Dynamics of a spherical particle and the suspending low-Reynolds-number fluid confined between two concentric spherical walls were studied numerically. We calculated the particle’s hydrodynamic mobilities at various locations in the confined space. It was observed that the mobility is largest near the middle of confined space along the radial direction, and decays as the particle becomes closer to no-slip walls. At a certain confinement level, the maximal mobility occurs near the inner wall. We also calculated the drift velocity of the particle perpendicular to the external force. The magnitude of the drift velocity normalised by the velocity along the external force was found to depend on particle location and the confinement level; it is observed that the maximal drift velocity occurs near the wall. Fluid vortices in the confined space induced by particle motion were observed and analysed. In addition, we studied particle trajectories in the flow when the walls rotate at constant angular velocities. The externally applied force, rotation-induced flow and centrifugal/centripetal force, and particle–wall interaction lead to various modes of particle motion. This work lays the foundation to understand and manipulate particulate transport in microfluidic applications such as intracellular transport and encapsulation technologies.

Interdisciplinary work environments, such as in the engineering of Cyber-Physical Systems (CPS), face significant communication challenges due to the need for collaboration among different engineering domains. This study examines communication comprehensibility within a CPS research project involving 30 researchers from multiple universities. We conducted two surveys to assess the status quo of communication comprehensibility. While most research descriptions are generally understandable, significant barriers exist due to technical terminology and differing epistemic foundations. The study presents a systematic approach to assess communication comprehensibility in interdisciplinary projects and highlights the need for support in enhancing communication. Further data from multiple projects is needed to develop effective communication models for interdisciplinary teams.

Conformal prediction (CP) is a framework that provides uncertainty quantification output as valid marginal coverage for predictive models. At present, the main methods used are divided into Bayesian methods and statistical inference method. Among the statistical inference methods, split, full and adaptive conformal prediction are the basic methods. Although there are numerous variations of these methods, a clear comparison is lacking. In this paper, three basic conformal prediction methods are compared on low-dimensional and high-dimensional dataset to illustrate the advantages and disadvantages of each method. The experiment shows that split conformal prediction performs stable coverage but holds data partition as key issue to solve; Expected coverage could not be achieved by Full conformal though it can decrease the prediction interval; Adaptive conformal prediction faces the quantile distribution deviation of complex model. This paper also illustrate the direction of future research.

This study investigates user engagement and its relationship with the visual aspects of design using a newly designed 3D Tic-Tac-Toe. The research examines user experience factors like cognitive engagement, fun, stress relief, etc., and to analyze their correlation with the design principles found in literature, such as Contrast, Framing, and Balance. 15 teams, comprising 2 players each, from design academic backgrounds, were provided with the game board to play. Researchers observed interactions and challenges, while subsequent surveys captured experience, aesthetics, emotional response, and design principles. The findings reveal the strong and weak correlations amongst the factors and the principles, highlights further prototype refinement. The insights integrate cognitive and emotional dimensions with core principles of design to create engaging and visually satisfying products.

Cyber-physical production systems (CPPS) are responsible for a significant portion of manufacturers’ carbon emissions. Since 80% of product-related environmental impacts are determined at the design stage, there is a need for CPPS manufacturers to focus on decarbonization at the design stage. To date, there is a lack of design-for-decarbonization guidance for CPPS. This paper proposes a procedural framework for the effective selection of decarbonization measures for the design of CPPS. A Decarbonization Wheel is developed to establish a product-specific decarbonization strategy. This tool is linked to a catalogue of decarbonization measures. A measure prioritization logic provides a structure for systematizing selected measures. The framework is validated in the case of an intelligent industrial control valve.

This study investigates the integration of Large Language Models with the TRIZ to improve problem solving and innovation in industrial product development. By combining the structured problem-solving framework of TRIZ with LLMs to process large amounts of data and generate ideas, this hybrid approach seeks to overcome the limitations of traditional TRIZ and optimize solution generation. In a case study conducted in an industrial setting, the effectiveness of this integration was investigated by comparing team-generated solutions with those derived using LLMs and TRIZ-enhanced LLMs. The results show that while LLMs accelerate idea generation and provide practical solutions, the additional structure of TRIZ can provide unique insights, however depending on the application context.

Repair plays a critical role in promoting circular economy principles and fostering resource efficiency. However, the current environment often discourages repair activities. While new policies, such as the Green Deal and EU directives, aim to disseminate and implement repair strategies, there remains a significant need to support users throughout the repair process. This study aims to explore the existing body of knowledge that supports users at various stages of the repair activity, focusing specifically on household appliances. Through a systematic literature review, 12 articles were identified, analyzed, and categorized into five themes. Furthermore, seven key attributes were identified, against which the selected papers were classified. The analysis highlights the need for effective and efficient support, particularly for non-tech-savvy users, during self-repair activities.

