Search Results (392)

Against the dual backdrop of rapid population aging and legacy neighborhood renewal, morphologically planning-locked legacy neighborhoods in high-density cities face persistent imbalances in outdoor activity spaces that undermine aging-in-place participation and health equity. This study advances a Spatial Pathology framework. Using nine representative communities in Longtan Subdistrict, Dongcheng District, Beijing, we develop a GIS-assisted spatial audit, a systematic behavioral observation protocol with temporal-intensity metrics, and a validated perception instrument. These tools form a closed evidentiary loop with explicit indicator definitions, formulas, and decision thresholds, alongside a reproducible analytic and visualization pipeline. Tri-dimensional baselines revealed substantial inter-community disparities: Spatial Quality Index (SQI) ranged from 43.3 to 77.0; activity intensity varied from 1.5 to 15.7 persons/100 m²·hour; and overall satisfaction scores spanned 3.88–4.49. It quantifies and identifies three core paradoxes in outdoor activity spaces within this context: (1) the Functional Failure Paradox with FFI exceeding +0.5 and ELR surpassing 60% in dormant communities; (2) the Value Misalignment Paradox where Facilities & Equipment showed the strongest satisfaction impact (β = 0.344) yet the largest unmet-need gap (VQGI > +8); (3) the Practice–Perception Decoupling Paradox evidenced by a negative correlation (r = −0.38) between usage intensity and satisfaction. These paradoxes reveal the spatial roots of planning-locked legacy neighborhoods—compound mechanisms of planning inertia, decision–demand information gaps, and elderly adaptability masking environmental deficits. We translate the diagnosis into typology-specific prescriptions—reactivating dormant spaces via “route–node–plane” continuity and proximal micro-spaces; decongesting peak periods through elastic zoning and equipment redistribution; and precision calibration of facilities and walking loops—implemented through co-creation and light-touch stewardship. This provides evidence-based, precision-targeted intervention pathways for micro-renewal of aging neighborhoods, supporting localized implementation of UN Sustainable Development Goals (SDG 11 Sustainable Cities; SDG 10 Reduced Inequalities). This methodological framework is transferable to other high-density aging cities, offering theoretical scaffolding and empirical reference for multi-source geographic data-driven urban spatial analysis and equity-oriented age-friendly retrofitting. Full article

Amidst the paradigm shift in park city development from quantitative metrics to spatial performance, urban complex parks—a novel green space type developed privately yet fulfilling public functions—present an innovative approach to park provision in high-density urban areas. However, systematic empirical evidence on their social value remains scarce. This study characterizes urban complex parks as a new form of green public space that provides key ecosystem services and proposes a three-dimensional evaluation framework integrating “usage vitality, place attractiveness, and user satisfaction.” Analyzing 19 park-equipped complexes among 75 cases in Shanghai using LBS data and online reviews through controlled linear regression and comparative analysis, our results indicate complexes with parks were associated with significantly outperforming others in place attractiveness and user satisfaction. Key findings include associations with a 413.7 m increase in average OD distance, a 3.4–4.0% higher city-level visitor share, and 5.24 percentage points greater median positive review rate. Crucially, spatial location outweighs green ratio and size in determining social value. Ground-level parks, through superior spatial integration, function as effective “social-ecological interfaces,” significantly outperforming rooftop parks in attracting long-distance visitors, stabilizing foot traffic (≈3% lower fluctuation), and enhancing per-store visitation. This demonstrates that green space quality (experiential quality and spatial configuration) matters more than quantity. Our findings suggest that urban complex parks can create social value through perceivable naturalness and restorative environments, providing an empirical basis for optimizing park city implementation in high-density contexts and highlighting the need to reconcile broad attractiveness with equitable local access. Full article

