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Difference in movement coordination and variability during Five-Repetition Sit-to-Stand between people with and without Chronic Low back pain
No full textChronic low back pain (CLBP) affects people’s activities of daily living, including sitting down and standing up. Movement pattern analyses during five-repetition sit-to-stand (5RSTS) may allow CLBP status differentiation. 44 CLBP and 22 asymptomatic participants performed 5RSTS in this study, with their trunk and lower limb movements recorded using 3-dimensional motion capture system. Joint active range of motion, joint maximal velocity, joint and segment continuous relative phase (CRP) were analyzed. Mean absolute relative phase (MARP) and deviation phase (DP) variables were calculated in CRP analysis. Between-group kinematic variables were compared using One-way Multivariate Analysis of Covariance (MANCOVA). Significant variables from different methods were compared using binomial logistic regression to assess accuracy for CLBP status. Results showed that segmental CRP is the most sensitive method for CLBP assessment, with the CLBP group femur-to?pelvis and lumbar-to-pelvis movement coordination was more in-phase MARP (F(8,56) = 7.127, p < 0.001, Wilks’Λ = 0.441, ηp2 = 0.559) and stable DP (F(8,56) = 4.585, p < 0.001, Wilks’Λ = 0.551, ηp2 = 0.449) during both standing up and sitting down. Utilizing CRP variables yielded Nagelkerke R2 = 0.708 and overall correct classification of 93 % for CLBP status. Individuals with CLBP exhibited distinct movement coordination and stability, which should be considered in CLBP assessments and intervention. Variable combination from the segment analysis was found to be the most predictive to CLBP status, and significantly different to the results obtained from joint analysis, highlighting the necessity for CRP method standardization in future studies.</p
Regulating the “Trouble” of Used Textiles: Insights from Australia
No full textThe volume of used textiles, commonly termed “textile waste”, has grown significantly, driven by the rise of fast fashion. New forms of regulation and collaboration across the textile value chain will be required to address the “trouble” of used textiles; however, there is a lack of agreement on how to best frame the problem of used textiles in a regulatory context. In this article, we employ regulatory theory and problem representation theory to analyse emerging regulation in Australia focused on addressing used textile material. We track the proposed regulatory interventions for addressing used textiles, from the submissions to the 2019 Senate Standing Inquiry to the early stages of establishing a voluntary National Clothing Product Stewardship Scheme in 2021–2023. Through analysis of stakeholder perspectives, current legislation, and proposed interventions, we argue that the trouble of used textiles in Australia requires smart regulation that is attentive to stakeholders’ conflicting problem representations and seeks to build consensus among them.</p
Efficient Deep Learning Algorithms for Resource Limited Edge Computing
No full textDeep Neural Networks (DNNs) have become the de facto standard for artificial intelligence (AI) applications, including visual recognition, natural language processing, and autonomous driving. Modern research has demonstrated that the performance of DNN is closely tied to its parameter count, which reflects its learning capacity. In other words, a large model with abundant parameters usually leads to superior performance across various downstream tasks. However, the growing model size of DNNs presents significant challenges for deployment on resource-constrained devices. Edge devices, e.g., smartphones, have revolutionized daily life but are often limited by storage and memory constraints, making them less capable of handling large AI models. A common solution is cloud computing. In this scenario, the users send their requests to the remote cloud servers that process AI models and return the results. Nonetheless, privacy concerns prevent many users from sharing sensitive data with external servers, creating a strong demand for on-device AI. To this end, efficient learning for DNNs has emerged as an important field of tremendous interest to the AI community, aiming to develop compact models with satisfactory performance.In this thesis, we systematically investigate efficient neural models from three perspectives. Firstly, we present a knowledge distillation (KD) framework that improves small models seamlessly without architecture modification and extra inference overhead. Notably, we observe a semantic gap between the small student models and the large teacher models due to the variation in learning capacity. To address this, we propose the one-to-all distillation using the attention mechanism to bridge this gap. Second, we investigate the widely used attention module, which is believed the key to Transformers yet criticized for quadratic computational complexity. We found that some attention layers are less informative and could be removed without performance compromise. Specifically, we utilize transfer entropy to quantify the importance of the attention layers within a Transformer. Lastly, we investigate integrating multi-modal input in a single model to handle multiple tasks simultaneously, which reduces model size compared to training separate models for each task. We propose the gradient calibration to mitigate the challenges of task conflict and modality bias.We conduct extensive experiments on large-scale benchmarks to validate the effectiveness of the proposed methods. Our research contributes largely to the development of efficient learning for deep models, marking a significant step toward compact AI solutions for resource-constrained devices.</p