E-commerce’s rapid growth has increased demand for logistics services, pressuring logistics service providers (LSPs) to offer more competitive solutions in a fragmented industry. This drives a shift from customized to standardized services, which also impacts business processes. While configuration systems are widely adopted in manufacturing companies to support the sales process of products, their application in LSPs remains unexplored. A case study explored their feasibility in warehouse services and found that these services could be modeled and incorporated in a sales configurator, saving time on customer communication, reducing errors during the sales process, and enhancing collaboration on warehouse service design. Thus, the study points to a new application area for configurators, which neither the industry nor academia has given much focus.

As the global elderly population grows, emotional challenges unique to this demographic are often neglected in design under the assumption that older adults can regulate their emotions independently. This study highlights the importance of fostering positive emotions in the elderly through leisure activities. It examines (1) how design practitioners conceptualize emotion regulation in older adults, (2) the challenges they face in creating supportive designs, and (3) enablers identified by elderly individuals. Twelve design practitioners generated 64 interactive design concepts to enhance elderly leisure experiences, followed by interviews with five elderly participants to explore their emotional needs and preferences. The findings underscore designers’ challenges and highlight opportunities for user-centered approaches to promote emotional well-being in aging populations.

Light weight design Plans am cranial role in enhancing efficiency and sustainability. The strategic use of advanced materials, such as fiber-reinforced plastics, can help achieving lightweight designs. However, the anisotropic material properties of composite materials also lead to new challenges in the design and manufacturing process. Additionally, due to the layered structure of composite parts, the number of design points is increased drastically. Moreover, the complex manufacturing process, including curing, makes composite parts prone to variations. Therefore, this research paper presents an innovative lightweight design approach that aims to overcome the described difficulties by linking the individual simulation steps, providing a continuous simulation strategy and taking variations into account. Finally, the presented simulation strategy is applied to an electrified cross skate.

Design decision-making under competition is a critical challenge in real-world engineering design. These challenges are compounded by bounded rationality, where cognitive limitations and imperfect information influence decision-making strategies. To address these issues, we develop a game-theoretic research platform to investigate team-based design under competition. This platform abstracts and simulates real-world competitive design scenarios through controlled experiments. It features a user-friendly interface to collect behavioral data, which supports the analysis of team and individual strategies. Additionally, we validated the platform through a pilot study, demonstrating its ability to capture realistic design features and generate meaningful insights into competitive design behaviors.

Emotional symptoms are common in children with attention-deficit/hyperactivity disorder (ADHD) and are often associated with long-term adverse outcomes. However, little is known about how emotional symptoms develop from middle childhood to early adolescence in individuals with ADHD, including how they differ between boys and girls. This study investigated the trajectories of emotional symptoms in children with ADHD during this transition period and compared to neurotypical peers, using longitudinal data from the UK Millennium Cohort Study, while also examining potential sex differences. Latent growth curve modeling was employed to model emotional symptoms at ages 7, 11, and 14. Children with ADHD had significantly higher levels of emotional symptoms than neurotypical peers across all three waves, with levels remaining stable over time. Boys and girls with ADHD did not differ in their emotional symptoms levels at any wave. Girls with ADHD however did show a significant increase in emotional symptoms over time, whilst boys’ levels remained relatively stable over the same period. These findings highlight the importance of early screening for emotional symptoms in children with early-diagnosed ADHD, with particular attention to the increasing levels of emotional symptoms in girls as they transition into adolescence.

Digital Twins are widely recognized as a transformative technological trend, yet their potential to foster innovation, particularly their generative capabilities, remains underexplored. This paper investigates how they can transcend traditional optimization roles to serve as tools for advancing knowledge and generativity in the design of their physical counterparts. Leveraging C-K theory, a framework is presented for modeling design processes with Digital Twins, characterizing design scenarios and identifying two distinct forms of generativity. An illustration of these results shows how designers can leverage Digital Twin reflexive capacity to challenge and reconfigure underlying knowledge of their physical counterparts. The transformative value of this reflexivity, combined with remodeling capabilities, is highlights the exploration of new design pathway for Digital Twins themselves.