This paper addresses the challenge of optimizing cloudlet resource allocation in a code evaluation system. The study models the relationship between system load and response time when users submit code to an online code-evaluation platform, LambdaChecker, which operates a cloudlet-based processing pipeline. The pipeline includes code correctness checks, static analysis, and design-pattern detection using a local Large Language Model (LLM). To optimize the system, we develop a mathematical model and apply it to the LambdaChecker resource management problem. The proposed approach is evaluated using both simulations and real contest data, with a focus on improvements in average response time, resource utilization efficiency, and user satisfaction. The results indicate that adaptive scheduling and workload prediction effectively reduce waiting times without substantially increasing operational costs. Overall, the study suggests that systematic cloudlet optimization can enhance the educational value of automated code evaluation systems by improving responsiveness while preserving sustainable resource usage. Full article

Background: Rising obesity rates among young adults increase long-term health risks, especially cardiometabolic conditions such as type 2 diabetes mellitus. Digital interventions can offer scalable solutions to promote and support healthy behaviors by integrating personalized diet, physical activity promotion, and behavioral support. Objective: To assess the feasibility, user friendliness, adherence, and satisfaction of the Healthy Lifestyle Recommender System (HLRS). Secondary outcomes will include measures of metabolic health and obesity. Methods: A 3-month, single-arm pilot study conducted across European countries, including Bulgaria, Germany, Italy, Netherlands, Portugal, and Spain, enrolling 351 young adults (18–25 years old, BMI 18.5–29.9 kg/m²). The intervention includes a mobile app for meal planning (Nutrida v.1), gamified physical activity encouragement (GameBus), and real-time monitoring via a wearable smartwatch device. Primary outcomes are adherence and engagement, measured through app usage and participant feedback; secondary outcomes include anthropometry, physical activity, dietary patterns, psychological well-being, and selected biomarkers of metabolic health. Expected Outcomes: Improved engagement is expected to enhance lifestyle behaviors, supporting weight management and overall well-being. Findings will guide future large-scale interventions. Conclusions: This study will contribute to minimizing the impact of obesity in Europe. Full article

The integration of large language models (LLMs) into project-based learning (PBL) holds significant potential for addressing enduring pedagogical challenges in engineering education, such as providing scalable, personalized support during complex problem-solving. Grounded in Self-Determination Theory (SDT), this study investigates how different LLM usage strategies impact student learning within a blended engineering geology PBL context. A one-semester quasi-experiment (N = 120) employed a 2 (usage mode: individual/shared) × 2 (interaction restriction: restricted/unrestricted) factorial design. Mixed-methods data, including surveys, interaction logs, and reflective reports, were analyzed to assess learning engagement, psychological needs satisfaction, cognitive interaction levels, and project outcomes. Results demonstrate that the individual use strategy significantly outperformed shared use in enhancing engagement, needs satisfaction, higher-order cognitive interactions, and final project scores. The restricted interaction strategy effectively served as a metacognitive scaffold, optimizing the learning process by promoting deliberate planning. Notably, individual autonomy did not undermine collaboration but enhanced it by improving the quality of individual contributions to group work. Students also developed robust critical verification habits to navigate LLM “hallucinations.” This research identifies “individual autonomy” as the core mechanism and “moderate constraint” as a crucial design principle for LLM integration, providing an empirically supported framework for harnessing generative AI to foster both motivational and cognitive outcomes in engineering PBL. Full article

With the growing popularity of leisure travel, small recreational vehicles have gained significant attention for their flexibility and cost-effectiveness. A crucial aspect of recreational vehicle design is the interior space, which heavily influences the users’ satisfaction. This paper introduces a novel approach to designing recreational vehicles’ interior space based on users’ behavior data analysis. Firstly, drawing on the properties of the correlation coefficient in statistics, the correlation degree between different functional facilities is defined according to the usage time interval to establish the correlation degree matrix; then, the correlation degree matrix is proved to be a real symmetric positive definite matrix; finally, based on the correlation degree matrix, the factor analysis method is adopted for grouping all the functional facilities to maximize the correlation degrees between functional facilities in the same group and minimize the ones between different groups so as to better satisfy the users’ needs for convenience. A case study using the CCHW–Weiman recreational vehicle demonstrates the effectiveness of this method. Male passengers’ average movement distances during typical activities—washing, cooking, and sleeping—decreased by 17.18%, 36.34%, and 30.68%, respectively, while female passengers’ average movement distances decreased by 13.75%, 37.70%, and 18.82%, respectively. The results suggest that the proposed method offers a data-driven, user-centered approach to improving the interior space of recreational vehicles. Full article

