Visual Analysis of Global Carbon Mitigation Research Based on Scientific Knowledge Graphs.

Governance effects of pollution reduction and carbon mitigation of carbon emission trading policy in China

Sustainable agriculture and good governance are part of the UN Sustainable Development Goals (SDGs), which have attracted great attention from all nations around the world. A scientific metrological and knowledge map analysis was conducted on the spatial–temporal evolution, collaboration network, research hotspots, cluster labels, frontier detection, and evolution path of 2350 pieces of data in this paper. The main results show that research hotspots such as sustainable development, rural development, agriculture, and others have influenced the development of the entire research process and have evolved into larger topic cluster groups such as ecosystem service, sustainable agriculture, land consolidation, and agricultural intensification. Research frontiers such as agriculture, integrated systems, smallholder systems, rural sustainable development, and land consolidation play key roles. Based on the findings, it is necessary to focus on the UN 2030 SDGs, combine the countries’ regional development needs and reality, and further clarify and refine the topics that need to be studied and the problems that need to be solved. More scientific demonstration and more feasible measures should be adopted to jointly deal with and enhance awareness of the current problems and practical challenges and further promote practical development by cohering academic consensus and expanding and innovating the governance models from the comprehensive dimensions of economy, politics, society, culture, and ecological environment so as to achieve good agricultural and rural governance.

<p> Background: The application of Unmanned Aerial Vehicle (UAV) is a major turning point in the history of power line inspection and is of increasing interest to a growing number of researchers. </p><p> Objective: This study aimed to clarify the research status, hotspots, and evolutionary trends of UAV power line inspection, to help researchers understand the dynamic evolution of research topics and provide guidance for future research directions. </p><p> Methods: 737 high-quality papers were collected from the Web of Science Core Collection (WoSCC) database from 2001 to 2023, and descriptive statistical analysis, cooperation network analysis, keyword co-occurrence analysis, keyword clustering analysis, and keyword citation burst analysis were conducted using VOSviewer and CiteSpace. </p><p> Results: The popularity of research in this field is increasing. Chinese academic institutions and scholars have made outstanding contributions. The level of cooperation between different countries, academic institutions, and scholars is low. The research on UAV power line inspection has a wide range of topics and obvious interdisciplinary characteristics, mainly focusing on fault detection and diagnosis, path planning, and the application of deep learning in intelligent inspection. The research hotspot and trend is the integration of artificial intelligence, deep learning, and modern information technology to achieve UAV autonomous intelligent inspection. Some of the challenges faced in the development of the field are also summarized and possible solutions are proposed. </p><p> Conclusion: This study provides a comprehensive and systematic review, and the results can provide a quick overview of the research status, hotspots, and evolutionary trends.

This paper describes the process of the construction of a scientific knowledge graph via semantic annotation and linking of academic research fields. The method aims to combine the broad scope of generic classifications of research areas with the specialized knowledge and domain fields of specific scientific classifications in order to build a unified scientific knowledge graph including all the research fields of the respective scientific areas in a common hierarchy. First, a survey of scientific classifications has been conducted in order to identify the ones that are the most common and complete for the knowledge graph to build upon. Classifications from different research domains have been used to semantically annotate their thematic topics and fields. The various scientific fields are connected based on their similarity, enlightening and creating, in this way, cross-domain research fields. A core scientific graph containing main fields of science with their relations to domain specific vocabularies and classifications has been created. This knowledge graph can be used to retrieve specific scientific fields in a related, broader or narrower, research area. Finally, a use case leveraging the semantic features of the graph is presented, indicating its usefulness for research activities and PhD web services.

Graph databases capture richly linked domain knowledge by integrating heterogeneous data and metadata into a unified representation. Here, we present the use of bespoke, interactive data graphics (bar charts, scatter plots, etc.) for visual exploration of a knowledge graph. By modeling a chart as a set of metadata that describes semantic context (SPARQL query) separately from visual context (Vega-Lite specification), we leverage the high-level, declarative nature of the SPARQL and Vega-Lite grammars to concisely specify web-based, interactive data graphics synchronized to a knowledge graph. Resources with dereferenceable URIs (uniform resource identifiers) can employ the hyperlink encoding channel or image marks in Vega-Lite to amplify the information content of a given data graphic, and published charts populate a browsable gallery of the database. We discuss design considerations that arise in relation to portability, persistence, and performance. Altogether, this pairing of SPARQL and Vega-Lite—demonstrated here in the domain of polymer nanocomposite materials science—offers an extensible approach to FAIR (findable, accessible, interoperable, reusable) scientific data visualization within a knowledge graph framework.

