Search Results (59)

In response to the growing relevance of shared housing models such as co-living and co-housing, this study investigates how spatial configuration affects the experience and negotiation of privacy in shared domestic environments. While privacy is often treated as a subjective or cultural concern, this research adopts a spatial perspective to examine its morphological underpinnings. Using space syntax methods, the study analyses contemporary shared housing models, focusing on three shared housing developments in Barcelona. Through Visual Graph Analysis (VGA), spatial parameters, including integration, through vision, control, and controllability values, are applied to assess the degree of accessibility, visibility, and spatial separation within and between private and communal areas. The results reveal distinct configurational patterns that correlate with different privacy gradients, identifying how spatial arrangement enables or restricts autonomy and co-presence among residents. The study concludes that privacy in shared housing is not only a matter of design intention but is embedded in the spatial logic of dwelling morphology: exposed and controlled spaces provide less privacy but enhance sociability, while spatial elements such as boundaries and transitions play an important role in managing privacy gradation and degrees. These findings offer a framework for understanding and designing shared living environments that are better attuned to the complexities of everyday privacy needs. Full article

Amid expanding higher education and enhancing spatial quality, modern university campuses face challenges including inefficient space utilization and a disconnect from human-centered design. We developed a coupled model that integrates the analytic hierarchy process (AHP) with space syntax theory to identify and address functional fragmentation, limited accessibility, and diminished spatial vitality. The Delphi method was employed to determine weights on visual and traffic influence factors. Through spatial quantitative analysis using Depthmap software, we estimated spatial-efficiency discrepancies across 11 component types, including school gates, teaching buildings, and libraries. A case study was conducted at a university located in the hilly terrain of Conghua District, Guangzhou, China which revealed significant contradictions between subjective evaluations and objective data at components, such as the administrative building and gymnasium. These contradictions led to poor visual permeability, excessive path redundancy, and imbalanced functional layouts. Based on the results of this study, targeted optimization strategies were proposed, including permeable interface designs, path network reconfiguration, and the implementation of dynamic functional modules. These interventions were tailored to accommodate the humid subtropical climate, balancing shading, ventilation, and visual transparency. In this study, methodological support for the renovation of existing campus infrastructure was provided as theoretical and technical references for space renewal in tropical and subtropical academic environments and the enhancement of the quality and resilience of campus spaces. The results also broadened the application of interdisciplinary methods in university planning. Full article

Ontology technology addresses data heterogeneity challenges in Internet of Everything (IoE) systems enabled by Cyber Twin and 6G, yet the subjective nature of ontology engineering often leads to differing definitions of the same concept across ontologies, resulting in ontology heterogeneity. To solve this problem, this study introduces a hybrid ontology matching method that integrates a Recurrent Neural Network (RNN) with syntax-based analysis. The method first extracts representative entities by leveraging in-degree and out-degree information from ontological tree structures, which reduces training noise and improves model generalization. Next, a matching framework combining RNN and N-gram is designed: the RNN captures medium-distance dependencies and complex sequential patterns, supporting the dynamic optimization of embedding parameters and semantic feature extraction; the N-gram module further captures local information and relationships between adjacent characters, improving the coverage of matched entities. The experiments were conducted on the OAEI benchmark dataset, where the proposed method was compared with representative baseline methods from OAEI as well as a Transformer-based method. The results demonstrate that the proposed method achieved an 18.18% improvement in F-measure over the best-performing baseline. This improvement was statistically significant, as validated by the Friedman and Holm tests. Moreover, the proposed method achieves the shortest runtime among all the compared methods. Compared to other RNN-based hybrid frameworks that adopt classical structure-based and semantics-based similarity measures, the proposed method further improved the F-measure by 18.46%. Furthermore, a comparison of time and space complexity with the standalone RNN model and its variants demonstrated that the proposed method achieved high performance while maintaining favorable computational efficiency. These findings confirm the effectiveness and efficiency of the method in addressing ontology heterogeneity in complex IoE environments. Full article

Public spaces are fundamental spatial units within cities, serving as essential venues for residents’ daily activities and as resilient environments for responding to emergencies. They play a crucial role in enhancing urban resilience and promoting sustainable urban development. However, existing research predominantly focuses on objective spatial entities, often neglecting users’ behavioral and psychological perceptions. Studies that incorporate perceived resilience typically necessitate extensive, time-consuming, and costly fieldwork. To address these gaps, this study innovatively integrates space syntax into the Public Space Resilience (PSR) analytical framework, thereby bridging the subjective and objective dimensions of resilience in the evaluation process. A comprehensive resilience measurement framework is developed, linking ‘material entities’, ‘spatial perception (via space syntax)’, and ‘spatial resilience’. Using the Yuzhong Peninsula in Chongqing, China, as a case study, this research employs indicators such as integration, connectivity, and comprehensibility to quantitatively evaluate PSR. Based on the findings, this study also proposes strategies and recommendations to enhance PSR. The results contribute to both a practical measurement method and a theoretical framework for advancing PSR in urban planning and design. Full article

