[Purpose/Significance] Against the backdrop of a strategic transition from industrial efficiency to embodied intelligence within the "Silver-haired Economy," social robots are evolving from functional tools into social companions. However, the field faces a critical bottleneck: a lack of interaction stickiness and empathetic resonance, which leads to high abandonment rates. Affective computing (AC) serves as the core technology to bridge this gap by enabling machines to detect, interpret, and simulate human emotions. Unlike previous literature that often treats AC as a standalone algorithmic task, this research reconstructs the value of AC from a Human-AI Interaction (HAI) perspective. This approach responds to the national "15th Five-Year Plan" requirements for secure and controllable AI governance by integrating technical pathways with ethical boundaries. By situating social robots within complex social relationships, this study provides a theoretical roadmap for robots to transition from mechanical entities to responsible social agents, thereby supporting the high-quality development of population-centric services. [Method/Process] This study employs a systematic literature review methodology guided by the PRISMA framework to ensure scientific rigor and comprehensiveness. The Web of Science Core Collection served as the primary data source, with a search timeframe spanning from 2015 to 2025 to capture the paradigm shifts triggered by deep learning and large-scale language models. A tripartite search logic-integrating subject entities (social robots), core technologies (affective computing), and interaction contexts (human-robot interaction)-was implemented to filter relevant literature. After a multi-level screening process based on embodiment, technical integrity, and empirical validity, 97 high-quality articles were selected. The study utilizes CiteSpace for keyword clustering and citation burst analysis, mapping the evolution of the field across three distinct stages: from foundational signal processing (2018-2019) to dynamic adaptation models (2020-2022), and finally to generative-driven intelligence and ethical regulation (2023-2025). This systematic approach allows for a deep synthesis of multimodal perception technologies, including robust vision, paralinguistic decoding, and physiological signal sensing. [Results/Conclusions] The findings reveal a significant paradigm shift in affective computing for social robots, evolving from simple signal statistics to deep situational understanding and from static rule-based responses to generative dynamic adaptation. The research proposes a holistic interaction framework comprising three pillars: situational understanding, adaptive action, and ethical constraints. Situational understanding leverages multimodal semantic fusion to decode human intent beyond surface-level data, while adaptive action ensures cross-modal consistency in physical expression through generative AI and long-term memory architectures. Ethical constraints are identified as an internal safety mechanism rather than external regulations, addressing risks such as privacy asymmetry, cultural bias in datasets, and psychological manipulation stemming from high anthropomorphism. The study concludes that the future of social robotics lies in three innovative paradigms: enhancing ecological validity through real-world deployment, constructing lifelong learning mechanisms to sustain long-term relationships, and embedding "human-in-the-loop" ethical fuses directly into algorithmic architectures. Despite these advancements, the research is currently limited by a lack of diverse cultural data and long-term field studies. Future research should prioritize cross-cultural design and the development of explainable affective decision-making modules to ensure the sustainable and benevolent development of embodied intelligence in complex social environments.

[Purpose/Significance] With the continuous advancement of national governance modernization and the rapid development of artificial intelligence (AI) technologies, emotional-functional embodied intelligence has become integral to grassroots social governance. This development not only reshapes traditional governance tools but also triggers profound reflections on the balance between instrumental rationality and value rationality. In this context, systematically examining the internal mechanisms and potential risks associated with the integration of emotional-functional embodied intelligence into social governance can provide both theoretical enrichment and practical guidance for technology-enabled governance modernization. [Method/Process] Based on Max Weber's "tool-value" dichotomy, this study focuses on key issues concerning the influence mechanisms, risk boundaries, and regulatory pathways of emotional-functional embodied intelligence in social governance. By situating the analysis within concrete scenarios of its embedding in social governance practices, the research combines theoretical reflection with contextual examination to explore how emotional-functional embodied intelligence reshapes governance structures and processes. [Results/Conclusions] The findings reveal that AI, embodied intelligence, and emotional-functional embodied intelligence differ significantly in terms of technological architecture, functional form, and modes of integration into social governance. While AI optimizes decision-making through data empowerment and embodied intelligence delivers services through physical interaction, emotional-functional embodied intelligence achieves full-process and in-depth integration into social governance by relying on affective linkage. It forms an integrated structural system composed of the demand, intelligence, action, and support layers, thereby enabling coordinated governance operations that combine rational decision-making with emotional interaction. Through three core mechanisms - intelligence embedding, human-machine coupling and feedback-driven iteration, emotional-functional embodied intelligence is able to simultaneously accomplish rational decision-making tasks and emotional interaction objectives. However, the embedding of emotional-functional embodied intelligence in social governance also implies dual structure of risks. On one hand, it may amplify traditional risks inherent in AI technologies, such as algorithmic dependence and blurred responsibility attribution. On the other hand, it may generate new forms of context-specific risks, including emotional-cognitive alienation, value-guidance deviation, and the reconstruction of governance authority. To address these challenges, it is necessary to construct a full-chain regulatory framework for accountability and establish full-process technological safeguards encompassing ex-ante prevention, in-process monitoring, and ex-post traceability. Concurrently,it's essential to articulate value-oriented principles for emotion-informed governance and clarify a human-machine collaborative governance framework in which human actors retain primary authority while intelligent technologies play an auxiliary role. Through these coordinated measures, effective risk regulation and rational balance can be achieved in the application of emotional-functional embodied intelligence in social governance.

