Design Recommendations Research Articles

To investigate how rigid head motion interacts with 3D MRI k-space sampling strategies and to introduce motion-sampling plots as a framework for predicting motion artifacts. We evaluated a range of motion-sampling combinations across three sampling trajectories (Cartesian, stack-of-stars, kooshball) in both simulation and in vivo. Experiments included shifting motion states in k-space, changing the direction of motion with regards to the sampling, and varying the magnitude of motion. In vivo experiments were conducted on healthy volunteers mimicking patient motion while wearing a real-time pose-tracking device. Motion-sampling plots were used to map motion states directly onto k-space and assess their relationship to artifact appearance. Nine categories of motion artifacts were identified. The severity and nature of artifacts were found to depend heavily on the k-space distribution of motion states. Motion-sampling plots were seen to work as guides in predicting artifact appearance. In vivo findings supported simulation results. Artifacts were especially pronounced when motion discontinuities occurred near the center of k-space or aligned with slow phase-encoding directions. Motion-sampling plots offer an effective way to visualize and interpret motion artifacts in 3D MRI, providing insight beyond traditional motion-time plots. This framework enables systematic evaluation of motion robustness and can guide the development and validation of motion correction techniques. We propose practical recommendations for motion experiment design to improve reproducibility and benchmarking in MRI research.

As patient diversity continues to expand, nursing staff are increasingly required to support neurodivergent individuals, particularly in the context of diabetes care. This article explores the principles of neurodiversity and outlines how nurses can provide informed, inclusive support to both patients and colleagues across various healthcare settings. It considers communication techniques, sensory considerations, environmental design, and policy recommendations. A key focus is placed on strategies for behaviour change, managing comorbid conditions, and tailoring diabetes care to individuals with specific learning differences. Consistent communication plans, reasonable adjustments, and multiagency collaboration have been shown to significantly enhance care outcomes. There is a need for increased recognition of neurodiversity within nursing education and practice environments. Embracing neurodiversity fosters more equitable, person-centred care and supports nursing staff in delivering high-quality services.

The design of fallout shelters is located at the intersection of many disciplines, so this is a multifaceted challenge with a high level of engineering complexity. Nonetheless, it should be considered as part of sustainable development in a broader sense—as an investment in the resilience of the urban infrastructure, the safety of the population and the continuity of the city functioning in crisis situations. One can identify the research gap indicating a lack of contemporary model solutions for shelters and this article aims to fill this gap. A comparative analytical method with an interdisciplinary approach based on a comparison of 10 existing shelter infrastructure solutions in different parts of the world was proposed. Supporting research aspects were formulated and synthetically represented in table: (A) functional integration into the city; (B) minimisation of impact on the urban fabric; (C) self-sufficiency and renewability of resources; (D) inclusiveness vs. exclusiveness. The analysis show that the existing model of the shelter as a segregated exclusive military facility does not fit the contemporary world. The result is a set of practical design recommendations based on case studies that could provide a starting point for the development of the New Fallout Shelter Standard (NFSS) for urban shelters as a sustainable civil resilience infrastructure in the 21st century.

Purpose This study explores how digital exclusion impacts citizen engagement with e-government services in China, particularly among non-local (migrant) populations. Through surveys and interviews, this study will explore migrants' experiences of digital exclusion and its effects on empowerment and service satisfaction. It will also provide empirical insights into whether e-government enhances social belonging or deepens exclusion in China. Design/methodology/approach A mixed-methods approach combined quantitative surveys (N = 450) with qualitative interviews (N = 60). The study integrates the technology acceptance model (TAM), digital divide theory and empowerment theory to examine the hypotheses. Findings Results indicate that the digital divide reinforces social inequality, with older, less-educated and migrant users experiencing greater difficulty accessing digital public services. Perceived ease of use and usefulness significantly influence satisfaction and intention to use e-government services. Government responsiveness and expectation confirmation are critical in fostering psychological, social and political empowerment, particularly for migrants who rely more on digital platforms but do not have access. Originality/value This study contributes to the e-government studies within the public administration discipline by integrating digital empowerment theory with the technology acceptance model into a novel conceptual proposal that is empirically tested by focusing on the lived experiences of the migrants in China. It offers practical recommendations for inclusive digital governance design to ensure equitable access and engagement across diverse user groups.

This article explores essential principles and practices in assessing the four main language skills—writing,reading, listening, and speaking—as well as integrated language skills. It emphasizes the importance ofvalid, reliable, practical, and authentic assessment methods that reflect real-life language use and promoteeffective learning. The study also discusses the washback effect, highlighting how well-designed assessments can positively influence both teaching and student motivation, particularly at the C1 proficiency level.Practical recommendations for test design, scoring, and rubric development are presented to guide teachersin creating meaningful and fair language assessments.

