Residential satisfaction has always been a crucial concern in urban planning and community management. This paper conducts a study of key factors affecting residential satisfaction in settlements with multiple build periods coexisting in old neighborhoods. This study aims to comprehensively analyze the influencing factors of residential satisfaction in order to obtain the post-occupancy evaluation of the residential environment by residents in different communities and propose sustainable design strategies based on the evaluation analysis. By constructing an evaluation system of residential satisfaction with 19 evaluation indicators and based on the questionnaire, the sample frequency analysis, reliability and validity test, IPA analysis, and evaluation factor analysis of the data, the IPA mean distribution results of residential satisfaction in the four communities are obtained. The study reveals that residents are most satisfied with the surrounding services in their communities but generally less satisfied with the internal residential environment. Among the factors, fitness facilities and space in the community have a significant impact on residents’ satisfaction; community activities and neighbor relationships are also key influencing factors, which become more prominent as the construction period of the community approaches. Additionally, community residents’ self-organizational governance will affect their satisfaction with community conventions and social capital. Therefore, this study proposes improvement suggestions, including planning community life circles to fully utilize available resources in the surrounding area, establishing community self-organization for community governance and improving the quality of community life, and implementing mobile service stations to flexibly adapt to community space and service needs. This study provides a valuable reference for urban community renewal and sustainable development. The research findings are expected to provide practical guidance for improving the residential environment within old neighborhoods and enhancing residents’ satisfaction.

As urbanization progresses, large cities continue to attract population, causing depopulation and regional development imbalances, especially in remote rural areas facing sustainability challenges. This study aims to explore local resource potential and assess critical factors for regional revitalization, offering design strategies to promote local sustainability. The study is based on the UN Sustainable Development Goals (SDGs) and assesses the status of regional development through field research. The Delphi method was employed to interview experts and build a multi-tiered sustainable development evaluation indicator framework (Level 1: B1–B3, Level 2: C1–C8, Level 3: D1–D16), covering economic, social, and environmental dimensions. The weights of the indicators were determined through the analytic hierarchy process (AHP), and the fuzzy comprehensive evaluation (FCE) method was applied to comprehensively assess the sustainable development status of Qianfeng Community. The research findings revealed that due to population outflow and a lack of participation in co-building channels, the region scored lowest in “local employment & entrepreneurship (D2)”, “innovation & entrepreneurship culture (D10)”, and “endogenous development (D16)”. Consequently, the study proposes the establishment of a regional revitalization co-creation platform based on “life projects” as part of a sustainable design strategy. These research results provide valuable case studies and strategic references for future regional revitalization and sustainable design initiatives.

Historic districts are complex built heritage environments where conservation, commercial activities, and public use continuously interact. A key challenge is maintaining cultural meaning and spatial authenticity while meeting contemporary demands for leisure and accessibility. Taking the Fuzimiao–Qinhuai Scenic Belt in Nanjing, China, as a representative case, this study develops a computational mixed-methods framework to evaluate visitor perception and diagnose experiential imbalances in the built heritage environment. A total of 2940 online reviews (2020–2025) were analysed using TF-IDF, Latent Dirichlet Allocation (LDA), StructBERT sentiment analysis, and Importance–Performance Analysis (IPA). Six experiential dimensions were identified, covering cultural inheritance, nightscape and leisure, rituals and museum visits, architectural space, value evaluation, and practical services. Results reveal a clear disparity: nightscape and value-related dimensions received the highest attention and positive sentiment, whereas rituals and museum interpretation underperformed despite their central heritage significance. Based on the IPA diagnosis, the study proposes three strategies: reallocating resources from over-supplied services to underperforming cultural cores, integrating immersive digital technologies (VR/AR) to revitalise heritage interpretation, and embedding cultural narratives into nightscape experiences. These strategies support a paradigm shift from visual attraction to cultural resonance in the conservation-oriented regeneration of historic districts.

Affective computing aims to enable machines to recognize and simulate human emotions, forming a critical component of intuitive human-computer interaction. This study presents a systematic bibliometric review of 225 high-impact publications (2014–2024) from the Web of Science Core Collection. Utilizing tools like Bibliometrix and CiteSpace, this analysis maps the field's evolution, identifying a paradigm shift from basic emotion recognition to deep learning-based multi-modal fusion, with generative models and large language models for affective synthesis emerging as a new frontier. Persistent challenges include integrating multi-modal context for personalization, fulfilling real-time processing requirements, and addressing ethical issues like bias. To bridge the gap between emotion recognition and the development of genuinely adaptive, context-aware systems, the study highlights the urgent need for generative affective frameworks and neuroscience-informed lightweight models. This review synthesizes the developmental trajectory of affective computing in human-computer interaction to guide future research.

In order to improve the universality of the product family platform, from the perspective of extension innovation method, the product family architecture composed of demand domain, functional domain, technology domain and physical domain was studied. Based on the extension innovation methods, a product service system centered on the product family development platform was established. The basic-element logic language and method of extension design is employed to analyze the characteristics of product family design including generalization, parameterization, modularization, and intelligence. The product family design platform is built through three aspects: formal and modeled basic element representation, modular element configuration and intelligent generation paths. The platform consists of four models and three resource libraries, which is beneficial to forming a decision-making and configuration framework based on product family design platform and reveal the whole process of product development. Combined with artificial intelligence technology, this research constructs a smart product service system framework oriented towards product family design and proposes an extension design generation system. The main challenges and future research directions are also discussed.

Population aging has increased demand for walkable community healthcare for older adults. Using the six central districts of Nanjing as a case study, this study examines whether nominal 15 min access to community health service centers (CHSCs) translates into effective and equitable spatial access after accounting for pedestrian-network barriers, distance decay, and population competition. Based on the 2024 official CHSC roster (n = 60), a census-calibrated 100 m population grid, and an OpenStreetMap walking network, we computed walking times from 500 m hexagonal origins at 1.0 m/s. Binary coverage was compared with equal-supply Gaussian two-step floating catchment area accessibility, and population-weighted Lorenz–Gini measures were calculated overall and among covered older residents. Among 581,474 residents aged 65 years and older, only 28.1% could reach a CHSC within 15 min; 24.8% of covered residents fell below the first quartile of competition-adjusted accessibility. The weighted Gini coefficient was 0.861 overall and 0.506 among covered residents, and high-demand, low-effective areas contained 37.9% of the older population. Under the stated assumptions, the results indicate that nominal proximity overstates modeled equal-supply CHSC accessibility and that joint assessment of coverage, accessibility, conditional equity, and spatial typology can better screen areas for subsequent capacity audits, facility-siting assessment, or pedestrian-network improvement.