Vernacular architecture is a complex and living heritage type, and the study of the evolution laws of its spatial form is of great value to the conservation of architectural heritage diversity. Taking vernacular architecture in the Yunnan–Tibet area as the research object, based on the theory of spatial syntax, 30 building samples were subjected to global and local calculations of MD, I_RRA, and NACH values, while the common characteristics among the samples were obtained by using Kendall’s W test, and the individual characteristics among the samples were obtained by using differentiation analysis. The results show that: (a) vernacular architecture in the Yunnan–Tibet area exhibits characteristics of multi-cluster branched centrality and spatial hierarchical layout; (b) these architectures possess four categories of inheritance factors: the privacy of granary spaces, the centrality of corridor spaces, the passability of breeding areas, and the independence of scripture hall spaces; (c) these architectures possess three categories of differentiation factors: the functional evolution of traditional spaces, the spatial reconstruction of breeding areas, and the “Toilet Revolution” driven by multiple forces. This study elucidates the regulatory role of cultural continuity in shaping the spatial forms of vernacular architecture, providing new evidence for analyzing the formation mechanisms of vernacular architecture in the Yunnan–Tibet area. Full article

Urban trails, as vital urban spaces that integrate historical context with contemporary life, play a central role in the rise of deep tourism and the “City Walk” phenomenon. Their spatial legibility positions them as distinctive narrative media, serving as a key channel for promoting urban sustainable development and enhancing citizens’ sense of well-being. However, existing research has yet to establish a comprehensive and systematic framework for evaluating the “spatial narrative” of urban trail systems. This study proposes a dual-perspective quantitative framework for evaluating a spatial narrative, combining objective spatial dimensions with human experiential data to identify strengths and potentials for improvement. The Southwest Regional Trail in Chongqing (comprising the Zhongshan Fourth Road Section, People’s Assembly Hall Section, and Datianwan Section) was used as a case study. First, multi-source spatial data were analyzed via space syntax and ArcGIS to evaluate narrative value from an objective spatial perspective. Next, in-depth questionnaire interviews were conducted to collect subjective data, which were analyzed in SPSS to produce a structured analysis of participant feedback. The findings indicate that (1) Among the three sections of the Southwest Regional Trail, the narrative potential zones rank highest in the Zhongshan Fourth Road Section, followed by the People’s Assembly Hall Section and the Datianwan Section. (2) Urban trails characterized by rich narrative themes and cultural activities are more attractive to visitors. (3) The qualities of narrative symbols, routes, and educational elements are the key factors that specifically influence visitors’ satisfaction with the narrative experience on urban trails. Based on these results, we propose targeted planning and design recommendations for the Southwest Regional Trail. The evaluation methodology and process proposed in this study can provide references for design professionals and relevant urban development departments in conducting spatial narrative quantitative evaluations and optimizing sustainability place-making strategies. Full article

Short informal texts are increasingly prevalent in modern communication, often containing fragmented grammar, personal opinions, and limited context. Traditional NLP tasks for the texts ordinarily focus on the subjective aspect learning, such as sentiment analysis and polarity classification. The study of learning objectivity from the texts is similarly significant, which can benefit many real-world applications including information filtering, content verification, etc. Unfortunately, this study is not being explored. This paper proposes a novel task that aims at identifying objectivity in short informal texts. Inspired by the characteristics of objective statements that normally need complete syntax structures for knowledge expression and delivery, we try to leverage the viewpoint of subjects (U), the tense of predicates (V), and the viewpoint of objects (O) as critical factors for objectivity learning. Upon that, we further propose a two-stage objectivity identification approach: (1) a UVO quantification module is implemented via a proposed OpenIE and large language model (LLM)-based triple feature quantification procedure; (2) an objectivity identification module employs pre-trained base models like BERT or RoBERTa that are constrained with the quantified UVO. The experimental result demonstrates our approach can outperform the base models up to $5.91\%$ in objective-F1 and up to $6.97\%$ in accuracy. Full article

Structural Health Monitoring (SHM) relies on the effective communication between sensors and diagnostic systems, yet data interpretation remains inconsistent and subjective. This paper introduces a novel perspective, viewing data as a form of language with its own syntax, semantics, and pragmatics. By adopting this linguistic framework, the study emphasizes the need for standardized “grammars” in data collection, processing, and analysis to reduce ambiguity and enhance diagnostic reliability. Using case studies from SHM, the paper illustrates how subjective decisions in variable selection, cluster labels, preprocessing, and modeling introduce biases that affect the outcomes. The findings highlight the potential of context-aware algorithms and integrated data sources to mitigate these biases. This conceptual approach has broader implications for data science, suggesting a universal “language of data” that fosters consistency and collaboration across disciplines. By recognizing the constructed nature of data, this work offers a path toward more accurate, efficient, and reliable structural diagnostics, advancing both SHM practices and data interpretation methodologies. Full article

