Appendicectomy with 29,000 procedures per annum is the most common source of emergency hospitalizations in Australia(1). However, there has been little improvement in understanding acute appendicitis (AA) pathogenesis. Past studies based on online databases (i.e., UK Biobank) highlighted that dietary patterns could significantly contribute to AA development(2). More precisely, patterns aligned with the Mediterranean Diet (MD) were found to decrease the risk of developing AA. Therefore, the aim of this cross-sectional study was to examine whether dietary adherence to the MD had an impact on AA outcomes among appendicectomy patients in South-East Queensland (SEQ). It was hypothesized that clinically diagnosed AA cases would have lower adherence to a MD in comparison to control individuals without AA history. A total of 87 patients (confirmed with diagnostic histopathological reports) were recruited before undergoing appendicectomy at the Acute Surgical Unit at the Royal Brisbane and Women’s Hospital. Another 87 Australia-residing control participants, without AA history were recruited into the study involving a dietary survey based upon the 14-Item MD Assessment Tool from the PREDIMED Study(3). The 14 questions were related to the use of olive oil, daily/weekly intake frequency of fruits, vegetables, legumes, nuts, seafood, spreads, confectioneries, red meat (including processed meat), red/white meat preference, and drinking habits regarding sweet beverages and wine. A maximum score of 14 points (indicative of the complete MD diet) and a minimum score of 0 points (indicative of a diet with no pattern recognisable as MD at all) were possible resulting in two categories defined by ≤ 5 points and ≥ 6 points defined as low and moderate-high adherence to a MD, respectively. A chi-squared test was performed to determine the relationship between MD adherence and appendiceal inflammation status. The AA group 87 patients reported in this study had their AA status confirmed with diagnostic histopathological reports provided by Pathology Queensland following surgery. For the appendicitis cohort, 62% (54/87) could be classified as low adherence whilst 38% (33/87) fell under moderate-high adherence to the MD. In contrast, the control group were categorized 48% (42/87) as low and 52% as moderate-high MD adherence, accordingly. The chi-squared analysis showed a near-significant (trend) value of p = 0.07, confirming that dietary patterns maybe one of the main risk factors of developing the disease. One potential constraint of this study was that there was some discrepancy in socio-demographic characteristics between the intervention and control groups particularly relating to ethnicity, where there was a greater proportion of non-White participants recruited in the non-AA group. It is concluded that dietary patterns associated to low adherence to the MD are likely to increase the risk of developing AA in a Queensland context.

To illustrate the potential risks of overlooking WILD (i.e., Worldwide, Insitu, Local and Diverse) approaches in developmental psychology, we examined possible cultural biases in child protection interventions across WEIRD (i.e., Western, Educated, Industrialized, Rich and Democratic) countries. Analyses of national statistics revealed that children from minority cultural backgrounds are consistently overrepresented in care systems. We argue that equitable policies must adopt WILD-informed frameworks that respect cultural diversity while ensuring children’s safety and well-being.

Prebiotics can help to develop the gut and immune systems of young children via modulation of the gut microbiota(1), reducing the risk of infection and disease in later life. Breastmilk contains unique prebiotics and is associated with lower rates of infection, allergy and gut colonization of pathogenic bacteria, but not all parents can breastfeed. This review aims to understand if formula containing specific prebiotics can help modulate gut and immune outcomes in children up to 3 years, compared to standard formula. A systematic literature review of randomised controlled trials (RCTs) was conducted without date limits using six international databases. RCTs that reported on gut or immune outcomes and included an intervention where a prebiotic blend containing short-chain galactooligosaccharides (scGOS) and long-chain fructooligosaccharides (lcFOS) [(scGOS/lcFOS ratio 9:1)] in formula were included. Studies were assessed for methodological quality and consistency of results using the Cochrane Risk of Bias tool and Health Canada Consistency Rating tool, respectively. Twenty-eight studies were included, of which 24 were high quality (low risk of bias). scGOS/lcFOS prebiotic blend reduced incidence of respiratory and gastrointestinal infections, supported by increases in secretory IgA (first line of defense against pathogens in the gut) and decreases in stool pH. Improved markers of intestinal microbiota, including highly consistent beneficial increases in bifidobacteria and lactobacillus (beneficial bacteria), and decreases in clostridia (detrimental bacteria), were also reported. No study reported any unfavourable effects. Formula with scGOS/lcFOS prebiotic blend improves intestinal microbiota and reduces incidence of infection. When exclusive breastfeeding is not feasible, nurses can improve children’s gut-immunity outcomes by recommending formula with added scGOS/lcFOS prebiotic blend, instead of standard formula.

This study proposes a territorial-scale model to estimate flows of reusable building components by sequentially evaluating technical, logistical, and economic feasibility. It translates reuse barriers—such as disassembly potential, residual performance assessment, transportability, storage conditions, and costs—into measurable indicators. By aggregating component-level data into territorial indicators, the model links component-scale characteristics to overall territorial material flows, providing a framework to assess and compare reuse potential across territories.

We designed and evaluated an AI-based Application to enhance human creativity in design thinking workshops. The results indicated that AI hindered human creativity, resulting in fewer idea generations. The findings from quantitative and qualitative analyses comparing the only-human and human-AI teams indicated that AI contributed to the usability of ideas during the divergent phase and supported humans in converging on more novel ideas. The further development of the application is necessary to consider how humans can collaborate with AI without relying on it.

This study explores patient perspectives on hospital sustainability initiatives. Building on the Theory of Planned Behaviour, 30 interviews with patients reveal support for sustainability such as the use of reusable medical textiles, provided safety and quality are maintained. Patients view sustainability as a hospital responsibility, but value integrating sustainability communication into patient journeys. Informing and engaging patients can help shift sustainability from a background initiative into a trusted part of the healthcare system with patients as informed partners.

