Skateboards used in competitive events such as the Olympic Games are sophisticated products that have remained largely unchanged for over four decades. This presents an opportunity for improvement in the form of reduced weight and moment of inertia, while maintaining comparable stiffness to the most popular skateboard truck currently in use. To achieve this, topology optimization was employed with consideration of real-world loads, which are inherent to street skating. To ensure a reliable and predictable handling, a re-engineering of the benchmark truck was used. To assess the impact of weight reduction on the overall system, all skateboard components were modelled and assembled to compare the center of mass and moment of inertia with the benchmark. Following the virtual validation, the skateboard truck was printed via SLS with a weight reduction of 19 % compared to the benchmark.

The usage of micromobility devices is growing to promote sustainable transportation, prompting manufacturers and regulators to enable its safe integration into urban environments. This has created the need for a tool to evaluate such devices. This paper presents the development of a versatile dynamometer design for verification and validation of micromobility devices by emulating real-world conditions while capturing vehicle and battery performance in real-time. A custom Graphical User Interface (GUI) is used to control and configure the system, as well as enabling the user to analyze and save incoming data. Six devices were chosen from distinct categories to collect data and demonstrate the capabilities and modularity of the dynamometer. The results reflect the ability of the dynamometer to be used for standardized testing of various micromobility devices.

While LGBTQIA+ identities are already mostly invisible in the Italian education system, the current anti-gender policies proposed by right-wing and far-right politicians risk further hindering an inclusive education. However, recent Italian graphic novels pave the way for a multifaceted representation of the LGBTQIA+ community and an alternative form of education. For instance, Nicoz Balboa’s Play with Fire (2020) and Alec Trenta’s Barba (2022) are two autofictional graphic novels that depict the authors’ discovery of their trans identity and their experiences in the cis-heteronormative society. The article argues that the two works by Balboa and Trenta are not just examples of autofiction but also constitute an archive of memory and activism. First, the article traces the damaging effects of a lack of education around LGBTQIA+ themes. Then, it explores how Balboa and Trenta understand their lives by reading LGBTQIA+ stories and histories. Crucially, the article investigates how both authors become a point of reference themselves by representing their own bodies and including explanations about gender and sexuality topics. Documenting the way Balboa and Trenta build a counter-educational space in their graphic novels and chart a literary queer and trans genealogy, the article ultimately suggests that their works are a form of activist practice.

This study examines generative design (GD) within mass personalization (MP) workflows, using custom dental implant abutments as a case study. Selected for their complex functional requirements, a parametric model developed in Rhino3D and Grasshopper, augmented with Wallacei for optimization, was compared to conventional industrial CAD approaches. GD automates design iterations and handles multi-objective optimizations, with performance improvements achieved by segmenting the parametric model. However, GD requires precise parameterization, posing challenges for less experienced designers. While GD enhances iteration efficiency and explores complex design spaces, its computational demands and limited adaptability to extensive geometric variations reduce overall efficiency.

This study investigates the relationship between MBTI personality type diversity and team performance in the first-year “Introduction to Design” course at SUTD. Analysis reveals a statistically significant yet weak correlation between greater MBTI diversity and higher final project grades. Additionally, teams with more introverted (I) and intuitive (N) members tended to perform better, consistent with research linking introverts to deep reflection and structured decision-making, and intuitives to creative problem-solving and future-oriented thinking. Result also shows that teams with INTJ and ISTP members performed better, while those with ISFP members showed lower performance. While these findings suggest personality composition influences team performances, measured in terms of grades, further research is needed to establish causation and underlying mechanisms.

The Sustainable Product Development (SPD) module bridges sustainability concepts into higher education, equipping Master’s students with theoretical knowledge, practical skills, and critical thinking to address sustainability challenges. Combining lectures with hands-on exercises and a flipped classroom, it engages students with tools like Life Cycle Assessment (LCA) and Material Flow Analysis (MFA) to apply sustainability principles in real-world scenarios. Topics such as circular economy, sustainable business models, and ecolabels provide a comprehensive understanding of sustainability across the product lifecycle. The course progresses from foundational principles to advanced applications, linking theory and practice. This prepares students to assess environmental impacts, develop sustainable solutions, and balance competing requirements, meeting industry and societal needs.

