Teams have been favored due to the diverse knowledge access. However, diversity can also have negative effects, and team outputs can be influenced by many factors, such as psychological safety. While the effects of psychological safety have been studied, its development has received less attention. Prior research in this area has focused either on specific populations or cross-sectional effects. To add to this area, this study examined the longitudinal development of psychological safety in engineering capstone students: how it evolves, and whether this can be influenced by team-related experiences. This study showed that although psychological safety did change meaningfully with time, neither time nor experience alone could capture the change. The results could shed light on the evolution of psychological safety, as well as what factors could potentially influence its development.

The blowgun is a weapon that employs the force of breath for expelling a projectile and has been traditionally used for hunting and (occasionally) war. The use of blowguns extends to ancient times and is advantageous in dense-forest areas of South America and South East Asia. A classification system of blowgun types introduced in 1948 for South America is extended here. We assembled a global database that includes collection data and ethnographic accounts of blowgun types and other related features that were linked to available linguistic information. Our analyses show that geography explains the distribution of blowgun types to some degree, but within regions of the world it is possible to identify cultural connections. Darts are by far the most used projectiles and in combination with toxins (e.g. curare), these weapons reach their highest potential. A case study on the use of blowguns in groups of Austronesian language speakers shows clade-specific preferences across the tree. Our comprehensive database provides a general overview of large-scale patterns and suggests that incorporation of other related data (e.g. sights, mouthpieces, quivers) would enhance the understanding of fine-scale cultural patterns.

In this article, the author develops an Islamic normative legal theoretical framework by using three key Islamic methodological approaches—(1) juridical theory of law (uṣūl), (2) legal maxims (qawāʿid), and (3) purposive-based theory (maqāṣid)—in light of Ronald Dworkin’s notions of rules, principles, and policies, respectively. While uṣūl is used to develop rules, qawāʿid and maqāṣid provide the normative values that govern rulemaking. In addition to presenting a coherent model of Islamic normative legal theory, the author examines legitimacy issues of Islamic law that relate to links of rules to sharīʿa revealed texts and applies the Islamic normative legal theoretical framework to contemporary rulings on the environment, organ transplants, and Islamic finance. The case studies show that using the integrated normative framework would yield more ethical rulings than those that focus on juridical methods (uṣūl) only. The author argues that while the extent of legal legitimacy can vary across different rulings, the application of the Islamic normative legal framework ensures normative legitimacy in all cases, ensuring the moral character of Islamic law.

Design by Analogy (DbA) is a powerful method for fostering innovation by transferring knowledge from a source domain to solve problems in a target domain. However, traditional DbA approaches face significant challenges, including resource-intensive database management, linguistic and representational differences across domains, and the complexity of access and mapping processes. These limitations hinder scalability and efficiency, particularly for cross-domain analogies. Recent advancements in Artificial Intelligence (AI), especially Large Language Models (LLMs), offer promising solutions by facilitating efficient knowledge retrieval, bridging linguistic gaps, and enhancing semantic reasoning. This paper explores the potential of AI technologies to address these challenges, proposing a framework for analogical reasoning.

This paper challenges a false dichotomy between subjectivity and objectivity in understanding the nature of human social relationships. I argue that social relationships are composed of both subjective and objective components, which are inherently interdependent. They are influenced by biological properties and subject to evolutionary processes, yet they cannot be reduced to them. I use emerging research on kinship as an example that showcases the appeal of this integrated approach. This paper takes a step in the direction of a unified account of sociality, contributing to a more comprehensive understanding of human social behavior.

Given the rise of Generative AI and Large Language Models (LLMs), there is a high interest in their use also in engineering design domain. Current research approaches lack to leverage LLM's new orchestration capabilities and use the LLMs in ways that expose their inherent weaknesses. We present a conceptual model to visualize the contribution of LLMs to design tasks and distribute ownership in the design activities: the triangle of design responsibility. A literature review on the design engineering field presents its current uses in this community. The understanding of the model is validated with industry via survey. We identify future research directions in the field of complex product design. We hope that this model helps design automation developers, researchers and industry practitioners to position and assign responsibility effectively in their design automation implementation.

Uncertainty in coping with sustainability demands poses a challenge to decision makers concerned with manufacturing companies’ product engineering. Therefore, our paper reports on a newly developed guide to address their uncertainty and support them in initiating targeted sustainability action. The guide, based on an interview study (n = 25; 4 company cases and 1 consultancy) and a systematic literature review, addresses decision makers in product engineering and beyond. It was initially applied and evaluated in company workshops. The guide provides success criteria and reflection questions for each step toward targeted sustainability action: understanding, operationalizing, and implementing. This paper outlines the main concepts behind the guide and contributes to the literature by suggesting a novel approach to sustainability action in product engineering by addressing uncertainty.