[Purpose/Significance] Under the background of the digital economy, problems such as the difficulty in integrating multi-source heterogeneous data, low efficiency in matching supply and demand, and imbalance between security and openness in library data opening and sharing have restricted traditional technologies and service models from breaking through the bottlenecks. Large language models (LLMs) offer a new path to break through this predicament. This study aims to improve the theoretical system of technology that empowers the open sharing of library data. It also aims to fill the gap in existing research, which mostly focuses on general technologies and lacks systematic adaptation to library scenarios. Additionally, this study aims to provide theoretical and practical support for libraries to transform from data custodians to knowledge enablers, which will support the high-quality development of the industry. [Method/Process] Based on the elaboration of the practical impact of LLMs on the open sharing of library data, this paper analyzed the connotation, essence and characteristics of library data open sharing empowered by LLMs Based on this, the internal logic of LLMs driving the open sharing of library data was discussed, and the implementation path was explored. [Results/Conclusions] The open sharing of library data based on LLMs is manifested as a hierarchical leap in the value of data elements from basic integration, demand matching to decision support. This process needs to be efficiently advanced through human-machine collaboration on the supply side, user participation on the demand side, and cross-domain linkage on the ecosystem side. It should run through the entire life cycle of data production, governance, circulation, and application. Based on this, four guarantee strategies were proposed. In terms of technical architecture, we should adopt the "general model + domain fine-tuning" mode to adapt to the characteristics of library data. Efforts should be devoted to establishing a full-process quality control and hierarchical desensitization mechanism in data governance. In terms of talent cultivation, we should build a "business + discipline + technology" compound team. In terms of ethical construction, a full-process review and user rights protection system should be established. In the future, it is possible to further explore the in-depth adaptation of LLMs with the special collection resources of libraries, as well as the construction of a dynamic and elastic security governance framework, to promote the ecological development of industry data openness and sharing.

[Purpose/Significance] Starting from the perspective of technological complementarity, this paper proposes a new approach for identifying technological opportunities by comprehensively using outlier patents and hot patents. The fusion analysis of innovative outlier patents and market mature hot patents is carried out to identify "innovation maturity" technological opportunities that combineinnovation and maturity, which is of great significance for enriching the theory and methods of technological opportunityidentification. [Method/Process] First, based on the "association distribution" characteristics of patent classification numbers, a twostagemethod was adopted to screen patents. In the first stage, we used the association rule algorithms to find classification numberswith weak and strong associations, and obtained initial outlier patents and initial hotspot patents. In the second stage, outlier detectionalgorithms were used to obtain the marginalization classification numbers of the two types of patents in the first stage. Patentscontaining marginalization classification numbers were selected as the final outlier patents, while patents containing suchclassification numbers were removed as the final hotspot patents. Second, different methods were adopted for patent screening basedon the differences in innovation and maturity of patent content. Using structured and unstructured data from patent databases, weconstructed time weighted indicators and keyword uniqueness indicators as the screening indicators for innovative outlier patents. Weconstructed a technology lifecycle stage discrimination function and patent market value measurement indicators as the screeningcriteria for mature hot patents in the market. The screened patents were classified into technical fields based on the major categories inthe International Patent Classification. Finally, we identified technological opportunities based on technological complementarity. Byusing the generative topology mapping algorithm to obtain a technical blank point map, the top K keywords in each blank point wereobtained, and the sources of the keywords were marked to ensure that new technological opportunities have both good innovationcapabilities and mature market prospects. In the future, keyword combinations derived from different types of patents were regardedas "innovation mature" technological opportunities. [Results/Conclusions] Taking the field of new energy vehicle batteries as anexample, empirical analysis was conducted to obtain a total of 10 technical opportunities in 5 sub technical fields. Through contentcomparison with relevant policy texts, 7 technical opportunities showed high consistency. It was found that the identification resultswere highly consistent with the current technological layout and development direction of the field, indicating that this method hasgood effectiveness and scientificity in technology opportunity identification, and can provide support for technology prediction andinnovation decision-making.

