[Purpose/Significance] Based on the health ecology model, this paper explores the correlations among chronic disease prevalence factors in older adults in China. By analyzing the correlations among the prevalence factors of multiple chronic diseases in the elderly, it aims to provide targeted classification guidance for prevention and treatment. [Method/Process] Using the 2018 China Health and Retirement Longitudinal Study(CHARLS) as the data source, after data cleaning, a final sample of 9,545 individuals aged 60 and above was obtained. With the occurrence of chronic diseases as the dependent variable, independent variables were included based on the health ecology model. The samples were grouped by gender differences. Binary logistic regression was used to analyze the correlations among the influencing factors of chronic disease comorbidity in elderly people of different genders. [Result/Conclusion] The prevalence of chronic disease multimorbidity among older adults is 65.7%(6 274/9 545). The comorbidity of chronic diseases in women(69.0%) is higher than that in men(62.3%)(P<0.05), and there are correlations among several risk factors. The results from multivariate logistic regression analysis show that ethnicity, childhood health status, noon sleep duration, night sleep duration, local medical status, and working status are shared risk factors for multimorbidity in both men and women, and these factors were correlated with each other. The main male-specific influencing factors for comorbidity are marital status[OR(95%CI) = 0.742(0.617,0.891)] and health insurance coverage [OR=1.864, 95%CI(1.251, 2.778)]. Marital status has a certain degree of correlation with local medical status and medical insurance. The main female-specific influencing factor of comorbidity is smoking [OR(95%CI) = 1.307(1.052, 1.625)], but the impact of smoking is less related to other influencing factors. Corresponding prevention strategies for multimorbidity in the elderly should be formulated based on the inter-correlated prevalence factors.

[Purpose/Significance] The sharing and utilization of medical data is the key to promoting clinical research and unlocking the value of data. This paper deeply explores the influencing factors of medical data controller sharing in China's clinical research scenarios, and reveals the path of multi-factor collaborative improvement in sharing practices. It aims to provide important references for the construction of scientific research big data platforms and sharing practices in medical institutions. [Method/Process] Based on motivation-opportunity-ability(MOA), social capital, and planned behavior theories, this study identifies key factors influencing data sharing by medical data controllers and constructs an analytical framework for this practice in clinical research scenarios. It applies the analytic hierarchy process(AHP) to calculate the influencing factors and index weights. Taking the scientific research big data platforms of 15 domestic medical institutions as case samples, this paper explores the colinearity among the influencing factors of medical data sharing from the qualitative perspective of configuration combined with the quantitative weight of analytic hierarchy process. [Result/Conclusion] The findings show that there is no single unnecessary condition that affects the sharing practice of medical data controllers. Three effective configurations are identified: “motivation-opportunity-capability”, “opportunity-capability”, and “motivation-opportunity” type. Among them, reciprocity under the motivation dimension and data quality under the ability dimension have played a key role in promoting the sharing practice of medical data controllers, while policy support under the opportunity dimension has a broader and more universal effect. In the future, the mutually beneficial consensus and collaboration mechanism should be further deepened, and the internal “motivation” should be strengthened. It should build a full-process data quality management system to consolidate the “capability” foundation, and refine policy guidance and risk control to consolidate “opportunities”.

[Purpose/Significance] Ancient Chinese medicine books contain unique diagnosis and treatment ideas, rich treatment experience and profound theoretical basis. The construction of semantic description model of ancient Chinese medicine books resources can realize the construction of multi-dimensional, refined and deep-level knowledge system and semantic information mining of ancient Chinese texts. [Method/Process] Based on the semantic description path of ancient books of gynecology of TCM, this paper analyzes ancient books of gynecology of TCM by means of semantic network knowledge representation method, formulates knowledge extraction rules of ancient books of gynecology of TCM, establishes conceptual semantic types and semantic relationships, and constructs conceptual semantic framework of knowledge of ancient books of gynecology. Protege was used to formalize the constructed network structure, and finally to construct the resource description model of traditional Chinese gynecology ancient books, in order to realize the efficient integration of ancient books resources and the construction of organizational framework based on deep semantics. [Result/Conclusion] A resource semantic description model for TCM gynecology ancient books was constructed, which provided empirical support for further deepening the knowledge organization and mining of TCM ancient books.

[Purpose/Significance] This study aims to explore the intrinsic formation mechanism and influencing factors of the information cocoon effect in the process of public information disclosure acquisition during public health emergencies. The findings are expected to provide decision-making references for governments at all levels, facilitate the effective “breaking of the cocoon”, and enhance the efficiency of public information acquisition and utilization. [Method/Process] Based on the S-O-R theory, this study identified the influencing factors of the information cocoon effect from the dimensions of internal and external stimuli and their behavioral responses to construct a theoretical model. A questionnaire was designed, and 341 valid responses were collected. Structural equation modeling and the bootstrap method were employed to analyze the data, revealing the formation mechanism and operational pathways of the information cocoon effect. [Result/Conclusion] In the specific context of public health emergencies, the information cocoon effect in public information disclosure acquisition behavior is a complex system formed by the interaction of internal and external factors. Essentially, it is a biased behavioral outcome driven by the combined stimulation of subjective and objective factors. Furthermore, information literacy plays a moderating role and serves as a key factor in mitigating the information cocoon effect in the process of public information acquisition in public health emergencies.

