[Purpose/Significance] In order to promote the healthy and orderly development of open science, governments, academia and industry in many countries have agreed that policy should play a role in guiding, supporting and regulating open science. A systematic study on the issue of why open science can be entered the policy field, is of a great significance for revealing the evolutionary logic of open science policy formulation, distinguishing the values pursued by open science policies, and providing theoretical support for the promotion of special open science policies and the sustainable development of open science. [Method/Process] Considering the multiple streams theory and combination with the specific problem thresholds of open science in China,this paper proposes an analytical framework for setting the policy agenda for open science,namely that: 1) the actual requirements for the development of science, technology, and the economy, adverse feedback on the current policies and public health emergencies constitute the problem stream. 2) existing policies and recommendations of experts and scholars constitute the policy stream. 3) the political ideas held by the leadership group and the national emotions represented by the researchers and ordinary people constitute the political stream. On this basis, by analyzing the formulation of relevant policies, the practical progress and research status of open science in China, this article clarifies the reasons why "open science" has become the content regulated by the Science and Technology Progress Law of the People's Republic of China. [Results/Conclusions] This paper believes that: 1) In terms of the problem stream, the achievements of China's national science and technology innovation system construction have provided a large amount of human resources, knowledge resources and infrastructure resources for promoting open science, laying a solid foundation for the development of open science. However, China's requirements for openness and sharing in science and technology are scattered in different policy documents, making it difficult to form a policy synergy to jointly promote the vigorous development of open science. Given the impact of the COVID-19 pandemic on academic communication and research paradigms, it is necessary to shift the focus of open science policy from a social problem to a policy issue. 2) In terms of the policy stream, many policies formulated and implemented by the Chinese government, research funding agencies and scientific research and education institutions involve the relevant content of open science, which provide important support for the entry of open science into law. 3) In the terms of the political stream, the Party and government in China have paid close attention to the issue of open science, treating it as an important topic for national scientific and technological innovation. This has been intertwined with the call from the general public for open science, which has made it a leading force in bringing open science to the attention of policymakers. 4) The convergence of these three streams, with the construction of Digital China rising to the national strategic level and the launch of UNESCO Recommendation on Open Science has pushed open science onto the policy agenda. Finally, this paper suggests that Chinese government departments and relevant institutions take systematic measures to ensure the effective implementation of open science policies.

[Purpose/Significance] Short video platforms have become the core arena for the digital presentation and dissemination of intangible cultural heritage (ICH). However, the "Matthew Effect" in the digital attention economy often causes high-quality ICH content to be submerged. Existing research predominantly suffers from "modal segmentation," focusing on single modalities such as text and visuals in isolation, which fails to explain how these elements synergistically drive user engagement. To address this gap, this study constructs a communication effect evaluation model based on multimodal machine learning. The innovation of this research lies in integrating computational communication methods with traditional persuasion theories, moving beyond simple content analysis to a quantifiable predictive framework. By identifying key influencing factors through data fusion, this study provides a scientific basis for optimizing the digital production strategies of the ICH content, offering significant value for enhancing the visibility of traditional culture and overcoming the barriers of digital dissemination. [Method/Process] This study integrates the elaboration likelihood model (ELM) and media ritual theory to establish a "cognitive-behavioral-cultural" dual-path analytical framework. Theoretically, the study maps content quality (video/audio/text) to the "Central Route" and source credibility (author attributes) to the "Peripheral Route." Empirically, focusing on ICH videos on Douyin as the subject, the study collected data from May 2024 to May 2025. After rigorous cleaning, a dataset of 2,869 valid samples was established. The study employs a multimodal feature engineering approach: visual and textual features are extracted to represent content quality; audio features (including FBank and MFCC) are processed using the OpenSMILE toolkit to capture prosodic and spectral characteristics; and author data are collected to quantify social influence. The Random Forest algorithm is utilized to fuse these heterogeneous data sources, analyze feature importance, and predict communication effectiveness. [Results/Conclusions] The empirical results demonstrate that the multimodal fusion model significantly outperforms single-modality approaches in predicting communication effects, confirming that ICH dissemination is a result of complex symbol interaction. Feature importance analysis reveals a distinct hierarchy: Author attributes make the highest contribution, indicating that the "Peripheral Route" - driven by the creator's social capital - is the decisive factor in determining communication heat. Its persuasive power far surpasses that of the content itself. Regarding content modalities, text and video follow in importance, serving as critical tools for user retention, while the audio modality holds supplementary semantic value by setting the emotional atmosphere. The study does not account for dynamic temporal changes or external trending events. Effective ICH dissemination requires a synergistic strategy: prioritizing the accumulation of the author's social influence as the core driver, while simultaneously optimizing visual and textual quality. Future research should incorporate time-series analysis to capture dynamic communication trends.