This paper presents a systematic literature review to figure out challenges of integration of used components into new product generations. Reuse of components is an essential strategy of circularity and is becoming highly relevant as resources are limited and sustainability requirements have to be meet across industries. The reuse process was examined from a constructive perspective. It was found that the reuse process is not uniformly defined and that there is a divergent understanding of it. This divergent understanding continues through the Reuse process steps and the added value of using Reuse. Various technical challenges of reuse were identified. These challenges were translated into requirements that are intended to enable reuse for used components. An initial concept for solving the design problem of integrating used components is proposed with the help of these requirements.

The integration of Model-Based Systems Engineering (MBSE) and data analytics (DA) has introduced a novel approach, Data-Driven Model-Based Systems Engineering (DDMBSE), which combines structured system modelling with data-driven insights. DDMBSE offers the potential for improvements in model optimisation, economic efficiency and the implementation of dynamic system updates based on real-time data. However, the diverse applications of DDMBSE lack a structured overview of its use cases. This paper addresses this gap by proposing a comprehensive framework for the categorisation and description of DDMBSE use cases. It provides users with a structure to navigate within DDMBSE landscape, consolidate knowledge, and identify underexplored areas for future research. This contribution establishes a foundation for advancing the implementation of DDMBSE across industries and fostering its adoption.

Variation simulation approaches are frequently used to analyse the effects of geometrical variations on the final product quality. Various software tools are used during product development as they strongly differ in their specified goals, the context of use, and users. Although a few workarounds and information-sharing strategies exist, switching software usually results in the simulation model being built from scratch, leading to redundant manual effort and uncertainties. This paper examines the potential and limitations of the Quality Information Framework (QIF) information model in improving collaborative work within a heterogeneous simulation software landscape by exchanging variation simulation model-related information in a standardised Model-Based Definition sense. An application scenario shows how QIF can bridge the gap between tools used in early and late design phases.

Spatial Computing (SC), the use of technology to blur the boundaries between physical and digital into an efficient, intuitive, high performance set of tools, holds huge promise for engineering design. With dramatic and accelerating industry prominence but little research in the design field, there is a need to generalize and frame SC for design. This paper contributes an operational framework for Spatial Engineering (SE) systems highlighting the roles of physical and digital users, objects, environments, and data, and five capabilities required for implementation. It then identifies value propositions for SE evidenced from review of the design field, including design activities in which value is generated. Finally, it presents research opportunities centered on good practice, system interaction and technology, and balancing overhead with the value that these systems provide.

This work describes and discusses Permian ammonoid faunas collected in two stratigraphic sections from the Las Delicias Formation of Coahuila state, northern Mexico. The taxa identified comprise 18 species, including Demarezites quirozii new species, as well as Mexicoceras smithi (Miller and Furnish, 1940), a variety of Mexicoceras guadalupense (Girty, 1908) here upgraded to specific status. The systematic analysis of the species found allowed us to recognize two middle Permian faunal zones, represented in ascending order by the Waagenoceras dieneri-Adrianites elegans Biozone from the Wordian and the Timorites schucherti-Cibolites uddeni Biozone from the Capitanian. Thus, the relative age of the Las Difuntas-18 section is established as Wordian (middle Guadalupian), whereas the Las Manuelas I section is Wordian–Capitanian (middle–upper Guadalupian). Both ammonoid zones are correlated with those recorded in Guadalupian outcrops from the southern USA, northeastern Japan, and southern China. This faunal resemblance between Mexican ammonoids and those taxa reported in these regions (USA, Japan, and China) supports the proposal that during the middle Guadalupian there was a marine corridor through the Panthalassa Ocean, which could have connected the Paleotethys and North American regions. It should be noted that ammonoids of both studied sections from the Las Delicias Formation were correlated better with West Texas (USA) and British Columbia (Canada) faunas, which are included in the North American Realm.

UUID: https://zoobank.org/60c6c43c-6536-4fbf-a372-c610bec86626

This research investigates the needs and preferences of low-income angioplasty patients and their caregivers in India during post-angioplasty recovery. Through in-depth interviews and contextual inquiries, the study uncovers critical informational, physical, and emotional needs. Patients often lack access to reliable health information, leading to misconceptions about care and medication adherence. Pain management and emotional support are significant concerns for both patients and caregivers. The study proposes the integration of digital health solutions to address these challenges, providing a platform for reliable information, communication, and support. This research emphasizes the need for context-sensitive interventions to improve patient outcomes and enhance the quality of life for vulnerable populations in developing countries.