Background: The modified Blalock-Taussig-Thomas shunt (mBTTS) is a critical palliative procedure for infants with single-ventricle physiology, but thrombosis-related occlusion affects 8-12% of cases and carries nearly 50% mortality. Meanwhile, existing antithrombotic strategies fail to address the hemodynamic factors driving thrombosis, highlighting the need for a deeper understanding of flow dynamics in shunt failure. Research Question: Can engineering principles inform and optimize procedural interventions to reduce flow-mediated platelet activation and subsequent aggregation? Aims: This study aims to identify how mBTTS geometry influences hemodynamics and thrombosis risk, providing quantitative guidance for surgical planning and shunt design optimization. Methods: We used patient-specific imaging data to construct 54 idealized mBTTS configurations, systematically varying key geometric factors; pulmonary artery diameter, shunt diameter, and insertion angle. Using computational fluid dynamics, we analyzed how these variables influence wall shear rate (WSR), elongational strain rate (ESR), and turbulence intensity (TI); hemodynamic parameters known to affect thrombosis risk, to identify patterns linked to thrombosis. Results: We computationally identified optimal geometric configurations. Peak Wall Shear Rate (WSR) and Elongational Strain Rate (ESR) were primarily located at bifurcation points, while peak Turbulence Intensity (TI) was concentrated within the shunt channel. Shunt insertion distal to the right carotid artery with a 60° insertion angle and with a 4.0mm shunt graft demonstrated the most favorable hemodynamic profiles to prevent clots. Statistical analysis confirmed strong correlations between geometric parameters and flow characteristics. Conclusion: Results provide a framework for optimizing mBTTS design to reduce thrombosis risk based on hemodynamic risk factors, including actionable recommendations for shunt placement and design. These insights provide a foundation for hemodynamically guided surgical interventions with potential to improve survival rates in this high-risk patient population and for broader applications in cardiovascular surgery.

The increase in cases of social isolation and loneliness among the elderly is a topic of concern and often occurs worldwide and in Bangladesh itself, as this trend is affected by such demographic changes as the variety of social bonds within a family unit. The paper is a qualitative piece of research that investigates the relationships between the ageing phenomenon, technology, and social network connectivity through interviews among older adults in rural and urban territories. By analysing the data thematically and decomposing visual data, the study determines the most important issues that lead to people feeling lonely, and assesses the perception and uptake of digital interventions by older people. The results show that though most of the elderly people are willing to interact with technology, physiological concerns and technological barriers curtail effectiveness. Nonetheless, technology has the potential to become a very useful resource in improving well-being and overcoming isolation through focused training, community acceptance, and design. This research paper ends with policy, design, and social framework recommendations that can narrow the digital divide gap and enhance the living standards of senior adults in Bangladesh.

Purpose This paper aims to provide product design recommendations for electric vehicle supply chains (EVSCs) to improve market penetration in cold regions amidst growing market competition. Design/methodology/approach Based on two green product design approaches, we propose two electric vehicle (EV) designs with distinct cost structures: power battery expansion (Scheme N) and cold-resistance R&D (Scheme R). From a product design perspective, we consider the characteristics of the EVSC and use game theory to develop a dual oligopoly supply chain (SC) model under joint competition in price and range. By introducing range as a decision variable, we comprehensively analyze the effects of range anxiety, low temperature coefficients, production and R&D capabilities and competitive intensities on optimal solutions for firms. Findings The findings of the study are as follows: (1) the applicability and advantages of Scheme R increase as the gap between joint competition intensities narrows. High levels of range competition are consistently detrimental to the EVSC, as they hinder improvements in EV range and may reduce profits when consumer range anxiety is mitigated. (2) R&D capability significantly influences the choice of the optimal scheme. Scheme N should be selected only when R&D capabilities are limited and optimal cold-resistance performance is low. Unexpectedly, in colder temperatures with higher consumer anxiety, consumers tend to prefer purchasing EVs under Scheme N. Originality/value This study extends the green SC research by incorporating the specific needs of EVSCs and exploring the competitive dynamics of products with different structural approaches within the same market.