[Purpose/Significance] The rapid expansion of artificial intelligence generated content (AIGC) is transforming how intellectual property (IP) literacy is cultivated in universities. Conventional approaches, often constrained by disciplinary fragmentation, uneven teaching capacity, and time–space limitations, are increasingly misaligned with human-AI collaborative learning. Against this backdrop, IP literacy must integrate legal knowledge, ethical judgment, compliance awareness, and AI-enabled creative practice. This study clarifies the renewed connotations of IP literacy in the AIGC era, develops a theoretically grounded model of influencing factors, and examines how multiple educational conditions combine to generate high-level outcomes. By focusing on IP literacy rather than generic digital competence, the paper addresses a clear gap in existing research and offers a configuration-based understanding that links theory to implementable strategies for intelligent, student-centered IP literacy education. [Method/Process] Grounded in Activity Theory, the study developed a six-dimensional framework consisting of the following variables: teacher professional competence, AI-IP awareness, diversified educational support, role division, evaluation mechanisms, and AI resources. These variables were operationalized via a structured questionnaire. Fuzzy-set Qualitative Comparative Analysis (fsQCA) was then employed to identify conjunctural causality and equifinal pathways that extend beyond linear models. High-outcome configurations were achieved through variable calibration, truth-table analysis, and minimization. Robustness was confirmed by tightening the PRI consistency threshold from 0.80 to 0.85. The path structure, overall coverage, and overall consistency remained stable. [Results/Conclusions] Findings show that AIGC-enabled IP literacy emerges through multiple effective configurational paths, rather than a single dominant factor. Across high-outcome configurations, teacher professional competence, AI–IP awareness, and diversified educational support consistently function as core drivers that shape learning processes and outcomes. Evaluation mechanisms and AI resources act as complementary or substitutive conditions, reinforcing effectiveness under specific institutional and resource constraints. Three typical paths were identified: a path emphasizing practice generation coupled with collaborative organization; a path that integrates resource sharing with practice-oriented development; and a path highlighting collaborative division of labor and effective communication to compensate for limited technical supply. Together, these paths confirm the internal logic of the six-dimensional model and demonstrate that coordinated configurations, rather than isolated improvements, are necessary to optimize IP literacy education in AI-rich contexts. Practical implications include strengthening AI-oriented teacher development, embedding AI-IP awareness in curricula and supporting services, building cross-unit collaboration mechanisms, and aligning role division and process evaluation with available AI resources. Although the cross-sectional design and limited scope constrain generalizability, the results provide a theoretically grounded and empirically supported basis for developing intelligent, collaborative, and student-centered IP literacy systems and offer a foundation for future longitudinal and comparative research in AIGC-enabled higher education.

