Victoria University

Diabetes Mellitus in older adults reduces the accuracy of foot landing adjustments and increases the risk of falling. This study investigated whether targeted visual feedback enhances the accuracy of the foot landing in older participants with diabetes. Forty-eight volunteers in three groups of young, healthy older and older adults with diabetes participated. During treadmill walking, Nexus Vicon software streamed real-time orientation data of two markers on the first toes into MATLAB scripts through a Visual3D server. The system visualised real-meaningful step length or minimum toe clearance (MTC) in each step on a monitor in front of a treadmill at eye level. Participants responded to four subject-specific step-length (±10% mean baseline step length) or MTC targets (3.5 and 5.5 cm higher than the mean baseline MTC). One target was displayed every 10 steps and removed after 10 steps when participants walked without seeing any target, then a new or the same target appeared and stayed on for another 10 steps. Tasks were increasing or decreasing baseline step length or increasing the baseline MTC in response to virtual targets. The accuracy (absolute error) of each step adjustment in each 10-step block with a target was calculated. The mean accuracy of Step 1 and the mean accuracy of Steps 2–10 were measured and compared within and between groups using three-way ANOVA tests. Errors significantly differed between conditions (Step 1 and Steps 2–10) in all groups. All groups showed reduced errors in Step 1 during Steps 2–10. Among groups, the group with diabetes presented the greatest errors in Step 1 and Steps 2–10. These findings suggest that meaningful visual feedback about spatial gait parameters (step length, MTC) can improve foot-landing accuracy in older participants with diabetes, highlighting its potential as a training tool to prevent falls in this high-risk population.

Sleep problems and disorders are prevalent in individuals with chronic musculoskeletal pain (CMP). Yet, previous reviews have struggled to draw precise conclusions due to inconsistent terminology and definitions of sleep problems and disorders. This review analyzed 225 studies to map terminology and definitions for sleep problems and disorders in CMP research. The included studies provided 326 definitions for 39 terminologies. The terminologies “insomnia,” “poor sleep quality,” and “sleep disturbance” were the most commonly used, though definitions varied significantly. Definitions of, for example, insomnia included different questionnaires, diagnostic criteria, and symptom-based assessments. This pattern was seen across most terminologies. This review also found overlapping definitions, such as the Pittsburgh Sleep Quality Index being used for 7 different terminologies. Inconsistent and overlapping use of terminologies and definitions creates confusion and potentially obscures sleep-pain links and the effectiveness of sleep interventions for CMP. This review makes recommendations for CMP researchers to choose the most appropriate terminology and definition for their research aim but also underlines the need for a consensus on terminology and measurement approaches. Standardizing terminology and definitions will enhance research accuracy, improve comparability, and strengthen the evidence base in the sleep-CMP field.

Background Obesity prevalence differs by neighbourhood. One such characteristic of these neighbourhoods is the level of socioeconomic disadvantage. Understanding the nature of neighbourhood socioeconomic inequalities is important for shaping targeted interventions and policies to promote equitable access to resources and opportunities that support healthy living. The aim of this study was to examine associations between neighbourhood socioeconomic disadvantage and body mass index (BMI) over a 16-year period among a population-representative Australian sample. Methods This study used data from 208 309 observations collected between 2006 and 2021 from the Household, Income and Labour Dynamics in Australia Survey. Neighbourhood disadvantage was measured via a census-derived index, and participants self-reported height and weight, which was computed to BMI. Data were analysed using multilevel and fixed effects regression to examine overall associations, trends over time and changes in neighbourhoods with changes in BMI. Results There was an overall association between neighbourhood socioeconomic disadvantage and BMI. BMI was higher among those in the most disadvantaged neighbourhoods compared with the least disadvantaged neighbourhoods (β=1.31, 95% CI 1.15 to 1.46). BMI trends over time were widening with greater increases in BMI among those in the most disadvantaged neighbourhoods (Q1: β=0.04, 95% CI 0.02 to 0.06 and Q2: β=0.05, 95% CI 0.03 to 0.06). Changes in the level of neighbourhood socioeconomic disadvantage were positively associated with changes in BMI, with the strongest association among those transitioning to more disadvantaged neighbourhoods (Q1: β=0.10, 95% CI 0.02 to 0.18 and Q2: β=0.08, 95% CI 0.02 to 0.15). Conclusions Using methodologically rigorous epidemiological approaches along with longitudinal, national data, this study found strong evidence of neighbourhood socioeconomic inequalities in BMI. Understanding the neighbourhood-level mechanisms likely to exacerbate these inequalities remains a future research priority.