Ocean carbon sink is an emerging and interdisciplinary research area that plays a vital role in the global carbon cycle. This paper reviews recent scientific advancements in ocean carbon sink research, focusing on the mechanisms for capturing, utilizing, and sequestering atmospheric CO 2 , and highlights its contribution to climate change mitigation and adaptation. Using bibliometric analysis based on CiteSpace and data from the Web of Science and Scopus, we examine research hotspots and topic evolution through country collaboration, journal co-citation, and keyword co-occurrence networks. The findings show that ocean carbon sink research is shaped by complex scientific uncertainties and the integration of multiple disciplines. Current research hotspots include scientific advances, technological innovation, and governance challenges related to sustainable development. In general, recent studies emphasize the role of carbon sink, the value of nature, and the importance of precautionary management. This paper underlines the need for coordination between scientific and social dimensions of carbon sink functions, and it draws attention to the ethical aspects of carbon sink governance. It advocates for multi-stakeholder participation, precautionary governance, and policy-based financial system to support climate resilience and foster the sustainable development of the oceans.

In recent years, with the spread and popularization of health knowledge, more and more people have begun to participate in fitness exercises to strengthen their bodies and prevent diseases. However, due to the lack of fitness knowledge base and the imperfection of fitness recommendation algorithm, fitness enthusiasts cannot obtain accurate fitness knowledge. Therefore, how to recommend personalized content for users according to their preferences has become a practical topic. Therefore, based on the knowledge graph technology, this paper constructs the scientific fitness knowledge graph, and proposes a model R-CKGAT that integrates collaborative knowledge embedding, user preference propagation and knowledge graph attention mechanism. Experimental results show that compared with MF, CKE and other baseline algorithms, the AUC and ACC values of the proposed algorithm in the scientific fitness data set are better than those baseline algorithms. The AUC and ACC of the model were 92.76% and 88.67% correspondingly.

This study aims to explore the research situation of recent smart clothing based on summarizing the research hotspots and predicting the research trends in smart clothing through scientific knowledge mapping. The English literature related to smart garments collected in the Web of Science (WOS) core database up to 31 December 2023 was searched by the co-occurrence analysis method, and the visual knowledge mapping analysis was conducted. The study found that China has a high influence in the field of smart clothing, with the highest number of articles accounting for 44.95% (178 articles) of the total number of articles. The study authors are closely linked but do not form a core group of authors. The keywords and emergent words reflect the corresponding research hotspots for design, performance, emi shielding, pressure, thermal management, wearable electronics, composites and fabrics of smart clothing. With social and environmental technology development, smart clothing will be allowed in the coming period; the research prospect is broad and technological.

Autophagy plays a pivotal role in the progression and management of colorectal cancer (CRC). Recently, numerous articles focusing on the role of autophagy in CRC have emerged. The present study was conducted to provide a comprehensive analysis of the current state and changing trends in the relationship of autophagy and CRC over the past 20 years. The Web of Science Core Collection (WOSCC) was utilized to extracted all publications with respect to autophagy and CRC during 2002-2021. The contributions of various countries/regions, institutions and journals in this field were analyzed, moreover, research hotspots and promising future trends predicted through keywords were identified by the online platform of bibliometrics, CiteSpace and VOSviewer. A total of 2418 related publications from 2002 to 2021 were identified and collected. China occupied first place with respect to the number of publications, followed by the USA and South Korea. Shanghai Jiao Tong University published the most papers in this field. Most publications were published in Oncotarget. Additionally, analysis of the keywords identified 4 clusters with various research focuses: "mechanism-related research", "clinical-related research", "tumorigenesis research" and "chemotherapy-related research". The three latest hot keywords in this field were epithelial-mesenchymal transition (EMT), promote and invasion. The number of publications and research interest on autophagy and CRC are increasing annually, and the USA had prominent academic positions in the field. Shanghai Jiao Tong University represents a high level of research and the latest progress in this field can be tracked at Oncotarget. Throughout the research history of autophagy and CRC in the past 20 years, previous studies have mainly concentrated on apoptosis and drug resistance in tumor cells, while EMT in regulating tumorigenesis and development of clinical drugs that inhibit tumor invasion through autophagy may be novel hotspots in the future.