[Purpose/Significance] This paper examines the ongoing transformation of library information systems, shifting from platform-oriented architectures to agent-based ones, in the context of generative artificial intelligence. It argues that, although Integrated Library Systems (ILS) and Library Services Platforms (LSP) have improved workflow automation and resource management, they remain constrained by poor semantic understanding, restricted cross-system orchestration, and insufficient support for proactive, personalized services. Building on these observations, the paper proposes a transformation path in which existing ILS/LSP infrastructures are not discarded, but rather re-positioned as providers of capabilities within a broader ecosystem of generative intelligent agents. This provides libraries facing both legacy constraints and pressures for service innovation with a feasible evolution strategy. [Method/Process] The study first reviews service-level limitations of ILS and LSP through the lenses of interaction patterns, data openness, and intelligent service support, and distills typical pain points encountered in cataloging, circulation, reference services, and subject liaison work. On this basis, it constructs a graded capability model for generative intelligent agents that encompasses semantic perception, context modeling, goal-driven behavior, preference adaptation, and reflective evolution. It also discusses how different types of agents can be aligned with specific library roles and task granularities. The study then proposes a three-layer architecture consisting of a basic service layer, an agent coordination layer, and a semantic interaction layer. The bottom layer exposes atomic capabilities such as search, metadata editing, authentication, and logging; the middle layer orchestrates multiple agents via lightweight protocols and shared task states; and the top layer supports natural-language-driven interaction while maintaining semantic consistency and traceable reasoning paths. Finally, leveraging a "Library Assistant" prototype that integrates these components, the study designs and conducts experimental evaluations in bibliographic follow-up and recommendation scenarios, combining task-based user tests with qualitative feedback from librarians and domain experts. [Results/Conclusions] Experimental results indicate that the proposed architecture outperforms traditional models in terms of answer relevance, interaction fluency, and perceived service intelligence, particularly in multi-step information-seeking and follow-up recommendation tasks. At the same time, the study found that the mechanisms for long-term memory, cross-session user modeling, and explicit feedback loops were underdeveloped. This can lead to inconsistencies in sustained interactions and complex task chains. The paper concludes with a discussion of the design implications for the evolution of library systems, suggesting that future work should focus on trustworthy memory management, transparent agent coordination, and robust evaluation metrics. It also recommends the development of governance frameworks that jointly consider system performance, user experience, professional ethics, and institutional policy requirements together. In this way, the study provides both a conceptual blueprint and empirical evidence to guide the transition from platform-oriented systems to agent-based, generative AI-enabled library architectures.

[Purpose/Significance] This study explores the characteristics of organized research collaboration among humanities and social sciences (HSS) researchers and their impact on paper output, aiming to optimize such collaboration and provide theoretical and practical support for enhancing the effectiveness of organized research in HSS. [Method/Process] We selected 163 high-impact scholars serving as chief investigators of Major Project supported by the National Social Science Fundation of China from 2015 to 2021 as the research subjects, and used their papers funded by these projects and published in the Chinese key journals as the data source. Nine explanatory variables (e.g., co-authorship degree, co-authorship rate) and five explained variables (e.g., first-author publication volume, relative publication volume) were designed. Factor analysis was employed to reduce dimensionality and extract three common factors of organized research collaboration: "collaboration stability and intensity," "collaboration breadth and depth," and "collaboration diversity." Combined with control variables such as gender, educational background, and administrative positions, Spearman correlation analysis and multiple linear regression models were used to empirically test the impact of organized research collaboration characteristics on academic paper output. [Results/Conclusions] Under the organized research paradigm: 1) Organized research collaboration characteristics' common factors exhibit a significant inhibiting effect on the quantity of academic paper output; 2) Organized research collaboration characteristics demonstrate a significant enhancing effect on the proportion of high-impact papers; 3) Individual characteristics show no significant effect on academic paper output. Corresponding implications are drawn from the perspective of promoting high-quality development of organized research collaboration in HSS. We put forward some suggestions. Research management institutions should promote interdisciplinary and cross-domain collaborative innovation, optimize research evaluation to guide the quality of cooperation, and strengthen regional collaboration and international cooperation networks. Research institutions should enhance the development and management of research teams, intensify academic exchanges and capacity training, and optimize the allocation of research resources. Researchers should dynamically adjust their cooperation strategies, make good use of digital tools to streamline cooperation processes, balance administrative duties with academic outputs, and attach importance to the training of young scholars.