This paper presents an efficient feature selection based on Ruzicka similarity to detect and diagnoses seizures caused by epilepsy. The proposed approach reduces the feature space while retaining the most relevant features for classification, enhancing the performance of standard Machine Learning (ML) classifiers. Technically, Bonn University EEG dataset is utilized to validate the model, and classifiers such as Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Decision Tree (DT), Naive Bayes (NB), and Random Forest (RF) are applied. Several measures such as accuracy, recall, precision, and F1-score have been applied for the model evaluation. Results demonstrate that the proposed Ruzicka-based feature selection method achieves superior classification accuracy of 100% with DT, NB, and RF for binary class combinations, outperforming other feature selection strategies. The Ruzicka-based feature selection reduces the feature space from 4097 to 1229 features (30% selection ratio) for the 23.6-s Electroencephalogram (EEG) signal while maintaining high classification accuracy. These findings highlight the potential of the proposed approach to improve diagnostic accuracy in medical applications.

In bearing failure diagnosis, accurate fault detection is essential for ensuring the safe operation of machinery. However, acquiring enough labeled fault data for training is expensive and challenging. This paper aims to address key challenges in few-shot fault diagnosis by proposing a novel framework incorporating an Adaptive Detail Convolution and a dual-branch architecture. The proposed framework consists of three main components: an Adaptive Detail Convolution module for enhanced feature extraction, a Global KAN-Transformer learning branch to model long-range dependencies between global features, and an adaptive-regularized Mahalanobis distance module to measure the similarity of local features between support and query samples. Experimental results on the CWRU dataset show that the proposed framework significantly improves classification performance in terms of accuracy, robustness, and efficiency. The proposed solution offers an effective approach for few-shot bearing fault diagnosis and outperforms existing methods in both accuracy and computational efficiency.

Background Decision-making is integral to navigating everyday life, and understanding the cognitive and emotional factors influencing affective decision-making is crucial. Methods In this study, 149 participants completed the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT) to measure ability emotional intelligence, a N-back working memory task, and three affective decision-making tasks: the Iowa Gambling Task (IGT), Balloon Analogue Risk Task (BART), and Columbia Card Task (CCT). Results The results revealed that understanding emotions, a domain of emotional intelligence, was a significant predictor of superior decision-making on both the IGT and CCT, even after controlling for working memory abilities. This finding suggests that the relationship between understanding emotions and affective decision-making is not merely a reflection of general cognitive abilities, but rather highlights the unique contribution of emotional understanding to strategic decision-making in emotionally charged contexts. However, emotional intelligence was not significantly associated with BART performance. Conclusions These findings highlight the importance of understanding emotions in strategic decision-making and open avenues for future research to investigate whether training ability emotional intelligence can improve affective decision-making tasks and yield meaningful benefits in real-world contexts.

Gait analysis is a crucial tool for understanding human locomotion, particularly in clinical settings where it aids in diagnosing and managing conditions that affect movement. This study investigated muscle activity, intra-, and inter-muscular correlations during gait phases, including first double support (DS1), single support (SS), second double support (DS2), and swing (SW) in both healthy individuals and stroke patients. By examining the root mean square (RMS) values and the area under the curve of RMS envelope of EMG for the gluteus medius (GM), rectus femoris (RF), biceps femoris (BF), medial gastrocnemius (MG), tibialis anterior (TA) and peroneus longus (PL) muscles, this research was designed to enhance our understanding of muscle coordination and its complications in stroke gait rehabilitation. The findings indicated significant differences in muscular activity and inter-limb correlations between limbs within both groups. Stroke patients exhibited knee hyperextension during stance phase, primarily due to muscle weakness and compensatory mechanisms, which may coexist with stiff knee gait during swing phase. Healthy participants showed proximal muscle weakness, likely age-related. Asymmetries in muscle activation between limbs were also observed in both groups, contributing to gait instability and an increased risk of falls. This study provides insights into the differences in muscle coordination between healthy individuals and stroke patients during various phases of walking. The findings emphasize the importance of training distal muscles, including the MG, TA, and PL muscles, in stroke patients, particularly in elderly, while also focusing on core/proximal muscles like the GM, RF, and BF muscles to improve weight-bearing support and gait stability, especially in cases of limited ankle movement. For age-induced muscle weakness, the emphasis should be on distal muscles. These findings have the potential to improve clinical practices by offering better-tailored interventions to enhance mobility and quality of life in stroke survivors.