This study examines how different AR platforms support learning and creativity in Additive Manufacturing (AM) education. Design students used either a smartphone- or headset-based AR app to explore virtual AM models before completing a design task and questionnaire. Expert reviews and Mann–Whitney U tests showed that headset AR users reported higher usability, better AM understanding, and produced more creative designs. The results highlight the educational value of immersive AR in enhancing technological comprehension and creative performance.

This work introduces a graph-based CAD assistant that predicts the next modelling operation in parametric design sequences. Real CATIA V5 models from the automotive domain are converted into directed acyclic graphs capturing feature dependencies, enabling learning directly from structural design data. A four-layer Graph Attention Network achieved a top-5 prediction accuracy of 94%, outperforming a frequency-based non-parametric baseline. The results show that graph representations and attention-based message passing provide a strong foundation for context-aware modelling assistance.

Social robots increasingly interact with humans in diverse contexts. In this study, a systematic framework is proposed for selecting stakeholders based on the user requirements in participatory design of social robots. Matching social robot design dimensions with stakeholder fields in the framework, is achieved using Quality Function Deployment (QFD) and Design Structure Matrix (DSM) methodologies. A case study is presented to demonstrate utilization of the framework. The contribution of this paper is to develop an infrastructure towards formalization of participatory design of social robots.

Sustainability transitions in manufacturing require new competences and organisational learning. This paper presents Schedazioni, a learner-led assessment tool that helps companies analyse past sustainable design actions. Developed through case studies and a Research-through-Design process, and piloted in industry, it enables teams to map transformations, identify problems, and reflect on impacts. By shifting assessment to internal sensemaking, it supports shared understanding and strengthens sustainability capability.

Companies lack methods to anticipate rebound effects (RE) in design, jeopardising their sustainability ambitions. This action research at Beiersdorf pilots a framework for ex-ante RE identification, modelling, and prevention. The study found 31 economic, behavioural, and social rebound mechanisms triggered by a refillable packaging innovation, using system dynamics to find leverage points for prevention (e.g., foster non-msaterial practices via packaging design). This paper offers a first attempt at a practical approach to integrate RE analysis into design, towards absolute sustainability.

Cost planning for Product-Service Systems faces rising complexity, making life-cycle cost estimates essential. This paper investigates how machine learning (ML) can be applied for life-cycle cost estimation in product development. A literature review was conducted to identify ML-based methods, classify them across life cycle phases, and compare them against traditional methods. Results show that traditional models remain transparent but limited in early stages, while ML methods achieve higher accuracy in data-rich phases. A clear research gap exists for hybrid models and end-of-life costing.

This study examines how engineers formulate natural language prompts for searching existing assemblies in mechanical design. A survey with 48 engineers produced 169 prompts for different assemblies. Results show that prompts are mostly written as bullet points with an average of three and up to seven requirements. The engineers describe assemblies mainly through implicit functional descriptions and geometric or physical parameters. These findings form an empirical basis for developing generative AI-driven, prompt-based systems to foster design reuse.

Engineering outreach helps to address the STEM “leaky pipeline,” yet often lacks inclusive design guidance. This paper presents a methodology for co-designing activities using Inclusivity, Diversity, Equity, and Accessibility (IDEA) principles. Through three workshops integrating pedagogy training and storytelling, the method proved effective: participating engineers’ IDEA knowledge jumped from 20% to 75%, and delivery confidence rose from 24% to 71%. This methodology successfully equips professionals with the confidence and skills to foster a more diverse engineering workforce.

This study utilises low-cost 2D pose tracking to analyse individual technique differences in elite rowers. We established key biomechanical metrics, revealing variations linked to anthropometrics, training style and flexibility. A technique mapping tool was developed, providing objective insights that supplemented expert opinion. A pilot demonstrated the utility of this analysis to generate actionable insights for equipment personalisation. This showcases that low-cost automated methods can provide proactive and meaningful insights suitable for individualized training strategies.

Various methods are offered to measure design creativity. Nonetheless, a debate continues over the development of a trustworthy and objective method to mitigate the influences on the evaluation. Therefore, we propose and develop a novel tool and approach for evaluating design creativity, which reframes creativity evaluation as a structured and data-driven process. This tool represents a significant advancement in the evaluation of design creativity by mitigating objective factors. Importantly, our tool enables researchers and educators to adopt it freely and objectively for evaluation.

Current approaches for the generative design of sheet metal parts only take singular optimization goals into account. This paper presents a concept for a deep reinforcement learning approach to train an agent to generate sheet metal parts by combining segments from a predefined library. Through a weighted reward function, agents can be trained for different or combined optimization goals, such as weight, cost, or sustainability. The resulting agents enable the creation of a pareto front of optimal solutions, supporting efficient exploration of the design space for diverse design objectives.

Generative Artificial Intelligence (GenAI) is transforming design practice yet research lacks empirical insights into adoption in real-world design organisations. Through the case study of a European automotive OEM, we found that GenAI could accelerate ideation, but adoption was limited due to critical concerns regarding intellectual property, data security, originality, and the risk of skill atrophy. Thus, organisational capabilities like workflow specific training, transparent governance of data protection policies, and cohesive toolchains are needed for successful GenAI integration.

Electronic waste is one of the fastest-growing waste streams, yet only a small fraction is properly recycled. Many challenges in recycling originate in product design; for example the choice of materials and joining methods. This paper presents the first version of the Design for Recycling of Electronics Guide, developed to bridge the gap between design and recycling practice. Based on case studies, shredding experiments, and method reviews, it provides practical guidance to help designers anticipate and improve recyclability during product development.