Topology optimization is a powerful tool for the development of light and strong structures. Due to the preliminary nature of the resulting design proposals, a geometry reconstruction process is required. This primarily serves the purpose to create a functional design. In doing so, parameterization of the geometry and the option to modify are demanded in product development as well as automation. A specific medial axis based reconstruction method not only facilitates the automation, but also the intervention with several possibilities for modification of an optimized design proposal. In this paper, we examine at an examplary use case, how this practice could reduce design iteration cycles, although intermediate new design requirements emerge. We discuss the advantages and limitations of this approach.

This paper introduces a novel methodology for analyzing customer preferences within product ecosystems by leveraging video reviews from social media platforms. The approach includes three stages: collecting and preprocessing video reviews, extracting product features using Latent Dirichlet Allocation (LDA), and analyzing sentiment with the VADER package. By utilizing video reviews, this study captures a more detailed and structured understanding of customer experiences compared to traditional textual reviews, offering actionable guidance for product interoperability and user sentiment analysis. The research highlights the importance of understanding the relationships between products and their accessories, providing specific design insights for creating cohesive product ecosystems that resonate with users on both functional and emotional levels.

Within-region geographical variation in Canadian Englishes has rarely been investigated on a large scale. This is at least in part due to claims of Canadian “Englishes” being largely geographically homogeneous (Chambers, 2004; Boberg, 2010; Denis, 2020), despite evidence of regional variation (Dollinger, 2019). Here, we build on older literature that documented regional variation in English spoken in British Columbia (BC). We focus on two regions in BC—the Okanagan and the Lower Mainland—examining four phonological patterns: pre-velar raising of kit, dress, and trap, and Canadian Raising of price. Using Generalized Additive Mixed Models, we find regional differences in vowel pronunciation patterns for pre-velar raising of the examined front vowels and for Canadian Raising of price. Both regions engage in Canadian Raising and pre-velar raising. From that lens, the regions are homogeneous. However, the patterns are produced in regionally specific ways, providing further evidence that regional variation exists within smaller geographical areas in Canadian English. Overall, this challenges the claims of homogeneity for English spoken in Canada and more generally invites an interrogation of what homogeneity means.

A major cause of diagnostic errors is the underlying complexity caused by patient presentations and the context in which diagnosis is being undertaken. This is especially true for settings like emergency medicine and disease spectrums like infectious diseases. To design artefacts that counter such errors, it is essential to map the factors contributing to diagnostic complexity. However, existing complexity assessment methods in healthcare are limited in scope. Addressing this gap, our work operationalises a complexity estimation tool to identify factors contributing to the diagnostic complexity of 10 infectious disease cases in an emergency medicine setting. Our objective findings are further validated by a strong correlation with the difficulty perceived by attending doctors. The work provides a basis for the design of targeted interventions aiming to mitigate complexity in diagnosis.

Resonance, where individual creative moments resonate with each other, has been qualitatively recognized as an important phenomenon during co-creation. In a previous study, the authors conducted a concept generation pair work experiment using biosignal indicators and quantitatively grasped the difference between creative states that are simply creative and those that are resonant. This study explores whether it is possible to estimate these creative states using biosignal indicators with the Hidden Markov Model. The parameters for the Hidden Markov Model were based on multimodal biosignal indicators and subjective self-reflection reports regarding the creative states during co-creation. The results suggested that creative states can be estimated during co-creation using a Hidden Markov Model, and resonance can be understood as a shared form of self-resonance driven by concept generation.

Maritime navigation in low visibility presents a significant challenge, jeopardising seafarers’ situational awareness and escalating collision risks. This study introduces a maritime head-up display (mHUD) to address this issue. The mHUD, a 2-m diameter aluminium ring with dual rows of LEDs, enhances visibility for autonomous ships in adverse conditions on ship bridges and remote operating centres (ROCs). Displaying various modes such as shallow waters, land, lighthouses, beacons, buoys and maritime traffic, the mHUD was evaluated in a ship bridge simulator by 12 navigation students. Results revealed that the mHUD substantially improved situational awareness, proving more efficient and effective than navigating without it in poor visibility conditions. Participants found the mHUD easy to learn and expressed willingness to use it in real-world situations. The study highlights the mHUD’s potential to enhance situational awareness on ship bridges and ROCs for autonomous ships, while suggesting potential enhancements to increase usability and user satisfaction.