Neuromuscular ageing is characterized by neural and/or skeletal muscle degeneration that decreases maximal force and power. Female neuromuscular ageing occurs earlier in life compared to males, potentially due to sex hormone changes during the menopausal transition. We quantified neuromuscular function in 88 females represented equally over each decade from 18 to 80 years of age and investigated the role of decreased ovarian hormone concentrations following menopause. Neuromuscular assessment included quadriceps maximal voluntary and evoked isometric torque and surface electromyography measurements, plus one‐repetition maximum leg press. Voluntary and evoked torques and one‐repetition maximum decreased non‐linearly with age, with accelerated reductions starting during the fourth decade. An absence of changes in volitional recruitment of existing quadriceps motor units and Ia afferent facilitation of spinal motoneurons suggests that functional decline was largely mediated by impairment in intrinsic peripheral muscle function and/or neuromuscular transmission. Maximal muscle compound action potential amplitude decreased with increasing age for rectus femoris muscle only, indicating increased vulnerability to neuromuscular degeneration compared to vastus lateralis and medialis. In postmenopausal females, some variance was explained by inter‐individual differences in quadriceps tissue composition and lifestyle factors, but changes in total or free concentrations of oestradiol, progesterone and/or testosterone were included in all correlations with age‐related decreases in isometric voluntary and evoked torques. We demonstrate an accelerated onset of neuromuscular degeneration of peripheral muscular origin around menopause onset associated with changes in sex hormone concentrations. Interventions aimed at mitigating declines in ovarian hormones and their subsequent effects on neuromuscular function after menopause should be further explored. image Key points Neuromuscular deterioration with age is associated with poor physical function and quality of life in older adults, but female‐specific trajectories and mechanisms remain unclear. This study is the first to map neuromuscular function across each decade of the adult lifespan in 88 females from 18 to 80 years old and to examine the potential role of hormonal changes after menopause. We show an accelerated reduction in neuromuscular function, primarily of peripheral muscular origin, that occurs during the fourth decade and coincides with menopause onset. In postmenopausal females, age‐related reductions in neuromuscular function can in part be explained by quadriceps lean and intramuscular fat composition, physical activity and protein intake, and sex hormone concentrations. These findings help us better understand the factors that contribute to the loss of neuromuscular function with age in females, enabling the identification of potential therapeutic interventions to prolong female health span.

In 2001, S. S. Dragomir introduced a generalized class of convexity, the so-called \left(m,M,\psi ) -convex functions, which covers many other classes of convexity. In this article, we prove some useful characterizations of this generalized class of convex functions. We obtain majorization-type inequalities for \left(m,M,\psi ) -convex functions, providing also applications to new estimates for some well-known mean inequalities.

Active learning and inquiry-based learning in higher education foster critical thinking and engagement, preparing students to become lifelong learners and adaptable problem solvers. While intensive delivery modes often incorporate these pedagogies, research has predominantly focused on outcomes rather than the pedagogical approaches themselves. This study addresses this gap by exploring academics’ experiences with active and inquiry-based learning methodologies in the VU Block Model®. Through semi-structured interviews with nine academics, thematic analysis identified five themes illustrating the implementation of these methodologies in intensive delivery modes. Academics described employing active learning practices such as peer teaching, collaboration, hands-on activities and real-world projects in their university classroom. However, the participants' views of the implementation of inquiry-based learning methodologies proved problematic in intensive delivery contexts, often being reduced to posing questions and overlooking its broader scope and potential. The utilisation of active learning and inquiry-based approaches in the context of VU Block Model® presented an opportunity for pedagogical innovation deeply rooted in Dewey’s philosophy of learning through participative and collaborative experience. This study highlights the need for continued exploration of innovative pedagogies in intensive teaching to enhance teaching capacities of academic staff.