Background: Outdoor nighttime mass gatherings pose challenges for OHCA responses. While drone AED delivery shows promise in daytime (Jakobsen et al., 2024), this study’s major objective was to compare the feasibility (flight performance) and safety of manual AED drone deliveries (incident rates) by paramedics during daytime versus nighttime. Only one prior study (Scholz et al., 2023) evaluated automated nighttime operations, leaving manual flights understudied. Methods: (Update) A quasi-experimental within-subjects trial was conducted in Hong Kong’s High Island Reservoir (semi-urban, light-pollution-free) from January–March 2024. Twelve advanced-certified paramedic pilots (mean age 34 ± 5.2 years, 10 male, 2 female) manually operated a DJI M30T drone (3.9 kg) equipped with infrared/night vision, strobe lights, and a 480g AED across 800m during 12 daytime and 12 nighttime flights. The sample size of 12 per group followed the pilot study design recommendation (Julious, 2005) Primary outcomes were flight time (seconds) and incident rates; exposure was time-of-day (day/night). Flights followed EVLOS protocols with safety officers. Paired t-tests compared flight times; chi-square assessed incident differences. Ethical approval was obtained from Hong Kong Metropolitan University and under the approval of the Hong Kong Civil Aviation Department. Results: All 24 flights (12 pilots × 2 conditions) concluded without incidents or obstacle triggers. Mean flight times were 136 ± 8.71s (day) vs. 139 ± 14.16s (night), with an unadjusted mean difference of 3.92s (95% CI: -6.1 to 13.9; p=0.43; Cohen’s d=0.24). Incident rates did not differ (0% vs. 0%, p>0.05). Paramedics Pilots reported comparable situational awareness during nighttime operations, attributing confidence to infrared navigation and strobe lighting systems. Conclusions: Manual nighttime AED drone delivery with lights is feasible and safe, with performance parity to daytime. Infrared technology and trained paramedic pilots enable scalable 24/7 deployment, potentially reducing OHCA mortality disparities. Findings directly support integrating drones into mass-gathering emergency protocols. Future full scale studies should validate findings.

Nan Province has an elderly population proportion of 26.64%, prompting the provincial government to introduce the “Healthy City” policy as a model for developing public buildings with environments and facilities that are inclusive and suitable for everyone. As people age, their bodily functions deteriorate, leading most elderly individuals to suffer from chronic illnesses and require regular medical visits. This results in a high proportion of elderly patients in outpatient departments. Due to the typically long waiting times during hospital visits, elderly patients often need to use the restroom. However, mobility issues and balance problems common in this age group increase the risk of accidents enroute to the facilities. This study was therefore conducted to investigate the factors that create obstacles in restroom usage among elderly outpatients at Nan Hospital, in order to propose suitable facility arrangements aligned with the physical environment. The objectives of this research were to identify the barriers elderly patients face in restroom use within the outpatient department and to recommend appropriate supportive facilities tailored to the needs of the elderly. The research question guiding the study was: "What are the appropriate design details for supportive facilities that accommodate restroom use for elderly patients in outpatient departments?" The study was based on the conceptual framework that age-related musculoskeletal degeneration contributes to balance issues. When combined with long walking distances and crowded spaces, these factors can increase the risk of restroom-related accidents. Providing suitable facilities can help mitigate these risks in crowded outpatient areas. The research employed a mixed-methods approach, collecting both qualitative and quantitative data through a questionnaire administered to 285 elderly outpatients at Nan Hospital. The study was conducted in a natural setting without controlling environmental variables. Descriptive statistics, including frequency, percentage, and mean, were used for data analysis. Additionally, a chi-square statistical method was applied to examine the relationships between variables, leading to evidence-based recommendations for appropriate facility design. The findings revealed two primary barriers to restroom use among elderly outpatients: 1) Insufficient number of restrooms, especially for women. The number of women's restrooms was half of the required standard, resulting in overcrowding due to the higher proportion of female users. 2) Excessive walking distance between waiting areas and restrooms. In some areas, elderly patients had to walk 52.67 to 62.00 meters, which is particularly problematic for individuals with mobility or balance issues. Inadequate signage and poor restroom visibility also contributed to confusion and increased risk of falls, especially considering the reduced walking speed among the elderly. To address these challenges, it is recommended to install additional waiting seats or rest areas near restrooms. These would provide elderly patients a place to sit while waiting to use the facilities during peak times and help relieve muscle fatigue from prolonged standing or walking. Such measures enhance convenience and reduce fall risks. The seating should be robust, corrosion-resistant, moisture-resistant, capable of supporting weight safely, and designed to ensure user safety. Furthermore, walking paths should remain wide and unobstructed to accommodate safe movement.