Design has shifted from product manufacturing to tackling systems’ complexities in social innovation, focusing on participatory and human-centered design. Despite tools developed to enhance participation, differing perspectives complicate co-creation, necessitating better ways for interdependent thinking and communication. Designers must be embedded within the same social and cultural contexts as others, engaging in long-term participation. Establishing a design context that transcends temporary action but with a joint vision and tasks achievement is crucial. This study identifies varying levels of designers’ involvement and the differences of design context construction. Three modes are illustrated: (1) patching-based, (2) intertwining-based, and (3) expanding-based design context construction. This study advances design theory, encouraging designers to engage in multi-level collaboration.

Concept maps have been used to measure student learning and performance comparisons before and after interventions. However, these concept maps may vary in structure and content. The complexity of the maps are difficult to measure when multiple concepts are embedded within individuals nodes. A systematic coding scheme is evaluated for objectivity and reliability using 22 undergraduate researchers. The findings suggest that the coding scheme is suitable and will allow multiple different researchers to generate similar bi-partite graphs from the notional concept maps generated. Additional work is needed to ensure that the semantic content is not invalidated through the coding scheme.

This paper analyses the amount of design-oriented content in higher education, as well as the extend of activities from product development such as clarification of problem or task, shaping the modules and usage requirements and assurance of fulfilment of requirements. The mechanical engineering study degree program of three universities is analysed by categorizing courses to design-oriented, design-related, basic science and additional expense. These particular courses are then further investigated by assigning the learning hours to certain product development activities regarding the VDI 2221 guideline. The results show that between 14 % and 26 % (bachelor) and from 27 % to 33 % (master) of courses are design-oriented. Most of the time is spent on achieving competencies in shaping modules, e.g. design parts. The other eight activities are treated less than 10 % of the total workload.

The predominant adoption of artificial intelligence (AI) in the design process is constantly evolving with the continuous upgradation of generative AI tools. Current studies emphasised generative AI’s role in individual disciplines, with limited understanding of its use across diverse design disciplines like product, fashion, and UX design. Therefore, the importance of this review is to explore the latest trends in utilisation, commonalities, and differences of generative AI tools and tasks, and AI types across design disciplines. With the assistance of Google Scholar, relevant papers were identified based on alignment with the review’s scope. The study highlights the transformative role of tools like ChatGPT and DALL-E in enhancing creativity, ideation, and decision-making. The outcomes of the review offer insights for future systematic reviews and practical guidance for designers.

Engineering design tasks are cognitively complex and there is a growing interest in understanding the neurocognitive processes involved in design. Consequently, researchers are increasingly using bio-physical markers such as eye tracking to study design neurocognition. However, these studies are largely correlational, and little is understood about the construct validity of eye-tracking metrics such as fixation durations and saccade frequency. Moreover, these studies rarely account for non-design factors such as neurodivergence (e.g., ADHD) on eye-tracking metrics during design. We aim to examine this research gap through a causal-comparative study with designers with and without ADHD, performing divergent and convergent design tasks. Our findings call for a deeper investigation into the construct validity of eye-tracking metrics while considering a broad range of external factors.

The application of Generative Artificial Intelligence (AI) in early-stage design processes has emerged as a promising method for generating innovative solution concepts. However, AI-driven concepts may introduce secondary problems when implemented practically. This study proposes a systematic framework integrating Generative AI (GPT-4o), patent analysis using Retrieval-Augmented Generation (RAG), and Failure Mode and Effects Analysis (FMEA) to predict, evaluate, and mitigate potential risks. Applied to a case study on nickel recovery through froth flotation, the framework significantly enhanced the feasibility, usefulness, and sustainability of solution concepts. The research highlights the scientific contribution and practical benefits of combining Generative AI with structured risk-analysis methods for sustainable innovation.