While performing design tasks, engineers rely heavily on their knowledge. However, the expanding knowledge space makes it impractical to perform the design tasks without external inputs. This study explores how AI can bridge the knowledge space expansion gap in design. The study introduces the AICED framework implemented as a web tool Pro-Explora, leveraging advanced multi-agent LLM technology to accelerate early-stage design tasks. Pro-Explora generates professional problem definitions, PDS documents, and unique solution concept images within five minutes, maintaining creative flow. Its effectiveness was validated in a real-life project, with outputs deemed highly relevant by experienced designers. The study highlights the AICED framework’s industry implications, addressing required knowledge. This pioneering study opens new avenues for specific LLM applications in engineering design.

The evolving needs of customers and stakeholders necessitate the collaboration of diverse system elements within a cyber-physical, socio-technical network. Such Sociotechnical systems are characterized by numerous complex interdependencies as well as by endogenous and exogenous influences. A key issue that developers must address is the mitigation of data and information uncertainties. This paper introduces an ontological approach to facilitate the identification and mitigation of uncertainties in data and information within a model-based methodology for satellite development projects. The work outlines the results of preliminary studies forming the foundation for this ontological concept. The proposed approach comprises an overarching General Ontology, complemented by a Uncertainty and Structure Ontology, creating a framework for uncertainty management in satellite development.

Increased interest in space exploration demands a shift in the design and manufacturing of space systems. Traditionally, space structures are limited by constraints associated with launch systems that affect cost, volume, and mass. The concept of Factory in Space (FIS) proposes the fabrication of systems in space to circumvent the launch constraints. FIS offers a transition to a circular economy in space by minimizing resource consumption and creating a self-sustaining factory ecosystem. This paper evaluates the role of circular design in FIS. Circular design in FIS leads to a reduction in design complexity and modular designs that could enhance space exploration. Material selection, modular design, design for robustness, and lifecycle thinking are highlighted as factors that influence design for circularity in FIS. Finally, the challenges associated with circularity in FIS are presented

The development of smart Product-Service Systems (smart PSS) introduces unique challenges for requirements management due to their dynamic, data-driven, and multidisciplinary nature. This paper investigates methods and principles for data-driven requirements management, emphasizing lifecycle alignment, data utilization, multidisciplinary collaboration, and customer-centricity. A systematic literature review forms the basis for assessing 16 existing frameworks, focusing on their suitability for the data-driven design of smart PSS. Key gaps are identified in areas such as data planning, lifecycle integration, and the handling of system-level requirements. To address these challenges, this study proposes principles for data-driven requirements management that leverage real-time data, ensure traceability, foster interdisciplinary alignment, and adapt to contextual variables.

The process of gathering needs and generating requirements for design for individuals with special needs can be particularly challenging, and the intended solutions are increasingly evolving into Cyber-Physical-Social Systems (CPSS) further complicating the task. Co-design is the preferred approach but when the primary users are children, the challenges are compounded since they are unable to partner in the design process making the task of eliciting needs further difficult. This paper presents an empirical attempt to collate a master list of requirements for design for children with special needs to aid the design process. The study revealed several lacunae in comprehensibility of Requirements and Criteria, and mapping of the two, prompting further investigation into the hindrances to developing a robust and comprehensive resource for designers by designers.

This study applies Artificial Intelligence-Generated Content (AIGC) to design cultural products inspired by Sanxingdui, an ancient Chinese civilization famed for mystical bronze artifacts. Addressing the challenge of merging tradition with modernity, an AIGC framework automates cultural element extraction, generates design concepts, and optimizes aesthetics using generative models. Comparative analysis via Quality Function Deployment (QFD) shows AIGC products achieve higher user satisfaction in aesthetics, symbolism, and engagement. The research highlights the significance of AI in enhancing creativity, efficiency, and cultural preservation, despite algorithmic limitations. It provides actionable strategies for integrating AI into cultural industries, bridging heritage and technology to drive sustainable innovation.

The article presents the techno-typological analysis of a large bone arrow point assemblage recovered at different sites from the Late period of Sierras de Córdoba, Argentina (around 1220–330 cal BP). These bone arrow points exhibit a wide range of morphology and sizes. We classified them into typological groups or subgroups according to their morphology. Basic attributes (weight, length, neck width, blade width, thickness, angle of barbs, etc.) were measured to roughly assess the mass, velocity, and capability for tissue damage of bone-tipped projectiles. Bone arrow points were part of a specialized mechanism system designed to severely wound enemies or occasionally finish off prey from a short distance, creating more serious bleeding wounds than the smaller, easy-to-make chipped-stone arrow points that dominated late-period assemblages. Our analysis shows that the adoption of a broad-spectrum foraging and cultivation base around 1220 cal BP was accompanied by the development of new types of weapons for hunting and warfare. The design of the bone projectile points is consistent with a period during which social tensions increased across the Sierras de Córdoba, with clear evidence of physical violence.