[Purpose/Significance] The integration of artificial intelligence technology into archival open access review work helps to improve the efficiency of archival open access review and, promote the open utilization of archival resources, which is one of the key priorities of future archival open access review work. [Method/Process] This article combines SOR theory to analyze the elements of the adoption behavior of artificial intelligence assisted archival open access review in comprehensive archives from three dimensions of “stimulus organism response”. Based on the interview texts of 45 comprehensive archives, the internal mechanism of such behavior is explored using phenomenological analysis research methods. [Results/Conclusion] The study finds that the generation mechanism of this behavior is “contextual trigger-cognitive judgment-behavioral feedback”. The contextual trigger mechanism includes multiple stimulus factors such as laws and regulations, data security, personnel security, input cost and output benefit, peer experience, and confidentiality bureau supervision. In the process of active or passive information search and communication in comprehensive archives, their psychological attitudes change positively or negatively, leading to behavioral feedback. By analyzing its mechanism content and functional relationships, a comprehensive archive artificial intelligence assisted behavior generation mechanism model for archival open access review is constructed to promote the intellectualization of archival open access review and improve the quality and efficiency of archival open access review work.

[Purpose/Significance] In the process of using generative artificial intelligence(Generative AI), users often find that the generated content does not meet their expectations and must optimize their interaction with the AI to obtain satisfactory results. However, research on the mechanisms underlying dialogue optimization remains underdeveloped. [Method/Process] This study explored the mechanisms of user dialogue optimization in the context of generative AI. Using grounded theory, the study conducted a coding analysis of 22 interview transcripts and 6 online documents to investigate the influencing factors, strategy content, and behavioral outcomes of user dialogue optimization in the context of generative AI usage. Based on this, a theoretical model of the mechanisms of user dialogue optimization behaviors was proposed. [Result/Conclusion] The findings reveal that task, user, and technology factors influence the content generation, which in turn affects user dialogue optimization. Typical strategies for dialogue optimization include content provision and instruction clarification, output format and structure optimization, feedback mechanisms and iterative optimization, task decomposition and step-by-step execution, the use and optimization of prompt engineering, and the leveraging of external resources. These strategies lead to enhanced user experience, user learning and alignment.

[Purpose/Significance] The data broker system in China is in the initial exploration stage, and a perfect data broker system has not yet been established. As an intermediary between the supply and demand sides of data market, and the promotion of value mining and ecological chain construction, analysis of data brokers' mechanism is helpful to solve the problem of information asymmetry and promote the circulation and transaction of data. [Method/Process] A data elements circulation trading system including data brokers participate was built based on the theory of information ecology. System dynamics method was used to analyze the causal relationship between factors, identify key variables, and carry out system simulation and sensitivity analysis. [Result/Conclusion] Data brokers play a matching role through intermediary services, and their professional ability and services directly affect the efficiency of data circulation transactions. Its mechanism of operation varies at different stages. In the stage of supply and demand matching, the efficiency of supply and demand docking is improved through accurate intermediary matching. In the stage of transaction matching, as an intermediary connector, the circulation channels of data resources is broadened, and the incoming transactions is matched. In the transaction execution stage, relying on third-party services such as compliance review and pricing evaluation, the risk is reduced and the compliance transaction is orderly promoted. In the future, the data broker system should be optimized, and the intermediary service efficiency and transaction conversion rate should be improved, to accelerate the realization of trusted circulation and value transformation of data.

[Purpose/Significance] This paper evaluates the capability of Chinese large language models to recognize textual fairness, constructs a corresponding fairness evaluation dataset and methodological frameworks, and promotes the fair and healthy development of large language models. [Method/Process] This paper constructed a sentence-level multidimensional fairness dataset comprising ten group categories, five text genres, and three fairness recognition tasks. The dataset was designed to evaluate the fairness recognition capabilities of eleven language models, including neural network language models, pre-trained language models, and large language models. Additionally, it examined changes in the performance of large language models after in-context learning. [Result/Conclusion] Compared to the relatively objective task of sentiment recognition, large language models exhibit a decline in performance on the more subjective task of harmfulness recognition, especially when considering the potential for harmfulness. The models struggle to learn new human-assigned values solely through instruction from prompt-based directives. In both sentiment recognition and harmfulness recognition tasks, large language models underperform compared to fine-tuned pre-trained language models specifically designed for these tasks. Additionally, the fairness recognition capabilities of large language models are influenced by the text's genre. However, after in-context learning through prompts, the fairness recognition capabilities of large language models show notable improvement.