To meet the upcoming sustainability challenges, aerospace manufacturers need to develop products that both address complex sustainability factors and ensure profitable realization. Furthermore, the sustainability perspective needs to be lifted from focusing on carbon emissions, and broadened to include a system-level socio-ecological view. Manufacturers are thus challenged to balance sustainability, manufacturability, and performance, but lack the methods and tools to make well-informed decisions. We propose a method for conducting multi-domain trade-off studies in the early design phase. A functional architecture modelling approach is utilized to model performance and manufacturing aspects. Together with a relative sustainability fingerprint conducted on design alternatives, design spaces can be explored with respect to performance, manufacturability, and sustainability.

This study investigates the elements influencing consumer behavior in the proper disposal of e-waste to advance management practices and circularity. Anchored in Sustainable Behavior Theory and the SHIFT framework, it analyzes secondary data from 51 Brazilian e-waste management companies through document analysis. Findings reveal diverse strategies addressing behavioral barriers and gaps in consumer engagement, informing the Circular Behavior Integration Framework (CBIF). The CBIF provides actionable insights for aligning consumer behavior with reverse logistics systems, advancing material circularity. This study contributes to theory by integrating behavioral dimensions with circular economy principles and offers practical guidance for policymakers and practitioners.

Current legislative frameworks reflect a societal consensus to prioritize sustainability, incentivizing industries to integrate environmental goals into strategic objectives. Embedding sustainability into product development requires appropriate methods and tools. Technological advancements enable the utilization and analysis of operational machine data to support the development of new generations of sustainable systems and the conduction of Life-Cycle-Assessments. This research presents a method to support data-driven product development to reduce the environmental impact of new product generations of complex mechatronic systems during operation, addressing key factors such as the technical system, organizational infrastructure, and regulations. The application of the method resulted in multiple proposed design changes able to enhance machine sustainability and operational efficiency.

Gene expression can be quantified using the sensitive technique of quantitative reverse transcription real-time polymerase chain reaction. Inter-sample variances can be minimised through normalisation with an appropriate reference gene. Bemisia tabaci, a significant insect vector of the Begomovirus family, transmits the Tomato Leaf Curl Bangalore Virus, for which there is a dearth of information regarding appropriate reference genes for autophagy. The viral load surpasses the vector’s capacity when autophagy is activated, which is also detrimental to whiteflies, particularly concerning virus translocation. To mitigate this vector using a double-stranded RNA approach, a precise measurement of gene silencing is required. For this investigation, normalisation of housekeeping or internal control genes is necessary. The present work utilised software tools such as geNorm, NormFinder, and BestKeeper to assess the suitability of five reference genes, namely, α-tubulin, β-tubulin, elongation factor, actin, and sucrose synthase, for gene expression studies in viruliferous and non-viruliferous B. tabaci. The analysis of the data showed that β-tubulin, which exhibits more stable expression, is the best-ranked reference gene. Furthermore, the reference genes were verified using the target gene expression of atg3 (an autophagy gene). The current findings enable precise measurement of gene expression in begomovirus-induced autophagy conditions of B. tabaci.

Rapid pace of change and increasing complexity in today’s world demand innovative approaches to product development. Foresight methods enable the anticipation of future scenarios and the derivation of product properties. However, current approaches lack mechanisms to continuously align product development with evolving environment and customer requirements, often resulting in late changes and high costs. Early detection of deviations is needed. This paper presents an approach for continuous monitoring, bridging strategic foresight and the product engineering process (PEP). By analyzing prior work and literature, a process model was developed to identify tipping points where product adaptations are necessary using indications and indicators. Initial evaluation through a case study using coffee machines showed the approach’s usability but improvement potential was also identified.

This study explores the design of a compatibility evaluation framework for integrating 3PL warehouse clients into semi-automated warehouse setups. Using Action Design Research (ADR), an artifact was developed that combines data-driven decision-making (DDD) and multi-criteria decision analysis. The framework, implemented in Microsoft Power BI, enables the evaluation of client compatibility based on configurable criteria and relevant metrics. It was co-created with stakeholders and tested using data from 33 warehouse clients, demonstrating its practical value in identifying operational fit while facilitating data-driven discussions. The study highlights the potential of structured decision frameworks in environments with limited data, offering generalizable insights for 3PL warehouses and similar contexts.

Biodegradability is often framed as an intrinsic material property. By integrating industrial design and soil science, this research examines how material design can actively support ecological reintegration. Through a case study of Polylactic Acid (PLA)—marketed as sustainable yet resistant to breakdown in everyday soil—we challenge how biodegradability claims misalign with real-world decomposition. To address this, we designed and tested 3D printing filaments, using compost respiration analysis to show that microbial engagement depends on material composition and environmental factors. We then introduce decayability as a novel affordance that supports microbial activity. By extending affordance theory beyond human perception, this study establishes a framework for designing materials that mediate interactions between human fabrication needs and nonhuman decomposition processes.