To increase the utilization rate of charging facilities and promote electric vehicles (EV), charging infrastructure should be built in a rational manner. The deployment strategy of public fast-charging stations (CS) determines whether charging demand can be met efficiently. Early CS planning has achieved some success. In the past, little is known about the charging behaviors and preferences of EV users, leading to a lack of relevance in the decisions made for the government-led CS construction. To address these issues, we used data on charging orders collected from public fast-CS s in cities for the summer and winter of 2023 to analyze charging user behavior patterns and build a more realistic model. Using queuing theory, we analyzed the facility size and operational metrics of public fast-CSs. Based on this, a capacity optimization model for public fast-CS was established to optimize the facility configuration of CSs by considering two factors: Investment cost and time cost. The optimal charging equipment configuration scheme for the public fast-CS is an 800 kVA charging box variable and 8 charging terminals, and the proposed facility scheme reduces the comprehensive cost by 28.1% and the user's dwell time by 41.16%. If more consideration is given to the experience of EV users, the number of charging terminals can be set to 9.

Purposeful human action theory and empirical task performance research inform our understanding of human action and how human action may be improved. The findings of these fields are often assumed to be generalizable across all areas of human activity. Several design theories, however, characterize design as a distinct regime of human action with ill-structured, wicked, and messy qualities. This perspective suggests that insights from other fields about purposeful action and task performance may not be applicable in design. This research addresses the gap between assumptions about human action uniformity across disciplines and design's distinctive characteristics as an ill-structured domain. We proposed analogical reasoning as both an operational framework and an explanatory mechanism for transposing theories from well-structured contexts to design contexts. We demonstrated this approach with two investigations: Testing Kirsh and Maglio's theory of epistemic and pragmatic actions in design contexts and exploring an approach to testing Bavelas's empirical performance studies in design contexts. Our results showed that while some principles of purposeful human action theory and empirical task performance research remain relevant in design contexts, they could also require substantial adaptation. Without adaptation, the findings of both fields may be inapplicable or even misleading when applied to design. We hope this research contributes clarity to the development of design theory as well as to theory applications in design research, education, management, and practice.

The rapid advancement of digital technology has markedly expanded its environmental footprint, emphasizing the critical need for sustainable and eco-conscious user experience (UX) design. This paper explores the intersection of UX design and sustainability, demonstrating how UX principles can encourage sustainable user behaviors and reduce digital waste. Through a targeted review of existing literature and an analysis of effective design principles, this study unveils actionable strategies for integrating sustainability into UX practices. Sustainable UX design extends beyond traditional usability, emphasizing energy efficiency, digital minimalism, and the promotion of eco-friendly interactions. Critical principles include designing for energy efficiency, enhancing product longevity, and utilizing methods such as gamification to foster sustainable behavior. Case studies from leading organizations - such as Google, Ecosia, and Dropbox - demonstrate tangible outcomes, including reductions in energy use and digital waste, providing measurable benchmarks for industry-wide adoption. While the advantages are compelling, challenges remain. These include technical constraints, user resistance, and difficulties in quantifying environmental impact. To address these issues, we highlight future directions such as integrating artificial intelligence and blockchain, and fostering interdisciplinary collaboration to drive innovation. Ultimately, this study positions sustainable UX design not as a fleeting trend, but as an essential progression toward a more accountable digital domain. By adopting these practices, UX professionals can lead the transition to low-impact digital solutions, cultivating eco-conscious UXs and contributing meaningfully to global sustainability efforts.

Probability, along with logic and fuzziness, has become an essential framework for studying and managing complex, uncertain, and dynamic processes across science, engineering, and society, particularly in an era marked by globalization, incomplete information, and rapid technological change. The present work continues and further develops the exploration of the category of “probability” in its application to the technical field, particularly in radio engineering and electronics, as previously explored by the authors. In this interpretation, the concept of “probability” is examined across various areas of human activity, rendering it relevant to a broad range of specialists engaged with random processes in their respective fields. This study analyzes the varying interpretations underlying the theoretical foundations and practical applications of probability, logic, and fuzzy systems. This variability arises from differing understandings of the philosophical meaning of probability and logic, the objective principles governing the interconnection of probabilistic and logical reasoning, and the formation of fuzzy set theories and associated engineering tools. These tools have become increasingly useful in implementing the life cycle of structurally complex long-range technical systems, particularly in fields such as energy, telecommunications, military, and space technology. Moreover, the theory of fuzzy multitudes and related engineering approaches has gained relevance in studying climate change and the environmental ecology surrounding humans. They help establish the current state and predict future trends in social systems, wildlife populations, and other complex, dynamic environments.