[Purpose/Significance] This study proposes a citation pattern for identifying research contributions in scientific paper and refines its typology to offer an operational and structured classification standard. The aim is to support the automated analysis and evaluation of scientific papers and to enable the semantic-level quantification of research contributions. [Method/Process] The definitions and classification frameworks of research contributions were systematically reviewed to clarify their essential characteristics. Based on a large-scale corpus of English citation sentences, typical organizational structures of contribution expressions were identified, citation patterns were extracted, and the classification dimensions of the core elements within the pattern were further refined. [Result/Conclusion] A citation pattern for research contributions was established, formulated as: research contribution = contribution field + innovative work + influence value. Innovative work was categorized into four types: theoretical, methodological, applied, and cognitive. Influence value was classified along two horizontal dimensions and four vertical levels. The proposed citation pattern and classification framework provide a foundation for the automated identification and quantitative evaluation of research contributions and offer methodological support for advancing academic assessment from traditional bibliometric indicators to semantic-level analysis.

[Purpose/Significance] This study explores the approaches, driving mechanisms and optimization strategies for social forces' participation in rural new public cultural spaces, aiming to provide valuable insights for promoting high-quality rural public cultural services and improving social participation mechanisms. [Method/Process] Taking new rural public cultural spaces in Zhejiang Province as the research object, the study collected firsthand data through field investigations and in-depth interviews. It applied qualitative analysis to extract core dimensions of participation modes and driving factors, and employed fuzzy-set Qualitative Comparative Analysis(fsQCA) to identify the configuration paths of driving mechanisms under different participation modes. [Result/Conclusion] Social forces participating in new rural public cultural spaces mainly include enterprises, public institutions, social organizations, and individuals, with enterprises and individuals accounting for the majority. Participation modes can be categorized into four types: spatial construction, venue operation, content integration, and auxiliary support. Driving mechanisms are classified into six dimensions: ecological, strategic, institutional, interest-based, responsibility-driven, and demand-driven. Empirical results show that spatial construction and venue operation are often characterized by high-level participation driven by multiple interacting factors, whereas content integration and auxiliary support tend to follow medium-to low-level driven by single factors. Moving forward, efforts should focus on enhancing rural ecological conditions, optimizing institutional design, respecting value demands, and addressing diverse user needs, so as to comprehensively strengthen the motivation, mechanisms, and service capacity of social participation, and promote the high-quality and sustainable development of new rural public cultural spaces.

[Purpose/Significance] User relationships are a key variable for the survival and development of libraries. Exploring the change of user relationships in the new era can promote the innovation of library service models and high-quality development. [Method/Process] Based on the text analysis, the shortcomings of the traditional user relationship management model were diagnosed. It combined with the value co-creation theory to redefine the connotation of user relationship, constructed the user value co-creation relationship model, and proposed the four-dimensional realization path of value consensus, co-construction, sharing and co-evaluation. [Result/Conclusion] The traditional model is difficult to adapt to the diversified needs of users and the complex service ecosystem in the digital age. Value co-creation theory promotes the transformation of user relationship from “dual service” to “multiple co-creation” by reshaping user subjectivity, stimulating participation motivation, and expanding collaborative network. The model emphasizes that the library should take the open service ecosystem, dynamic demand matching, and benefit-sharing mechanism as the core, integrate the resources and capabilities of multiple subjects, form a sustainable value co-creation cycle, and provide systematic guidance for the service transformation and function extension of university libraries.

[Purpose/Significance] Research on the immersive interactive experience space and services in UK public libraries can provide reference for the development of related services of public libraries in China. [Method/Process] A survey was conducted in nine UK public libraries covering four public library immersive experience projects. The practices were investigated and analyzed, using website surveys, email inquiries, and a literature review. The investigation and analysis were done across 10 dimensions: service philosophy, regulations and systems, spatial design, construction methods, service types and methods, service resources, technological applications, experiential equipment, interactive design, and effectiveness evaluation. [Result/Conclusion] Immersive interactive experience spaces and services in UK public libraries are mature and advanced. Significant emphasis is placed on pre-implementation research and impact evaluation, resulting in the establishment of clear service philosophies and regulations. Diverse construction models are adopted, with a focus on holistic spatial layout and environmental design. A wide range of service types and delivery methods is provided, and distinctive service resources are created. Multi-dimensional interactive designs are emphasized, and cutting-edge experiential equipment and technology applications are featured. China can draw on the experience of UK public libraries by prioritizing pre-planning and strengthening top-level design, innovating construction models and optimizing spatial structures, developing service specializations and building diverse services, restructuring interactive elements and improving service effectiveness, and emphasizing post-implementation summaries and continuous service improvements.