[Purpose/Significance] With the rapid development of technologies such as artificial intelligence, big data, and cloud computing, digital-intelligent technologies are profoundly revolutionizing the service models and management frameworks of public libraries. This study is based on the development background of the digital-intelligent era under the 15th Five-Year Plan. It investigates the smart library services of theNational Library, the Hong Kong Central Library, the Macao Central Library, libraries in theTaiwan region, and 31 provincial-level public libraries across China. The analysis focuses on the current research progress in smart library services provided by public libraries, examining both service content and methods. [Method/Process] This research employed a comparative analysis method, comparing the smart library services of 31 provincial-level public libraries in China with those in Hong Kong, Macao, and the Taiwan region to identify regional differences and development gaps. The investigation reveals that the development of smart library services in public libraries in China exhibits significant regional imbalances. Public libraries in economically developed regions demonstrate a significantly higher level of smart library services compared to those in less developed areas. / [ResultsConclusions] Based on the findings, this study proposes development strategies for smart library services in public libraries within the digital-intelligent environment. These strategies include building an intelligent technology management system, establishing tiered smart service standards, cultivating a multidisciplinary team of smart librarians, creating an inclusive smart service system, developing an integrated smart resource platform, designing blended physical-virtual smart service spaces, and fostering collaborative innovation in smart service alliances. The challenges faced and the experiences gained by public libraries during the "14th Five-Year Plan" period provide critical insights for the formulation of the "15th Five-Year Plan," while also representing core issues that must be acknowledged and addressed in the journey of the "15th Five-Year Plan." This necessitates the development of scientific and effective strategies by public libraries, which is also a key task of the "15th Five-Year Plan." As a pivotal phase for the innovative development of public libraries, the "15th Five-Year Plan" period should actively implement national policies, with each library formulating development strategies and specific measures for smart library services based on the needs of public cultural development and their own practical circumstances. Grounded in the context of the "15th Five-Year Plan" and building upon the current state of smart library services in provincial-level public libraries during the "14th Five-Year Plan" period, this paper proposes strategies for smart library services in public libraries during the "15th Five-Year Plan" period in the digital-intelligent era, with the aim of contributing to the promotion and development of smart library services in public libraries nationwide.