Electric bikes (E-bikes), recognized as a convenient and sustainable mode of transportation, have gained widespread adoption among urban residents. In order to regulate the e-bike industry, China introduced the “Safety Technical Standards for E-bikes” (GB17761-2024), which officially came into effect on 1 September 2025. This study examines residents’ usage behavior and their continued usage intention for e-bikes following the implementation of the new national standards. Using valid data collected from respondents, the ordered logit model is established to analyze the key factors and the mechanisms influencing the continued usage behavior of e-bikes. The results indicate that: (1) A monthly income of 3500–5000 CNY significantly positively influences the continued intention to use electric bikes for both the general population and the courier/food delivery person. (2) Satisfaction with current e-bike usage positively influences the continued usage intention for both the general population and delivery personnel. (3) An increase in usage costs negatively impacts the intention to continue using electric bikes; the reduced bike speed significantly reduces the continued usage intention among delivery persons. The extended battery life does not significantly influence the continued usage intention. Based on the model results, several policy recommendations are proposed to enhance the continued usage intention of e-bikes among residents. The findings could provide theoretical insights and practical suggestions for urban transportation policy optimization and the planning of non-motorized transport systems. Full article

In an increasingly centralized digital society, the widespread reliance on third-party cloud services has heightened user concerns about data privacy and control, driving a significant movement toward self-hosted solutions. This study investigates factors influencing continued use of self-hosting, proposing an extended research model that combines classic TAM constructs with domain-specific factors like perceived autonomy, privacy concerns, perceived trust, personal innovativeness and perceived enjoyment. A quantitative survey was conducted with $n=2158$ active self-hosting users, and the data was analyzed using PLS-SEM. The findings reveal that perceived enjoyment, perceived autonomy and perceived usefulness are the most significant positive drivers of continuance intention, confirming that intrinsic satisfaction and the desire for control are powerful motivators for sustained engagement. The study also found that the relationship between intention and usage is significantly moderated by perceived competence, highlighting that a user’s technical skill strengthens the link between their intent and actual use. The research offers key insights for developers and policymakers and contributes to academic discourse on sustained technology use by providing a validated measurement scale for self-hosted software usage and underscoring the importance of user empowerment and an enjoyable experience to foster the sustained engagement of decentralized digital solutions essential for the socio-technical sustainability of the digital society. Full article

This study investigates how perceived value influences user satisfaction and usage intention toward AI Digital Human Advisors in digital finance, drawing on the Stimulus–Organism–Response (S–O–R) framework. Perceived value is conceptualized as comprising functional, cognitive, and emotional dimensions, reflecting users’ utilitarian, intellectual, and affective evaluations of AI advisors. To empirically test the proposed model, a structured questionnaire survey was conducted with 524 adult users of digital financial applications in mainland China, and the data were analyzed using structural equation modeling (SEM). The results reveal that cognitive and emotional value significantly enhance both satisfaction and usage intention, whereas functional value shows no significant effect. Satisfaction fully mediates the effect of cognitive value and partially mediates that of emotional value. Moreover, switching barriers negatively moderate the satisfaction–intention link, indicating that high friction weakens the behavioral impact of satisfaction. The findings extend perceived value theory to AI-mediated financial contexts by demonstrating that emotional and cognitive engagement—rather than functional efficiency—drives sustained behavioral intention. Practically, the study highlights the importance of designing emotionally intelligent and cognitively transparent AI advisors. As the data were collected from urban users in China, where digital finance is relatively advanced, future research should validate these findings in other cultural and institutional contexts. Full article

Background: This study examined the relationship between screen time, body image satisfaction, body mass index (BMI), and quality of life among children and adolescents from two school clusters in Sesimbra, Portugal. Methods: The sample included 80 students aged 10 to 18 years, assessed using validated questionnaires (Collins’ Figure Rating Scale and KIDSCREEN-27). Results: Results indicated sex differences in electronic game use, with boys reporting higher usage. A negative association was found between time spent on social networks and perceived autonomy and parent–child relationship quality. A high prevalence of body image dissatisfaction was found, particularly among boys, which was significantly associated with BMI. Regarding quality of life, participants scored lower than the European average in the domains of physical and psychological well-being. Conclusions: Findings suggest that screen time, body image, and BMI interdependently affect quality of life, underscoring the need to promote digital literacy, self-esteem, body acceptance, and healthy lifestyles in both school and family settings. Full article