Developing new factories is effectively a design task. In this paper a case study on barriers to efficient project communication is presented. Preceding research has shown that production systems design projects can be more efficiently executed and that as many as 95% of all problems in collaborations are due to a lack of communication. The study was designed to grasp project communication barriers from three projects and developed a visual planning tool. The findings show that digital planning software supports mainly in the categories of Egocentrism and Mistrust, Equivocality and Ambiguity and less in Interaction Capability, Asynchronisity and Noise and Information-sharing Behaviour. Recommendations for future research is to connect the project communication support to quantitative project performance aswell as the acceptance of technology in production systems design.

Functional decomposition (FD) is essential for simplifying complex systems in engineering design but remains a resource-intensive task reliant on expert knowledge. Despite advances in artificial intelligence, the automation of FD remains underexplored. This study introduces the use of GPT-4o, enhanced with a proposed Monte Carlo tree search for functional decomposition (MCTS-FD) algorithm, to automate FD. The approach is evaluated qualitatively by comparing outputs with those of graduate engineering students and quantitatively by assessing metrics such as structural integrity and semantic accuracy. The results show that GPT-4o, enhanced by MCTS-FD, outperforms smaller models in error rates and graph connectivity, highlighting the potential of large language models to automate FD with human-like accuracy.

Generative AI, guided by inventive heuristics, can systematically and rapidly generate hundreds of ideas for engineering inventive design problems. This paper examines the reliability and effectiveness of AI-powered “idea funnelling,” a process that generates, evaluates, filters, and synthesizes raw ideas into feasible solution concepts. Key challenges include the consistency and objectivity of AI-driven evaluations, the robustness of concept generation, and the collaboration of multiple AI chatbots such as ChatGPT and Gemini. The study explores the integration of human expertise in hybrid problem-solving teams to improve feasibility, contextual relevance, and innovation quality. Through comparative experiments, it provides insights to improve the reliability of AI-driven concept creation and the performance of hybrid AI-human teams in solving complex engineering design problems.

Spermophagus niger L. is a well-known pest of roselle (Hibiscus sabdariffa L.) seeds in West Africa and responsible of mostly damage. This study first reported the presence of S. niger Motschulsky in kenaf (Hibiscus cannabinus L.) seeds stored. Samples of kenaf seeds collected at four locations in Burkina Faso. In the laboratory, the seeds were incubated until adults’ insects emerged. The emerged insects were first identified morphologically and their biodemographic parameters studied under controlled conditions (32°C ± 0.1, 43% ± 1 r.h.). The results showed that S. niger (Coleoptera: Chrysomelidae) was the only pest encountered on H. cannabinus seeds in storage and was able to complete its development cycle there. Over the course of its life, which lasts an average of 7 days, the female laid around 40 eggs, resulting in 24 individuals dominated by females. The embryonic and total development time were average 5 and 26 days, respectively. Spermophagus niger population doubled in 6 days, with an intrinsic rate of natural increase of 0.105. The finite rate of increase and the generation time averaged 1.11 and 31.86 days, respectively. This study pointed out for the first time that S. niger is able to evolve successfully on H. cannabinus seeds in storage conditions and therefore, could be a serious pest of this important crop. The data from this study could therefore be used as a basis for the post-harvest management of H. cannabinus seeds.

Did George Floyd’s murder and its ensuing protests produce a racial reckoning? Conventional social-science accounts, emphasizing the stability of racial attitudes, dismiss this possibility. In contrast, we theorize how these events may have altered Americans’ racial attitudes, in broadly progressive or in potentially countervailing ways across partisan and racial subgroups. An original content analysis of partisan media demonstrates how the information environment framed Black Americans before and after the summer of 2020. Then we examine temporal trends using three different attitude measures: most important problem judgments, explicit favorability towards Whites versus Blacks, and implicit associations. Challenging the conventional wisdom, our analyses demonstrate that racial attitudes changed following George Floyd’s murder, but in ways dependent upon attitude measure and population subgroup.