Cardiovascular diseases (CVDs) remain the leading cause of death globally. In recent years, interest in multicomponent interventions has grown as a response to the multifactorial complexity of CVDs. However, the literature still shows little systematic investigation into the effectiveness of multicomponent training (MCT) in the field of CVDs, accompanied by terminological confusion. This study aims to summarize and critically appraise the recent literature through a narrative review. A narrative review was conducted, synthesizing evidence from studies published between 2010 and January 2025. The databases searched included PubMed, Scopus, and Google Scholar using predefined search terms related to CVDs and MCT, and medical subject headings (MeSHs) and Boolean syntax. Two team authors independently extracted relevant information from the included studies. MCT significantly improved hemodynamic parameters in CVD patients, with reductions in systolic, diastolic, mean blood pressure, and heart rate. Physical fitness measures showed consistent enhancements whereas anthropometric improvements often corresponded with blood pressure reductions. Psychological outcomes varied across studies, with intervention duration emerging as a key factor in effectiveness. MCT interventions could lead to improvements in clinical outcomes, risk factor reduction, and patient adherence. Although findings on psychological parameters remain inconsistent, the overall evidence supports their integration into both clinical and community settings. Full article

Background/Objectives: Current evidence suggests that levosimendan may have a beneficial effect in the treatment of acute heart failure (AHF) or cardiogenic shock following primary percutaneous coronary intervention (PCI). However, there is a paucity of data on the use of levosimendan prior to PCI. Therefore, our pilot study aimed to assess the short-term prognosis of a new therapeutic protocol involving preprocedural infusion of levosimendan in patients with reduced left ventricular ejection fraction undergoing high-risk PCI for acute coronary syndrome (ACS). Methods: The study is a retrospective observational study, and the population includes all subjects who received levosimendan infusion prior to high-risk PCI for ACS. Subjects requiring urgent revascularization (cardiogenic shock, cardiac arrest) or with mechanical complications of ACS were excluded. Results: The study cohort consisted of 90 subjects, predominantly men (91.1%) with significantly reduced left ventricular function (28.7% (12)) and advanced coronary artery disease, mean SYNTAX Score 25.8 (19.3–33). During in-hospital follow-up, we observed 2 primary outcomes—death. The major adverse cardiac and cerebrovascular events (MACCE) rate was 7.8%. Two clinical adverse events that did not lead to discontinuation were observed during the in-hospital period. Both were related to hypotension. Conclusions: In short-term observation, novel therapeutic approach in the management of high-risk PCI in ACS patients—pre-procedural levosimendan—was a relatively safe approach. No significant adverse events were reported. Full article

Currently, coordinated development in terms of perceived urban quality and function has become a key problem. However, there is an imbalance between the street environment and urban amenities. It is necessary to explore the current status and propose optimization strategies to promote the coordinated development of urban spaces. Dalian, China, was selected as the study area. Based on space syntax, high-accessibility and low-accessibility streets were selected as study sites. An evaluation system was constructed as part of the study. It included the urban function and perceived street quality. Data on the density and diversity of urban amenities were obtained by establishing points of interest (POIs). The subjective and psychological perception of quality was calculated using street view images (SVIs). Then, a coupling analysis based on the urban function and perceived quality was conducted as part of the study. The results indicated that there were differences in the development levels of urban amenities and in regard to spatial quality in Dalian. Specifically, high-accessibility streets and urban amenities were mainly concentrated in the central urban area. The perceived quality of high-accessibility streets was higher than low-accessibility streets. The coupling analysis found that high-accessibility and low-accessibility streets had the highest proportions of advantage streets and opportunity streets. The urban amenities and subjective perception of quality were the highest in regard to advantage streets. The perception of beauty was the lowest in regard to maintenance streets. The psychological perception was the highest among improvement streets. Openness was the highest in regard to opportunity streets. As a result of the coupling analysis, this study not only helps to optimize the layout of urban amenities and improve the quality of the street environment, but also provides practical guidance for future urban design. Additionally, the results of this study will help to promote the coordinated development of street environments and urban amenities and enhance the overall livability and spatial quality of the urban environment. Full article