This study assesses De Lone and McLean’s Information System (D&M IS) Success Model concerning DAS throughout small and medium enterprises (SMEs) in Saudi Arabia (SA). The present work mainly sought to evaluate the impact of information quality (IQ), system quality (SysQ), service quality (SrvQ) serving, system utilization, and user satisfaction (Usat) on the usage of the Digital Accounting System (DAS), which is posited to ultimately improve the quality of sustainable decision-making. The research utilized a quantitative methodology, employing a self-administered questionnaire to collect data from 328 decision-makers who are knowledgeable about actual DAS usage by SMEs in SA. Subsequent to gathering data, validation was conducted via Structural Equation Modeling (SEM) by utilizing smart-PLS software. The findings indicate that SysQ and IQ significantly influenced system utilization, although SrvQ did not. DAS was determined to significantly influence user happiness. Moreover, system utilization and user satisfaction positively influenced DAS, thereby affecting the sustainability of decision-making and reflecting the overall benefits of DAS. This work enhances the current IS literature by identifying the characteristics that affect the net advantages of DAS, with the suggested model evaluated in SMEs in SA utilizing DAS. This study serves as a reference to elucidate the significance of DAS and offers consequences, limitations, and prospects for further research. Full article

Compared with other fossil energy sources, natural gas is characterized by compressibility, low energy density, high storage costs, and imbalanced usage. Natural gas pipeline supply systems possess unique attributes such as closed transportation and a highly integrated upstream, midstream, and downstream structure. Moreover, pipelines are almost the only economical means of onshore natural gas transportation. Given that the upstream of the pipeline features multi-entity and multi-channel supply including natural gas, coal-to-gas, and LNG vaporized gas, while the downstream presents a competitive landscape with multi-market and multi-user segments (e.g., urban residents, factories, power plants, and vehicles), there is an urgent social demand for non-discriminatory and fair opening of natural gas pipeline network infrastructure to third-party entities. However, after the fair opening of natural gas pipeline networks, the original “point-to-point” transaction model will be replaced by market-driven behaviors, making the verification and allocation of gas transmission capacity a key operational issue. Currently, neither pipeline operators nor government regulatory authorities have issued corresponding rules, regulations, or evaluation plans. To address this, this paper proposes a multi-dimensional quantitative evaluation model based on the Analytic Hierarchy Process (AHP), integrating both commercial and technical indicators. The model comprehensively considers six indicators: pipeline transportation fees, pipeline gas line pack, maximum gas storage capacity, pipeline pressure drop, energy consumption, and user satisfaction and constructs a quantitative evaluation system. Through the consistency check of the judgment matrix (CR = 0.06213 < 0.1), the weights of the respective indicators are determined as follows: 0.2584, 0.2054, 0.1419, 0.1166, 0.1419, and 0.1357. The specific score of each indicator is determined based on the deviation between each evaluation indicator and the theoretical optimal value under different gas volume allocation schemes. Combined with the weight proportion, the total score of each gas volume allocation scheme is finally calculated, thereby obtaining the recommended gas volume allocation scheme. The evaluation model was applied to a practical pipeline project. The evaluation results show that the AHP-based evaluation model can effectively quantify the advantages and disadvantages of different gas volume allocation schemes. Notably, the gas volume allocation scheme under normal operating conditions is not the optimal one; instead, it ranks last according to the scores, with a score 0.7 points lower than that of the optimal scheme. In addition, to facilitate rapid decision-making for gas volume allocation schemes, this paper designs a program using HTML and develops a gas volume allocation evaluation program with JavaScript based on the established model. This self-developed program has the function of automatically generating scheme scores once the proposed gas volume allocation for each station is input, providing a decision support tool for pipeline operators, shippers, and regulatory authorities. The evaluation model provides a theoretical and methodological basis for the dynamic optimization of natural gas pipeline gas volume allocation schemes under the fair opening model. It is expected to, on the one hand, provide a reference for transactions between pipeline network companies and shippers, and on the other hand, offer insights for regulatory authorities to further formulate detailed and fair gas transmission capacity transaction methods. Full article

