators are encouraged to reflect on the power dynamics, ideologies, and cultural implications inherent in design. O’Shea argues that designers should be reflecting on their position in society, both in training and in practice, and be open to changing their assumptions, approaches, and understandings of the discipline as a result. Many authors underscore the importance of teaching design in relation to its historical and cultural settings and in presenting design history as a legitimate area of pedagogy and research in design studies. </p