Programmable Photonic Waveguide Array Quantum Processors
No full textQuantum computers leverage quantum mechanics to process information, promising solutions to problems that remain intractable for even the most advanced classical supercomputers. Although various physical platforms have been explored for quantum computation, encoding quantum information in single photons stands out due to its inherent resistance to decoherence and the ability to manipulate photons with high fidelity through linear optical networks. In addition to programmable photonic circuits for quantum state manipulation, single-photon sources, and detectors are crucial for quantum state preparation and readout. Integrated photonic circuits, supported by the rapid advancements in semiconductor technology, offer a powerful avenue for miniaturizing and scaling optical quantum processors.Waveguide arrays (WAs) represent a unique platform in integrated photonics, enabling ``always-on'' Hamiltonians that provide direct access to higher-dimensional quantum systems. However, conventional WAs have largely been application-specific and fixed in functionality. In contrast, programmable waveguide arrays (PWAs) introduce dynamic reconfigurability by leveraging electro-optic materials, such as lithium niobate, enabled by micrometer-scale tuners placed between waveguides. PWAs not only overcome the limitations of application-specific WAs and traditional MZI-based architectures, such as the need for bends to route light paths and their sensitivity to fabrication imperfections, but also hold promise for significantly enhancing the scalability and versatility of photonic quantum processors.This thesis addresses significant research gaps by investigating the photonic device design, simulation, and experimental demonstration of PWAs as quantum processors. Previous work has not adequately explored how precise, reconfigurable control can be integrated into platforms that leverage electro-optic effects. By focusing on challenges in WAs and MZI-based architectures, this work fills a critical void in our understanding of how to design, simulate, characterize, and control PWAs, and how they can reliably enhance the scalability and versatility of photonic systems. The thesis begins with an overview of quantum information theory and the manipulation of photons as carriers of quantum information. It then introduces the fundamentals of integrated quantum photonics and PWAs, followed by two key experimental demonstrations on an 11-dimensional PWA based on lithium niobate (LN, LiNbO3) and a novel design for a tunable directional coupler. Finally, the work reviews the evolution of waveguide arrays and programmable waveguide arrays, proposing a vision for integrating PWAs into advanced photonic circuits and highlighting their transformative potential across interdisciplinary applications.</p
Making financial abuse visible: Embedding women's and children's voices in policymaking and research
No full textBy bringing together perspectives spanning advocacy, service organisations, and researchers working in the field of financial abuse prevention and intervention, this white paper shows the gaps in current data collection tools, such as the personal safety survey (ABS, 2024). The paper also discusses who needs to have a seat at the table in future data collection and research design.</p
Mathematical model for predicting carpenters' job-related risk of back musculoskeletal disorders in Australia
No full textA mathematical model is presented to predict the likelihood of upper and lower back musculoskeletal disorders (BMSDs) originating from carpenters’ lifting and lowering tasks. The model is based on quantitative data from carpenters through a systematic questionnaire survey in Australia's construction industry. Multinomial logistic regression was used to develop the predictive model that considers personal attributes, physical abilities, job demands, and task postures. The R2 values and χ2 tests suggest that the predictive model for lower and upper BMSDs fits different age demographics well. The Kruskal–Wallis test found significant differences in the prevalence of musculoskeletal disorders across age groups in the lower and upper back (p </p
Mapping deformation and pressure distribution of elastic maternity support garments for optimized therapeutic design
No full textMaternity support garments (MSGs) are therapeutic garments concerned with the
alleviation of pain, body support and improvement of the wearer’s comfort. MSGs have
been demonstrated to be effective in reducing lower back pain (LBP) and pelvic girdle pain
(PGP), in increasing balance and the wearer’s functionality and mobility. MSG are worn
next to the skin and are commonly made of elastic materials. They are constructed to have
a negative fit, meaning the garment is smaller than the body over which it is fitted. This
design generates pressure on the underlying tissue, compresses and maintains body parts in
correct anatomical position, reduces muscle oscillation, and supports the underlying tissues.