To tackle the pollution of tetracycline (TC) in aqueous environments, a few treatment methods, including ozonation, adsorption, and photocatalytic degradation, were compared using a novel and sustainable granular activated carbon-based zinc oxide nanoparticle (ZnO@GAC) composite. The results demonstrate that the ZnO@GAC composite towards TC exhibited a high removal efficiency of 82.1% in a batch adsorption system. Moreover, the photocatalytic TC degradation study on ZnO@GAC under UV light yields a maximum degradation efficiency of 86.4% with a pseudo-first-order rate constant value of 0.0059 min⁻¹. Ozonation treatment resulted in TC and total organic carbon (TOC) removal reaching a maximum of 95.3% and 79.7% for 4 mg O3/min and 99.6% and 86.6% for 16 mg O3/min after 10 min. Overall, in comparing the adsorption, photocatalysis, and ozonation techniques, in terms of removal efficiency and time, ozonation was found to be more promising for treating TC, while in terms of cost-effectiveness, the adsorption process is preferable. Finally, the application of the developed composite in municipal and hospital wastewater using adsorption, photocatalytic degradation, and ozonation techniques revealed that the TOC removal efficiencies were higher for hospital wastewater than municipal wastewater. Furthermore, the applicability of these techniques in treating hospital wastewater containing pharmaceuticals, antibiotics, fungicides, and antimicrobial pollutants shows an outstanding result after treatment. In conclusion, the technologies studied in this research can significantly improve the efficiency and effectiveness of wastewater treatment applications, providing a sustainable, cost-effective, and eco-friendly solution.

We are continuing to live in unsettling times that demand responses from researchers, scholars and activists to create and mobilise knowledge for liberation, wellbeing, and justice. This commentary draws from my lived experience and research in migration that I use to highlight the rootshock of displacement and the contributions of community psychology to understand these impacts. The commentary invites engagement with the decolonial turn, the need to examine longer histories of colonization and imperialism and how these continue to shape understandings of self and others, and intergroup relations. The commentary also emphasizes decoloniality as a movement of embrace that involves expanding our ecologies of knowledge and practice to support critical solidarities for liberation, wellbeing, and justice.

Climate change is a global phenomenon affecting every segment of the population. Yet, older adults are more vulnerable to climate change events (e.g., floods, heatwaves, landslides) owing to their functional limitations. Understandably, stakeholders have called for healthy ageing policies that enable older adults and individuals in the general population to maintain wellbeing despite climate change. This review aims to describe healthy ageing policies adopted or recommended in response to climate change. Eight databases (i.e., CINAHL, Cochrane library, ProQuest, PsycINFO, Google Scholar, Web of Science, Scopus, and MEDLINE) will be searched to identify relevant studies. Materials published anywhere in English to date will be included in the review. The Critical Appraisal Skills Programme (CASP) or Joanna Briggs Institute (JBI) checklist will be employed to assess the quality of studies. A narrative synthesis will be adopted to present the results. This review will highlight groups targeted with healthy ageing policies and describe policies in use or recommended. It will proffer implications for practice, research, and sustainability.

In the past decade, the governance of urban space, in connection with the triad, environmental, social, and governance (ESG), has trended towards greater humanization to achieve urban sustainability and social harmony in China. With a focus on the case of the Waliu Community (Zhengzhou), this study investigates the evolution of environmental governance in its vending zones. As one of the earliest Chinese communities to transition from spatial exclusion to spatial inclusion and then to spatial self-management in environmental governance, the Waliu Community established two specific vending zones, Tea City and Shenglong. These zones have transformed the governing mindset of the community’s urban environment. The latest strategy of spatial self-management enables urban low-income groups to participate in the co-governance of the urban environment. The research methods used in this study range from spatial analysis and direct observation to semi-structured interviews; data and information are collected through field notes, official records, and designed questionnaires. The study investigates key indicators spatial utilization efficiency, vendor livelihood, social order and safety, and stakeholder satisfaction. Results demonstrate that spatial self-management effectively optimizes community traffic flow, enhances waste collection efficiency, and fosters consensus and collaboration among stakeholders. It is concluded that spatial self-management facilitates the sustainable production of urban spaces for their users within China’s complex urban contexts.

The transition to carbon neutrality requires phasing out coal-fired power, a key contributor to global warming. This study quantifies the economic impacts of this shift in China, Japan, and South Korea using the GTAP-E model, focusing on East Asian and ASEAN economies. In cost-neutral scenarios where renewable energy (RE) costs are equal to coal, the phase-out results in slight GDP growth for these countries. However, if RE is 50% more expensive than coal, economic downturns are projected, impacting various regions except India and the EU. Globally, the transition is expected to reduce greenhouse gas emissions by 12–13%, depending on the cost scenario. Countries reliant on coal exports, like Mongolia, Australia, and Indonesia, face significant economic challenges and must diversify their economies to mitigate impacts. Key policy recommendations include developing frameworks to manage the economic effects of RE transitions, fostering international cooperation on RE innovation, and providing targeted support to coal-dependent regions. Carbon pricing mechanisms are essential to prevent carbon leakage and ensure a sustainable energy transition.