[Purpose/Significance] The effective flow of agricultural knowledge from innovation sources to fields is a core component of agricultural modernization. However, a persistent "structural knowledge gap" exists between macro-level knowledge supply and the micro-level needs of farmers, which traditional top-down extension systems often fail to bridge due to issues such as information decay, a lack of feedback, and poor contextual adaptation. In the context of promoting the high-quality development of rural public cultural services, grassroots reading spaces (e.g., rural libraries and village reading rooms) face a critical imperative to evolve beyond their traditional role as static repositories of books. This study reimagines grassroots reading spaces as dynamic "knowledge nodes" within rural socio-information ecosystems. The primary significance of this research lies in its innovative integration of public governance and knowledge management theories to construct a novel "node-interface-flow" analytical framework. It moves the discourse forward from predominant concerns with resource allocation or technology access to a deeper investigation of how internal governance mechanisms fundamentally shape these spaces' capacity to process and diffuse knowledge. By doing so, it positions the study at the intersection of rural studies, public administration, and knowledge science, offering a refined theoretical lens to understand and design rural knowledge infrastructure. Its practical importance stems from providing evidence-based, mechanistic explanations and actionable pathways for transforming these ubiquitous facilities from venues of "cultural provision" into active agents of "knowledge empowerment" for rural communities. [Method/Process] To uncover the mechanisms through which collaborative governance influences knowledge flow, this study employed a sequential explanatory mixed-methods design (QUAN → QUAL). The research was empirically grounded in a comparative case study of three rural reading spaces in China, deliberately selected through theoretical sampling to represent three distinct ideal-typical governance models: Jiangyin (exemplifying a deep contractual model involving long-term institutional agreements between local government and a vocational college), Liancheng (representing an administrative-dominant model operating within a standardized county-branch library system), and Yuhang (illustrating a social collaborative model based on government-purchased services from local social organizations). The methodological appropriateness of this multi-case comparative approach lies in its capacity to maximize variation in the key independent variable (governance model) while controlling for contextual factors, thereby allowing for clearer causal inference regarding the model's impact. Data were collected from March to August of 2024. The quantitative phase involved a structured questionnaire survey administered to 438 farmers across the villages served by the three case spaces (from 480 distributed, 91.3% valid response rate). The survey instrument was designed to measure key variables derived from the theoretical framework, including perceived interface quality (e.g., resource relevance, expert accessibility), knowledge acquisition, community knowledge sharing, and technology adoption intention. Reliability and validity tests (e.g., Cronbach's α, K-R20) confirmed the robustness of the measures. The subsequent qualitative phase comprised 38 in-depth, semi-structured interviews with space managers, active farmers, and key partners, supplemented by participatory observation and archival analysis. This phase aimed to provide rich, contextual insights into the operational mechanisms linking governance rules, interface functioning, and knowledge flow patterns. Quantitative data were analyzed using SPSS for ANOVA and regression analysis to test performance differences and mediation effects, while qualitative data were thematically coded using NVivo to elucidate underlying processes. [Results/Conclusions] The findings confirm the proposed "governance model → interface characteristics → flow efficacy" mechanism. The deep contractual model, through its "embedded interface," successfully couples strong formal institutional guarantees (e.g., mandated expert deployment, resource co-selection) with derived informal trust relationships from long-term embeddedness. This combination significantly drives the deep, closed-loop flow of highly complex, codified knowledge, completing cycles from external input to local application and feedback. In contrast, the social collaborative model's "networked interface," characterized by vibrant informal community networks activated by skilled social organizers, proves far more effective in stimulating the horizontal sharing, exchange, and co-creation of tacit knowledge within the community. The administrative-dominant model, with its standardized formal interface and underdeveloped informal connections, demonstrates limited efficacy, often resulting in interrupted, one-way knowledge flow. Based on these insights, the study proposes a two-dimensional model of "institutional depth" versus "networked breadth" to describe the unique effectiveness of different governance models. Based on these empirical results, three concrete policy and management recommendations have been proposed to foster responsive rural knowledge nodes: 1) shifting performance evaluation and resource allocation from static input metrics towards a focus on dynamic "interface capability"; 2) designing and institutionalizing specialized "knowledge broker" programs to staff these interfaces with trusted, skilled intermediaries; and 3) initiating collaborative "local knowledge repository" projects to systematically capture, digitize, and valorize indigenous community wisdom. The study acknowledges limitations regarding the generalizability of findings from a three-case comparison and suggests future research directions, including longitudinal studies to observe interface evolution, social network analysis to precisely map relational structures, and exploration of how digital "smart interfaces" might integrate with the social interfaces examined here to create new paradigms for rural knowledge service.