The rapid evolution of digital health tools and artificial intelligence has a transformative potential to improve mental health care access and delivery, yet people are often uninformed about their data. Privacy notices (or simply, “notices”) often fail to inform readers due to their length, complexity, and lack of accessibility. This study employs a value-sensitive design (VSD) approach to conceptually, empirically, and technically investigate how digital mental health notices can meaningfully inform their readers. Through a conceptual investigation, a conceptual model from prior VSD works was adapted to explicitly include the concept of meaningful consent. Honesty, helpfulness, universal usability, and privacy were the human values that were mapped to the different domains of the conceptual model for meaningful consent. Using these values as a framework, an empirical investigation and technical investigations were conducted to identify the values people associate with meaningful consent (empirical) and the tensions that exist between values in more innovative notice designs (technical). To identify the values and value tensions, 19 interviews were conducted with a diverse sample of past, present, and potential users of the Hope by Centre for Addiction and Mental Health suicide safety planning app to explore their views on meaningful consent. The findings from the empirical investigations added depth to the value definitions, where participants described honesty as “transparency,” emphasizing being upfront, straightforward, and candid. Helpfulness centered on simplifying notices and enhancing user experience and interfaces for better comprehension. Universal usability stressed equitable, compassionate design, while privacy required clear, formal choices (e.g., “yes” or “no”) in notices. The technical investigation identified tensions predominantly between honesty and helpfulness, where over-simple or over-complex designs can be received with skepticism. Based on these findings, this study provides recommendations for adjustments to existing guidelines for meaningful consent.

This study examines the implementation of the Da Vinci AI Tutor, an innovative artificial intelligence (AI)-based tutoring platform designed specifically for enhancing personalized and accessible learning in art history within higher education. Launched in Fall 2024 at a private liberal arts institution in the Midwest, the system integrates a conversational AI avatar modeled after Leonardo da Vinci, incorporating immersive virtual reality environments and multimodal interaction capabilities to engage students across undergraduate survey courses, advanced Renaissance classes, and graduate comprehensive exam preparations. Addressing significant gaps in existing humanities education research, the current study explores two primary research questions: (i) How AI-driven tutors can enhance student engagement, accessibility, and learning outcomes within the humanities; and (ii) what technical and pedagogical limitations arise when integrating such solutions. Initial findings indicate measurable improvements in student engagement, comprehension, and accessibility, positioning the Da Vinci AI Tutor as a promising model for scalable, adaptable instruction in higher education contexts. However, technical challenges such as avatar realism and system compatibility across various devices highlight areas for continued refinement. The results underscore both the theoretical potential of AI-driven tutoring solutions in humanities education and practical implications for managerial and policy considerations, including platform compatibility and ethical deployment.

Climate change is increasingly threatening human health, as rising global temperatures and more frequent extreme weather events intensify risks such as heat-related illnesses, respiratory problems, and vector-borne diseases. In response, this review examines the emerging field of climate-adaptive clothing systems, which offer innovative solutions to mitigate these health risks. Climate-adaptive clothing systems integrate advanced textiles, functional design features, and sustainable manufacturing practices. They aim to regulate body temperature, manage moisture, and protect against environmental hazards, enabling individuals to adapt to various climatic conditions. Central to these systems are thermoregulatory fabrics engineered to balance heat retention and dissipation in response to environmental changes. In hot climates, these fabrics incorporate moisture-wicking properties to cool the body, whereas in cold environments, they provide enhanced insulation to retain body heat. Additional features, such as integrated ventilation systems, ultraviolet protection, water resistance, and quick-drying capabilities, further improve the clothing's adaptability and performance under extreme weather conditions. The review also emphasizes the importance of sustainable practices in developing climate-adaptive clothing, focusing on eco-friendly materials and production methods to minimize environmental impact. By promoting thermal comfort, reducing thermal stress, and increasing resilience to climate variability, these clothing systems represent a promising strategy for enhancing human well-being in a rapidly changing world. Ultimately, this review highlights the potential of climate-adaptive clothing systems as a proactive approach to improving individual resilience to climate change when contributing to broader sustainability goals.

Pressurized shells with an obround cross-section are common components in the petrochemical industry. However, the analysis and design of obround components have been challenging due to their complex shapes. Empirical and numerical methods are commonly used for their analysis and design. In this study, the obround shape is divided into curved and straight segments to simplify the geometry and boundary conditions within each segment. The theoretical analysis of each segment was performed separately. By combining existing closed-form solutions, a theoretical solution was developed that partially satisfies the deformation at the junction of segments. This combined solution can accurately calculate stress and displacement in obround shells under internal pressure, representing a closed-form theoretical solution for pressurized obround shells. When the length of the straight segments approaches zero, the obround shell becomes cylinder, the proposed solution returns to the solution of cylindrical shell or Lame’s solution. The solution provides a new theoretical analysis approach that is simpler, more efficient, and more accurate than empirical methods or numerical analyses. It is expected to change the current reliance on empirical formulas and numerical simulations for analyzing obround components and to promote the development of a new design methodology for obround components.