Although it is commonly believed that garments made from elastic materials can
accommodate the body contours and shape differences among wearers of the same
size, inadequate fit can cause discomfort and irritation to the skin and body. This often
discourages their use. If the garment does not apply the appropriate interface pressure to the
intended body part, it may have no beneficial effect or could even cause negative effects for
the wearer. This can impact the effectiveness of the therapy and reduce patient adherence.
This study aims to understand the elastic behavior of MSG during wear and to create a
body map of its distribution. It also seeks to determine the pressure these garments exert
on the underlying body and how this relates to fabric stretch. These insights will help in
engineering MSG for specific body parts and functions.</p
Profiling gaming disorder risk: the role of family communication and vertical individualism
No full textInternet Gaming Disorder (IGD) is characterized by persistent gaming behavior that causes significant social and personal impairment. While most research has focused on individual and game-related factors contributing to IGD, less attention has been given to environmental influences such as family communication (FC), vertically individualistic (VI) values and their interaction effect. This study aimed to (1) profile adult and adolescent gamers based on their FC experiences, (2) examine differences in IGD levels across distinct FC profiles, and (3) assess whether FC moderates the relationship between VI values and IGD risk. A longitudinal design was employed with 565 gamers (ages 12–68, M = 29.27), 276 of whom participated in a six-month follow-up. Latent Profile Analysis conducted at the initial time point identified two FC profiles among adults: ‘Positive Family Communication’ (71.7%) and ‘Negative Family Communication’ (28.3%). Among adolescents, four distinct profiles emerged: Average Family Communication (44.6%), Positive Family Communication (14.9%), Average but Unsatisfied Family Communication (16.2%), and Negative Family Communication (24.3%). Significant differences in IGD levels were observed across these profiles for both age groups. However, FC did not significantly moderate the relationship between VI values and IGD risk at either time point. These results highlight the role of environmental factors in the development of IGD, with distinct patterns observed between adolescents and adults. Recognizing age-specific environmental influences on IGD can help inform more targeted treatment strategies.</p
Bondi Junction stabbings: Did guidelines for responsible reporting on mental illness and crime work?
No full textThis article examines if Australian media guidelines for reporting on mental illness in the context of crime were successfully implemented by the media in 2024 after the tragic events at Bondi Junction Shopping Centre. The incident was the first major news event featuring a person with complex mental illness after the publication of new Mindframe guidelines in 2020. We conducted an analysis of the television and text-based news coverage in Australia and asked, ‘Did mainstream media coverage of the Bondi stabbing adhere to newly established guidelines on ethical reporting of complex mental illness?’ We found some news organizations had implemented the best practice reporting that worked to de-stigmatize mental illness, but a significant amount of content was clearly stigmatizing towards people with complex mental illness. We concluded that more needs to be done to help experts and journalists understand the importance of the guidelines, which seek to provide a balanced and accurate view of people who live with complex mental illness and to encourage help-seeking behaviour.</p
Broadening the competencies of MBA students in Vietnam: Integrating andragogical approaches with sustainable development goals
No full textThis paper provides a case study on the integration of andragogical principles and Sustainable Development Goals (SDGs) into an MBA curriculum at a leading university in Vietnam, enhancing student learning and leadership development. It introduces a specific pedagogical innovation by combining andragogy, self-directed learning (SDL), and structured assurance of learning mechanisms to promote critical skills in ethical reasoning, problem-solving, and sustainability-oriented leadership. By drawing on models associated with self-directed learning (SDL) and assurance of learning, the study evaluates the implementation and outcomes of this methodology, emphasizing its contribution to the creation of responsible business leaders. The paper proposes a framework that extends existing models by embedding adult learning theories and sustainable development principles into the MBA curriculum. This framework highlights practical learning, SDL, and real-world application as key components. The findings suggest that embedding SDGs in MBA curricula equips students with the skills necessary for ethical leadership and sustainability, thereby advancing responsible management and reinforcing institutional commitment to sustainability. The study provides insights into the impact of these interventions on student and faculty development, as well as broader implications for management education in emerging markets.</p