[Purpose/Significance] Although traditional Chinese Medicine (TCM) classics contain valuable knowledge they remain difficult to process automatically due to their complex page layouts, coexistence of traditional and simplified variant characters, alias-rich terminology, and strong cross-paragraph semantic dependencies. Existing pipelines often split the processes of optical character recognition (OCR), normalization, entity recognition, relation extraction, and entity alignment. This leads to error propagation. Additionally, many studies also focus on modern clinical texts rather than historical sources. This paper addresses these gaps by presenting an end-to-end pipeline that transforms ancient page images to a structured knowledge graph. The central contribution is the CoTCMKE, which is a chain-of-thought (CoT) and ontology-constrained joint model that performs named entity recognition (NER), relation extraction (RE), and entity alignment (EA) simultaneously. By making intermediate reasoning explicit and binding predictions to a TCM ontology, the framework improves batch digitization efficiency, extraction accuracy, and interpretability for digital humanities and library & information science (LIS) applications. [Method/Process] We built a unified pipeline with three steps. 1) Text recognition: a multimodal large language model (MLLM) recognizes text directly from complex pages with mixed vertical/horizontal layouts and performs context-aware traditional-to-simplified conversion. 2) Ontology construction: following semantic completeness, multimodal friendliness, evolvability, and interoperability, experts curate an ontology of core TCM concepts (e.g., diseases, symptoms, formulae, herbs) with aliases and constraints to guide decoding and ensure consistency. 3) Knowledge extraction: CoTCMKE integrates CoT with ontology constraints for multi-task extraction, which is entity localization and normalization, ontology-consistent relation generation, and cross-passage/cross-volume entity alignment. Constraint-aware decoding uses immediate checks and backtracking when a generated entity or relation violates ontology rules or alias mappings. For data, we used Shang Han Lun. Qwen2.5-VL-32B assists OCR, conversion, and initial auto-labeling; two TCM-trained annotators independently review and reconcile results. The final sets contain 2 340 NER items, 1 880 RE items, and 450 EA pairs, evaluated with 10-fold cross-validation. The multimodal large language model (MLLM) was adapted via LoRA with early stopping. The comparisons include traditional deep models, a unified IE framework, prompt-only inference, and a LoRA-SFT baseline. [Results/Conclusions] On Shang Han Lun, CoTCMKE outperformed LoRA-SFT by +3.1 F1 for NER, +1.6 for RE, and +1.3 for EA. In cross-book transfer to Jin Kui Yao Lue, the model maintained stable performance without retraining, indicating robustness and scalability. Ablation results showed that CoT reduced boundary and ambiguity errors, while ontology constraints curbed illegal triples and alias fragmentation. Combining both yielded the best overall results. The analysis yielded the following observations. 1) explicit medical relation templates act as semantic guardrails; 2) proactive alias consolidation before decoding reduces entity scattering and improves alignment; 3) explicit type-path guidance helps disambiguate fine-grained categories (e.g., pulse findings vs. general symptoms). The framework supports the automatic construction of "formula-symptom-herb" triples, as well as alias and variant normalization. It also supports evidence-linked semantic searches and navigation, which benefit LIS workflows, education, and research. Current limitations include the scope of the curated ontology and its focus on two classics. Future work will extend to additional TCM classics and broader historical corpora, support continual incremental learning, and deliver knowledge services based on the constructed graphs.

[Purpose/Significance] In 2025, significant reforms were made to the South African intelligence system. Currently, the academic community in China lacks substantial research on the South African intelligence system and its reform. Providing an explanation and evaluation of the main motivations and basic contents of this reform would give all sectors a comprehensive and systematic understanding of the South African intelligence system. It would also provide a reference point for improving relevant systems in China. [Method/Process] We used a literature analysis method to study the main reasons for South Africa's 2025 intelligence reform, and adopted a normative analysis method to examine the fundamental aspects of this reform. [Results/Conclusions] The 2025 intelligence reform in South Africa is a response to the new era of national security threats, democratic governance of intelligence, and constitutional court rulings. This reform has reorganized the civilian intelligence structure, authorized the bulk interception of communications by intelligence agencies, and increased supervision of these agencies. This reform marks a return to the "intelligence philosophy" of 1994 and could enhance South Africa's capabilities in terms of national security governance. However, it does not clarify the National Security Councils position or its relationship with the intelligence community. Furthermore, intelligence agencies' control of bulk interception procedures is not yet strict. There are also doubts about the rationality of the establishment of the National Intelligence Academy. Although there are differences between China and South Africa in terms of politics, economy, culture, etc., South Africa's intelligence reform in 2025 still has important reference value for China. One is to scientifically allocate national intelligence power, which should be clarified by amending the National Intelligence Law to define the purpose and specific reasons for intelligence reconnaissance measures, and to clarify the applicant, conditions for approval, the subject of approval, the content of reviews, and execution procedures. The second is to strengthen the supervision of intelligence power by improving the mechanism for the full process of the prior authorization, in-process and post-supervision of intelligence reconnaissance measures. Thirdly, we should establish a specialized national intelligence academy to strengthen training management in terms of training philosophy, target selection, training content, and career development, and promote systematic education and training for intelligence personnel. In short, we need to strengthen research not only on the intelligence systems of developed countries, but also on those of countries in the Global South. We should adopt an open attitude, and absorb excellent experiences from around the world, providing intellectual support to help China modernize its national security system and capabilities.