Background/Objectives: Bulkamid^® (Axonics, Irvine, CA, USA) is a non-particulate polyacrylamide hydrogel used in the treatment of urinary incontinence. While its effectiveness is well-documented in female stress urinary incontinence (SUI), there is limited data on its role in male stress urinary incontinence, particularly post-prostatectomy incontinence (PPI). This study evaluates the efficacy of Bulkamid as a primary or adjunctive treatment for male PPI. Methods: A retrospective chart review was conducted on male patients who developed PPI and underwent Bulkamid injections between 2016 and 2021. Data collected included pre- and post-procedure pad usage, the volume of Bulkamid injected, prior and subsequent incontinence treatments, and patient-reported satisfaction. Bulkamid was injected transurethrally in four quadrants near the vesicourethral anastomosis using a rigid cystoscope. Results: Twenty-one men with a history of radical prostatectomy (six open and fifteen robotic), including four who received adjuvant radiotherapy, were included. Fifteen underwent Bulkamid injection as a primary treatment, with five (33%) requiring repeat injections due to initial improvement. Eight (54%) subsequently underwent an AdVance XP^® sling placement, while two (13%) required no further treatment. Six patients received Bulkamid as an adjunct to prior incontinence surgery, with 80% of post-sling patients reporting improved continence. Bulkamid was less effective in men with detrusor overactivity or prior radiation. Conclusions: Bulkamid demonstrated a higher success rate as an adjunct to the AdVance XP sling, with 80% of men experiencing improved continence. As a primary treatment for PPI, success was modest, with only 33% achieving improvement, often requiring repeat injections or conversion to a sling. Bulkamid presents a low-risk option for select male PPI patients, particularly those with prior sling placement, but durability and long-term effectiveness remain concerns. Full article

This paper introduces a gesture-controlled conversational interface driven by a local AI model, aimed at improving accessibility and facilitating hands-free interaction within digital environments. The technology utilizes real-time hand gesture recognition via a typical laptop camera and connects with a local AI engine to produce customized learning materials. Users can peruse educational documents, obtain topic summaries, and generate automated quizzes with intuitive gestures, including lateral finger movements, a two-finger gesture, or an open palm, without the need for conventional input devices. Upon selection of a file, the AI model analyzes its whole content, producing a structured summary and a multiple-choice assessment, both of which are immediately saved for subsequent inspection. A unified set of gestures facilitates seamless navigating within the user interface and the opened documents. The system underwent testing with university students and faculty (n = 31), utilizing assessment measures such as gesture detection accuracy, command-response latency, and user satisfaction. The findings demonstrate that the system offers a seamless, hands-free user experience with significant potential for usage in accessibility, human–computer interaction, and intelligent interface design. This work advances the creation of multimodal AI-driven educational aids, providing a pragmatic framework for gesture-based document navigation and intelligent content enhancement. Full article

This study examines the intention of Greek tourists who visit national touristic destinations to adopt Artificial Intelligence (AI) chatbots in the tourism sector. Using the UTAUT2 model as a framework, data were collected through a closed-ended questionnaire and analyzed with correlation and regression methods to identify the main drivers and barriers to this adoption. Results show that specific factors such as performance expectancy, hedonic motivation, and perceived innovativeness significantly and positively influence chatbot usage, emphasizing the role of usefulness, enjoyment, and innovation in shaping user acceptance. Conversely, factors such as inconvenience, habit, and difficulty of use negatively affect adoption, indicating the importance of overcoming usability challenges and resistance to change. These findings highlight the need for the development of accessible and engaging chatbot systems and underscore the value of continuous technological improvements. The study concludes that adopting AI-driven solutions can help tourism providers personalize services, improve operational efficiency, and enhance customer satisfaction, fostering sustainable competitiveness in the sector. Full article