This study deals with the finite element method-based simulations of a textured surface, two-lobe journal bearing operating with a magnetorheological (MR) lubricant—a smart fluid composed of fine magnetic particles suspended in a carrier fluid. The flow of the MR lubricant within the textured bearing, which incorporates rectangular micro-grooves along axial directions, is modeled using Reynolds’ equation. The Bingham plastic model defines the MR fluid's viscosity, accounting for the influence of yield stress, magnetic field, and shear-strain rate. The Reynolds equation is solved using the finite element method to determine film pressure, film direct stiffness coefficients, threshold speed, journal trajectories and limit cycles. A Multi-Objective Genetic Algorithm (MOGA) is used to optimize rectangular micro-groove attributes (i.e., number, width, depth and length) to maximize the direct film stiffness coefficients and threshold speed of stability. A robust design recommendation is proposed based on Fuzzy-based Multi-Objective Genetic Algorithm (Fuzzy-MOGA) optimization, targeting improved film stiffness coefficients and threshold speed. The results exhibit a stable and resilient optimization landscape, with minimal sensitivity to input variations. The numerical results demonstrate that the combined use of MR lubricant, two-lobe geometry and surface texturing enhances stiffness coefficients (116.7%∼850.8%) and threshold speed (81.3%). The two-lobe bearing with partial surface texturing in the leading half demonstrates the highest dynamic stability, as evidenced by threshold speed, minimal journal center trajectories and compact limit cycles.

Optimizing flexural ductility and mitigating crack localization in UHPC beams: Experiments, prediction, and design recommendations

This conceptual paper presents a multidimensional framework for applying affordance theory to language education, moving beyond traditional, linear models. Drawing on ecological and rhizomatic perspectives, the framework views affordances as context-sensitive opportunities for action, shaped and enacted by learners, and analyzed across five key dimensions: perceptibility, learning valence, compositionality, normativity, and intentionality. The article outlines pedagogical demonstrations to guide language teaching and learning, introducing three progressive levels for implementing affordance-based language education. It then explores research principles for studying affordances in increasingly complex, technology-rich environments. Readers are provided with practical strategies for capturing affordance dynamics and recommendations for research designs that support relational and emergent inquiry. Finally, the article discusses key methodological challenges that arise when teaching, learning, and researching from an affordance-based perspective. This approach promotes more adaptive, equitable, and learner-centered practices in contemporary language education by equipping educators and researchers with clear theoretical and analytical tools.

This research on architecture examines the challenges faced by individuals with visual impairments as they navigate schools and other built environments. It highlights the idea of "architectural visual bias," which favors sight over other sensory experiences. The study promotes architectural designs that go beyond visual considerations to enhance sensory interactions, ultimately aiming to make spaces more accessible to those with visual impairments. The objective is to identify the requirements of visually impaired individuals in the built environment, propose design principles and recommendations for inclusive architecture, and create a design for Pacelli School for the blind and partially sighted that embodies inclusive architectural design principles. A qualitative approach, including observations, interviews, and case studies, demonstrated how tactile surfaces, auditory signals, and olfactory cues enhance spatial awareness, stressing the importance of refining urban and architectural designs to support independent mobility in everyday activities for the visually impaired. The research indicates that such designs should employ strategies such as tactile feedback, sound indicators, and careful consideration of form and function to improve safety, mobility, and orientation for students. It illustrates why designers should integrate multisensory architectural principles to promote inclusivity. The study wraps up by urging professionals to follow universal design principles and other relevant guidelines that accommodate a range of abilities, ensuring that designs are not just accessible but inclusive for everyone.

Virtual reality (VR) is increasingly adopted for collaborative teaching and learning, enabling immersive and interactive experiences. As Artificial Intelligence (AI) tutors begin to take on roles alongside human instructors, it becomes crucial to understand how their integration influences interaction dynamics and role perception in these settings. This study investigates the role of Embodied Virtual Agents (EVAs) substituting human instructors in virtual training, specifically addressing the previously underexplored issue of EVA appearance consistency with instructors in Human-Agent Teaming (HAT). We recruited 21 participants to compare three conditions: No Agent, Shared-Appearance (SA) EVA, and Unique-Appearance (UA) EVA, where an EVA substitutes for the instructor during temporary absences. We evaluated collaboration efficiency, user perception/preference, and HAT dynamics. Our findings confirm that EVAs significantly enhance task efficiency compared to no support and reveal a key trade-off regarding appearance: SA fosters perceived continuity and trust but risks ambiguity and uncanny effects, while UA provides transparency and role clarity but may disrupt experiential coherence. These results have implications for designing dynamic HAT systems where control may shift. We discuss the benefits and limitations of each approach and offer design recommendations for future mixed-agency interfaces.

