Reminiscence activities, which involve recalling and sharing past experiences, have proven beneficial for improving cognitive function, mood, and overall well-being. However, urbanization has led to the disappearance of familiar environments, removing visual and audio cues for effective reminiscence. While old photos can serve as visual cues to aid reminiscence, it is challenging for people to reconstruct the reminisced content and environment that are not in the photos. Virtual reality (VR) and artificial intelligence (AI) offer the ability to reconstruct an immersive environment with dynamic content and to converse with people to help them gradually reminisce. We designed RemVerse, an AI-empowered VR prototype aimed to support reminiscence activities. Integrating generative models and AI agent into a VR environment, RemVerse helps older adults reminisce with AI-generated visual cues and interactive dialogues. Our user study with 14 older adults showed that RemVerse effectively supported reminiscence activities by triggering, concretizing, and deepening personal memories, while fostering increased engagement and autonomy among older adults. Based on our findings, we proposed design implications to make reminiscence activities in AI-assisted VR more accessible and engaging for older adults.

Urban–rural fringes (URFs) are crucial for biodiversity yet often neglected in conservation efforts. This study refines URF habitat evaluation and integrates it into a coordinated ecological network (EN) and territorial planning framework. Using Qingpu District, Shanghai as a case study, we defined its URF via k-means clustering of night-time light data and applied the InVEST model, MSPA, Integrated Habitat Value, Patch Importance, and Betweenness Centrality analyses to identify high-value URF habitats. Furthermore, we constructed the EN using circuit theory and evaluated the impact of URF sources on network connectivity and construction costs. Our findings reveal that integrating URF sources increased connectivity indices significantly (α by 127.18%, β by 47.00%, and γ by 33.4%) and decreased construction costs (CR index by 0.07). Despite these benefits, under China’s “Three Zones and Three Lines” policy, 78.18% of Qingpu’s URF sources remain unprotected, with 56.78% at risk of conversion to construction land. Our study proposes a comprehensive evaluation system for URF habitats and strategic recommendations for their incorporation into regional ENs, thus informing policy making and planning for more inclusive ecological conservation.