The Russia-Ukraine conflict and related geopolitical strategies, such as sanctions on Russian fossil fuel exports, have significant implications for global energy transitions and greenhouse gas (GHG) emissions. Disruptions in energy supply chains affect energy production, prices, and consumption, influencing the pace of the global shift toward renewables. This chapter explores three scenarios: (S1) a price cap on Russian fossil fuel exports, (S2) a comprehensive embargo, and (S3) an alliance supply chain. Using the GTAP-E model, we quantify their effects on real GDP, GHG emissions, and energy transitions. The modeling results demonstrate that S1 promotes energy transitions by reducing fossil fuel shares, particularly coal, while S2 increases reliance on fossil fuels like coal and natural gas, hindering decarbonization efforts. S3 presents mixed impacts, with some nations reducing coal but increasing oil and gas consumption. These findings highlight the complexity of balancing energy security, economic stability, and environmental sustainability amidst geopolitical tensions. Policymakers must tailor energy transition strategies to regional contexts, balancing geopolitical and economic objectives with climate goals. International cooperation is critical to accelerating global decarbonization efforts while ensuring energy security.

Problematic Social Media Use (PSMU), an experience associated with symptoms replicable to those of addiction, has become increasingly prevalent worldwide. Previous literature suggested that social media subgroups convey varying risks with PSMU behaviours. Theoretically prompted by the Self-Determination Theory (SDT), this study aimed to (i) identify homogenous profiles of users based on their amotivation, external regulation, identified regulation and intrinsic motivation; (ii) examine the differences in levels of PSMU amongst motivational profiles and (iii) investigate potential differences in PSMU levels for different motivation styles. 276 social media users (18–62 years, Mage = 31.90, SD = 9.94) were assessed using the Situational Motivation Scale (SIMS) and the Bergen Social Media Addiction Scale (BSMAS) at three-time points, one year apart. Latent profile analysis (LPA) identified two motivational profiles: the ‘Low-Risk Motivation’ (LRM; 77.2%) and the ‘High-Risk Motivation’ profile (HRM; 22.8%). As hypothesised, the HRM profile exhibited higher levels of PSMU across waves. However, PSMU levels did not increase across waves. Findings suggest that users endorsing higher levels of amotivation and external regulation (i.e., HRM) convey a greater prevalence of developing PSMU behaviours. Findings indicate that PSMU may pertain as a maladaptive coping mechanism to manage psychosocial deficiencies. As such, these findings provide significant implications for the intervention, prevention and treatment of PSMU.

Introduction/Purpose Compression garments are a commonly used recovery aid following resistance exercise, which may improve muscle blood flow and perceived recovery. However, there has been limited insight into the underlying molecular mechanisms that may mediate the physiological effects of compression garments. The aim of this study was to investigate the effect of compression tights on markers of muscle protein synthesis, muscle blood flow, and indices of recovery following a bout of resistance exercise. Methods Twenty resistance-trained participants (5 females, 15 males) completed a leg-press exercise session followed by a 5-h recovery period wearing either commercially available compression tights (COMP, n = 10) or no tights (CON, n = 10). Physiological (markers of muscle protein synthesis, muscle blood flow, blood lactate, blood glucose), perceptual (total quality of recovery, perceived muscle soreness and subjective wellbeing), and performance measures (countermovement jump and isometric mid-thigh pull) were collected at baseline, immediately post-exercise (performance and perceptual only), and at 1-h (physiological and perceptual only), 5-h and 24-h post-exercise. Results No significant ( p < 0.05) interactions were observed between groups in physiological, performance, and perceptual measures. There were main effects of time for post-exercise measures compared to baseline ( p < 0.05), with increased markers of muscle protein synthesis, muscle blood flow, blood lactate, muscle soreness, and reduced blood glucose, total quality of recovery, subjective wellbeing, and countermovement jump height for both groups. CONCLUSIONS Commercially available compression tights used post-resistance exercise did not influence muscle protein synthesis markers, muscle blood flow or indices of exercise recovery following resistance exercise in the current study.