[Purpose/Significance] Digital hoarding has emerged as a significant behavioral phenomenon in the digital age, particularly prevalent among social media users who engage in the excessive acquisition and retention of digital content. This behavior is further amplified by algorithmic recommendation systems that continuously personalize content delivery. Although existing research has examined individual psychological factors or platform characteristics using static approaches, it lacks a dynamic perspective to understand the co-evolutionary relationship between platform strategies and user behaviors. This study addresses this research gap by introducing evolutionary game theory as an innovative analytical framework. Theoretically, the significance lies in modeling the dynamic interactions between platforms' algorithmic adjustments and users' hoarding behaviors. This provides new insights into the adaptive mechanisms within socio-technical systems. From a practical standpoint, this research offers valuable implications for promoting healthier digital environments and developing sustainable governance models for platforms that balance commercial objectives with user well-being. [Method/Process] This study employs evolutionary game theory to model the dynamic interactions between social media platforms and boundedly rational users. This method is well-suited for analyzing how strategies co-evolve over time towards stable states. Based on literature from user behavior and platform economics, a game-theoretic model was developed. Numerical simulations in MATLAB analyzed evolutionary paths across four platform types (Instant Messaging, Public, Short Video, and Vertical Community), with the model calibrated against empirical typologies to investigate how key factors influence long-term outcomes. [Results/Conclusions] The simulation results reveal that the evolutionary path of the platform-user interaction system is highly sensitive to key parameters, ultimately converging to different evolutionarily stable strategies (ESS) under varying conditions. A principal finding is that a unilateral increase in algorithmic recommendation intensity by platforms, while potentially boosting short-term engagement, does not guarantee long-term benefits and may instead drive users towards non-hoarding strategies due to increased cognitive burden. Crucially, the reasonable regulation of recommendation intensity is identified as the key to achieving sustainable, positive interactions. Moderate algorithmic recommendations can effectively alleviate information overload, reduce the negative impacts of hoarding, enhance user experience and satisfaction, and ultimately increase long-term platform benefits, creating a win-win scenario. The study provides significant managerial implications, suggesting that platform operators should incorporate user well-being metrics into algorithm evaluation frameworks, moving beyond purely engagement-driven models. Differentiated governance strategies are recommended for various platform types, such as implementing intelligent filtering on instant messaging apps and content quality incentives on vertical communities. However, this study has limitations, primarily its assumption of user homogeneity, which overlooks the impact of individual differences in preferences and digital literacy. Future research should introduce user heterogeneity, explore multi-platform competition scenarios, and validate the model with empirical data to enhance its practical predictive power and application value.

[Purpose/Significance] Seoul Outdoor Library has not only gained recognition from Seoul citizens, but has also received awards from the International Federation of Library Associations and Institutions (IFLA) for two consecutive years. Since its opening, it has served 8 million users, with a user satisfaction rate of 96.6%. Moreover, it attracts the attention of the library industry both domestically and internationally. Based on this, this paper extracts replicable and scalable practical experiences and insights from the successful case of Seoul outdoor library. Its research significance lies in both addressing the dilemma of "practice taking precedence over theory" in outdoor libraries, filling the academic research gap in this field, and providing practical guidance for the long-term, high-quality development of outdoor libraries in China. [Method/Process] The research conclusions drawn from single case study methods often possess greater enlightenment and relevance to reality. Based on this, the paper analyzes the basic situation of Seoul Outdoor Library through a single case study method. Moreover, the paper adopts the "triangulation verification" multi-source data collection method to enhance the validity and reliability of the research. We found that the main service contents include book reading services, space services, art literacy education, tourism information services, and policy display and promotion services. In addition, Seoul Outdoor Library exhibits green integration and sustainability in its design, flexibility and decentralization in spatial characteristics, openness and flexibility in scene characteristics, and emphasizes interaction and human-centered service. The innovative value of Seoul Outdoor Library is reflected in the coexistence of low-cost space supply and high satisfaction, deepening the connection between libraries and public affairs, and the organic integration of social and economic benefits. [Results/Conclusions] The paper holds that the development of outdoor libraries in China should start with several aspects. Firstly, outdoor libraries should be based on observation to promote the "rediscovery of libraries" initiative. For example, outdoor libraries rediscover the new value of space, the new role of librarians, and the new connotation of resources. Secondly, outdoor libraries should be endowed with values and infused with soul, making full use of local resources to endow them with spiritual cores. Thirdly, outdoor libraries should shape their output, and optimize scene construction. Finally, outdoor libraries should nourish the heart through implementation, deeply cultivate emotional experiences, and allow users to feel a sense of belonging through humanistic details. Of course, the paper inevitably has limitations. Future research will expand case samples to gain a more comprehensive understanding of outdoor libraries and facilitate their high-quality development in China.