With recent advancements in data-driven methods, there has been a growing interest in implementing AI in design. Despite this, a comprehensive understanding of the critical AI methods in design and how they support design practices remains lacking. To deepen our understanding, we conduct a comprehensive literature review and propose a novel, design-centric AI typology, associated with six AI assistance types for product service development. Our typology differs from traditional ones by shifting the focus from an algorithmic perspective to how models support design practice. Key findings highlight how these six design-centric AI methods support design practices in different ways, each with its own application challenges. Establishing a shared design-centric AI typology and assistance framework will enhance the understanding of how AI works differently and supports practitioners.

Recent advances in AI offer promising opportunities for creative design, particularly through the generation of inspirational images. While prior research has explored the general benefits and limitations of text-to-image tools, there is significant potential in overcoming these constraints by investigating agile, multimodal prompting to facilitate more project-appropriate human-AI interaction. We present the development of a system designed to support both text-based and sketch-based image generation, serving as a research artefact for studying creativity support through multimodal Generative AI. The system enables dynamic dialogue interaction and visualization of the respective contributions. This paper focuses on the development of this AI system as a research artefact to enable future research through design, exploring how multimodal prompting can influence the design process.

This paper demonstrates how the Portfolio of Capability Constraint Network (PCCN) facilitates modeling and analyzing complex manufacturing networks by framing them as constraint satisfaction problems (CSPs). These models face high complexity due to numerous n-ary constraints and large solution spaces, posing challenges for standard solution algorithms. Existing CSP remodeling approaches were reviewed but found unsuitable for the specific needs of PCCNs. As a result, tailored design guidelines and heuristics were developed to reduce problem complexity effectively. The applicability of these guidelines was validated using a use case involving the production of a multi-material shaft with tailored forming technology. Results showed significant efficiency gains in solution searches, emphasizing the practical value of the proposed methods in simplifying and optimizing PCCN-based models.

The industrial application of additive manufacturing (AM) necessitates close collaboration between design and manufacturing. However, significant challenges persist throughout the product development process. To explore these challenges, we conducted interviews with 11 engineers from different companies utilizing AM technologies. These interviews revealed recurring themes, such as a lack of AM-specific mindset and uninformed decision-making, which pose challenges across different phases of product development. The identified challenges, along with proposed solutions and practices, were mapped to specific product development phases, providing a scope for development frameworks for AM. Our study indicates that while some challenges are phase-specific, others impact the entire product development process. Operational solutions for different development phases are still missing.

This study discusses the production of Eco-friendly mask using mushroom-based pulps through physicochemical treatment of mushrooms. Ultimately, it explores an approach to reduce the usage of petrochemical materials. Through the treatment of fruiting bodies from two mushroom species, Pleurotus ostreatus (Oyster mushroom) and Flammulina velutipes (Enoki mushroom), pulp was produced. Then, it was used in wet-laid sheet processing to fabricate both pure MBP sheets and composites blended with cotton. The manufactured textile was subjected to various property analyses, including antibacterial test and was also used to produce a mask prototype. In conclusion, although improvements in breathability are currently needed for practical application, the potential for further research is vast and promising. This study contributes to the advancement of sustainable, biodegradable materials as a solution to environmental challenges posed by the widespread use of synthetic polymers.

The aspiration of representative democracy is that the legislature will make decisions that reflect what the majority of people want. The US Constitution, however, created a Congress with both majoritarian and counter-majoritarian forces. We study public opinion on 103 important issues on the congressional agenda from 2006 to 2022 using the Cooperative Congressional Election Study. Congress made decisions that aligned with what the majority of people wanted on 55% of these issues. Analysis of each issue further reveals the circumstances under which Congress represents the majority and the many ways that representation fails. The likelihood that the House passes a bill is usually a reflection of public support for that policy, but Senate passage depends on how divided the public is on the issue and whether party control of the two chambers of Congress is divided. Legislative institutions make it difficult to pass popular bills but even more difficult to pass unpopular ones. As a result, most representational failures occur because Congress failed to pass a popular bill, rather than because it passed a bill that the public did not want.

This paper aims to assist learners in effectively documenting, transforming, and managing natural language-based information during the Design thinking (DT) process. Further, it seeks to aid evaluators in ensuring traceability and capturing design rationale when assessing the process and outcomes of DT. To achieve this, it presents templates that facilitate documentation and assessment. The effectiveness of these templates was evaluated through an empirical study involving 20 undergraduate students in a design thinking workshop. Analysis of documented templates, questionnaires, and interviews reveals the positive effects of templates on documentation and assessment activities and justifies using proposed documentation templates. The templates can be used as a support tool for process-based documentation as well as assessment activities during the early stages of the DT process.