Parametric studies and design recommendations for a novel hybrid battery thermal management system with ultrathin PCM layers between liquid cooling channels and batteries

In the face of increasing Polish and EU requirements for climate neutrality, the role of digital technologies in the design and operation of buildings is gaining strategic importance. This paper presents the integrated use of Building Information Modelling (BIM) and the Digital Twin concept in the context of selecting, modelling, and optimizing renewable energy sources (RES) in architectural structures. The analysis covers: (1) key tools and data exchange formats, (2) capabilities for dynamic simulations of energy consumption and production, and (3) the impact of digital twins on predictive management of PV installations, heat pumps, and micro wind turbines. A case study demonstrates the potential for a 32% reduction in CO2 emissions over five years through the integration of BIM and Digital Twin. The results indicate that the synergistic use of both technologies reduces the time required for RES scenario analysis by half and increases the accuracy of energy production forecasts by 15%. The paper concludes with recommendations for designers, investors, and researchers, emphasizing the need for tool interoperability and standardization of energy data.

In-vehicle voice assistants (VAs) can potentially enhance driving safety and user experience. However, their success depends on trust and acceptance. This study explores two influencing factors: (1) design-based and (2) performance-based attributes. In a driving simulator study, N = 53 participants engaged with VAs varying in anthropomorphic appearance and response latency. Results indicate that neither factor universally enhanced trust or acceptance. Instead, a nuanced interaction emerged: When response latency was short, anthropomorphic appearance had no impact. However, when response latency was long, both the non- and high-anthropomorphic VA were rated as more trustworthy than a low-anthropomorphic VA. Additionally, participants rated the high-anthropomorphic VA equally trustworthy across both latencies, suggesting a potential buffering effect of anthropomorphism under suboptimal performance conditions. Furthermore, trust fully mediated the relationship between the factors and acceptance, supporting models that conceptualize trust as a precursor of acceptance. Based on these insights, design recommendations were derived.

This study presents a comprehensive analysis of soft finger actuators using finite element modeling to assess their performance in various structural configurations. By conducting detailed numerical simulations, we explore how variations in structural parameters influence the bending angle, thereby guiding iterative design improvements. Specifically, the research examines the impact of critical design factors, such as the number of bellows, actuator height, surrounding thickness, and foot thickness, on the bending behavior of soft actuators. The objective is to optimize these actuators for use in rehabilitation training gloves, where precise motion control is para-mount. Our findings reveal that increasing both the height and the number of bellows significantly enhances the achievable bending angle, facilitating more effective rehabilitation exercises. In contrast, greater foot and surrounding thicknesses exhibit a restrictive effect on bending, underscoring the need to carefully consider these parameters in design processes. These insights are instrumental in formulating design guidelines that aim to optimize actuator performance in therapeutic applications. Crucially, the manuscript presents a rigorous comparison between the experimental results and simulation results, demonstrating a high degree of concordance that validates the FEM approach and the predictions of the neural networks. This close match between the observed and predicted data not only confirms the reliability of the simulations, but also enhances the credibility of the design recommendations for rehabilitation applications. Furthermore, the study uses artificial neural networks to predict bending angles with high precision. With a residual variance of just 0. 74% and an explained variance of 99. 26%, the neural network model demonstrates exceptional predictive capacity, highlighting its potential as a tool for further refinement of the design and optimization of the performance of soft actuators. This research not only advances our understanding of soft actuator mechanics, but also contributes to the development of more effective rehabilitation technologies.

The Smart House Planner is an AI-powered solution designed to simplify the process of residential home design by combining intelligent planning, 3D modelling, and real-time cost estimation through an interactive conversational interface. With the rising demand for personalized housing solutions and the complexity of balancing aesthetics, functionality, and budget, there is a growing need for systems that can automate architectural planning while remaining user-friendly. This project addresses that challenge by integrating Gemini AI for intelligent design recommendations, Blender for automated 3D visualization, and a cost estimation engine for transparent financial planning. The system enables users to specify requirements such as housing type (1BHK, 2BHK, 3BHK, Duplex, Villa), dimensions, and style preferences via a modern Django-based web interface. Gemini AI processes these inputs to generate optimized layouts by considering space utilization, and functional flow. These layouts are then transformed into realistic, interactive 3D models using Blender, allowing users to explore their prospective homes virtually. Simultaneously, the cost estimation module calculates material, labour, costs, producing downloadable reports that support informed decision-making and budget control. By unifying AI-driven design intelligence, real-time 3D modelling, and detailed cost breakdowns, Smart House Planner provides a comprehensive platform that enhances user engagement, reduces reliance on professional intervention, and democratizes access to architectural planning. This solution demonstrates how AI, visualization technologies, and web-based interfaces can transform the way individuals approach housing design, making the process more efficient, transparent, and accessible to both professionals and non-experts.