Objective: Homoarginine is a cationic amino acid derived from lysine. Evidence indicates that low-circulating homoarginine concentration is a risk factor for cardiovascular disease and all-cause mortality. A reduction in homoarginine concentrations has been observed in patients with ischemic heart disease, ischemic stroke, ischemic heart disease, and heart failure. The SYNTAX score (SS), an angiographic scoring system, defines the grade and complexity of coronary artery disease (CAD). The objective of this study was to evaluate the relationship between homoarginine level and the severity of CAD according to the SYNTAX score in patients with ST-segment elevation myocardial infarction (STEMI). Methods: A total of 67 subjects were enrolled into the study with the diagnosis of STEMI of those who underwent coronary angiography. STEMI patients were divided into two groups: low-medium SYNTAX score ≤ 14 (35 patients) and high SYNTAX score > 14 (32 patients). Results: Within the high SS group, serum homoarginine levels were markedly lower (2 ± 0.9 vs. 1.3 ± 0.7; p = 0.001). Homoarginine levels and SS showed a significant negative correlation in entire study cohort In multivariate regression analysis, serum homoarginine levels along with serum urea levels were significantly associated with having higher SS (OR 1.073 p = 0.049 and OR 0.346, p = 0.012, respectively). Conclusions: In conclusion, the diminished plasma homoarginine level emerges as an independent predictor of high atherosclerotic burden among STEMI patients. To the best of our knowledge, this is the first study to demonstrate the relationship between homoarginine and coronary artery complexity. Full article

Despite its potential for STEM education, educational robotics remains out of reach for many classrooms due to upfront purchase costs, maintenance requirements, storage space, and numerous other barriers to entry. As demonstrated previously, these physical robot limitations can be reduced or eliminated through simulation. This work presents a new version of RoboScape Online, a browser-based networked educational robotics simulation platform that aims to make robotics education more accessible while expanding both the breadth and depth of topics taught. Through cloud-hosted simulations, this platform enables distant students to collaborate and compete in real-time. Integration with NetsBlox, a block-based programming environment, allows students at any level to participate in computer science activities. By incorporating a virtual machine for running NetsBlox code into the server, RoboScape Online enables scenarios to be built using the same syntax and abstractions used to program the robots. This approach enables more creative curriculum activities while proving that block-based programming is a valuable development tool, not just a “toy language”. Classroom case studies demonstrate RoboScape Online’s potential to improve students’ computational thinking skills and foster positive attitudes toward STEM subjects, with especially significant improvements in attitudes toward self-expression and creativity within the realm of computer science. Full article

With the acceleration of global aging, outdoor environments, especially urban green space’s planning and design, play a crucial role in not only promoting physical health but also significantly increasing the opportunities for social interactions for older adults. In recent years, the study of age-friendly outdoor environments has attracted increasing attention, with digital methods emerging as essential tools due to their precision and versatility. In this research, three parks in the Nankai District, Tianjin, are taken as the subject of a case study to explore the spatial factors that may exert influence on the behavior distribution of older adults in summery urban parks’ planning and design. With the behavior data of the older adults in the park collected using an Insta360 camera every hour (from 8 a.m. to 15 p.m.), the three parks are divided into a total of 49 areas for further analysis. Additionally, the visual indexes of the spatial syntax are analyzed with Depthmap 10, the sunlight conditions are analyzed with the Tangent model, and some other spatial factors, such as the green space ratio and the hard ground ratio, are calculated according to the semantic segmentation of the 360-degree panoramic view photo from the center of every area. SPSS and Gradient Boosting Decision Trees (GBDTs) are used to reveal not only the correlations between the sunlight conditions and the behavior distribution of behavior of the older adults, but also the importance ranking of spatial factors. Furthermore, some improvement strategies are proposed for spatial facility configuration, park furniture arrangement, rational hardscape planning, as well as greening and landscape design. By exploring how to improve the spatial planning and design of summery urban green space for older adults, this research provides guidance on the creation of urban green spaces in extremely hot weather that are not only visually appealing but also socially equitable and environmentally sustainable. Full article

Historic districts are an important component of urban heritage, carrying the memory of the city. The study provides objective spatial level and subjective perception level analysis regarding the evaluation of the renewal of historic districts. We selected Qianmen Street, which is located on the central axis of Beijing, as the research subject. Space syntax was used to determine the importance of the main street to the district, and a kernel density analysis revealed that it was a poor tourist attraction. We used online comment data to establish an evaluation system, based on grounded theory, for the renewal of Qianmen Street. The evaluation system consisted of four primary indicators, including space creation, architectural style conservation, locality, and business management, as well as fifteen secondary indicators. Additionally, an importance–performance analysis (IPA) was used to conduct a quadrant analysis on tourist satisfaction evaluation indicators, in order to analyze influencing factors. The results show that tourists are most concerned about the dimensions of locality and business management, but the level of tourist satisfaction is low. The renewal of the Qianmen historic district should give priority to the creation of its historicity, cultural characteristics, and uniqueness, and should use a small-scale, gradual, and sustainable renewal method. Full article