IntroductionAs a new trend, the digital economy will promote “digital industrialization” in the process of promoting “industrial digitalization.” It can accelerate technological innovation by adjusting managerial behavior and strategic decisions, promoting and protecting technological research and development, and providing technological infrastructure. While technological innovation, which generally occurs in enterprises, will promote a new round of upgrading, optimization, and even reshaping of the whole industry. The two are highly synergistic. Therefore, it is of great practical significance to study the impact of the digital economy era on enterprise innovation behavior.MethodsWe analyzed the impact of the digital economy era on corporate innovation behavior in the Web of Science database from 2010 to 2020 through bibliometric and scientific knowledge mapping methods.Results and discussionOur study found that: the research on enterprise innovation behavior in the digital economy era has formed eight research directions, such as expertise, human capital FSA, integration in global value chains, financial innovation, fintech, people preference shift, internet of everything, and consumer co-creation. In addition, the research hotspots on enterprise innovation behavior in the digital economy era range from enterprises’ perception of digital economy contact, to enterprises’ familiarity with digital technology and its application, to enterprises’ attempted evolution of digital transformation, reflecting the potential of both theoretical and practical characteristics. Finally, we present an outlook on the future cross-sectional development of research on enterprise innovative behavior in the digital economy era and propose a research trend based on the Chinese context.

As global climate change intensifies, the ocean carbon sink has become a crucial natural mechanism for the international community to mitigate and adapt to climate change, owing to its vast carbon storage capacity and continuous absorption capabilities. China has a wealth of blue carbon ecosystems and recognizes the significant potential of ocean carbon sinks in addressing climate change. Currently, China is incorporating the development of blue carbon into its national strategic development plans. Through policy guidance, scientific and technological support, and pilot demonstrations, the country is actively exploring pathways for the protection, restoration, and sustainable use of blue carbon ecosystems. However, issues such as marine habitat degradation, the absence of specific domestic legislation, and an incomplete standards system for ocean carbon sinks are constraining the effectiveness and market-based development of China’s carbon sinks. To this end, this study proposes that China should actively promote the restoration of marine ecosystems, strengthen domestic legislation for carbon sink trading, and advance the clarification of property rights and the refinement of market rules. At the same time, China should deepen multi-level international cooperation and accelerate the development of a marine carbon sink standard system with Chinese characteristics that aligns with international standards. Through the synergistic advancement of institutions, technology, and cooperation, the full ecological and economic value of ocean carbon sinks can be unlocked, providing robust support for China to achieve its “dual carbon” goals and participate in global climate governance.

The purpose of this paper is to help better understand pre-service training for inclusive preschool teachers in China; to grasp the research context, evolution research hotspots and trends of pre-service training for inclusive preschool teachers in China. In this paper, we use the scientific quantitative knowledge graph method and using Cite Space visualization software to analyze 111 studies from 2009-2023 in CNKI (China National Knowledge Infrastructure) databases, Such as literature publication trend graph and analysis, keyword co-occurrence analysis, keyword clustering analysis, research hotspot analysis and research prospects. The results show that the current hot research on pre-service training for inclusive education teachers is mainly focused on: pre-service training for inclusive education literacy of preschool teachers (it includes the research of the concept, connotation, status quo and pre-service training of preschool inclusive education teachers); pre-service talent cultivation models for inclusive early childhood education and design of inclusive early childhood education course; future research on inclusive education for pre-service preschool teachers can actively explore three aspects: First, according to the China’s policy requirements for the training of inclusive teachers in colleges and universities, the preschool education major must clarify the pre-service training plan for preschool inclusive teachers. Secondly, it should analyze the social needs for preschool inclusive teachers and develop and design pre-service preschool inclusive education courses. Finally, pay attention to pre-service practice inclusive education and improve the pre-school inclusive education pre-service curriculum system.

ObjectiveTo identify author collaborations and impact; participating countries, institutions, and journals; evaluate the knowledge base; and analyze research hotspots and frontiers in teaching reforms in physiology.MethodsArticles and reviews related to teaching reforms in physiology published between January 1, 2012, and December 31, 2021, were obtained from the Web of Science Core Collection. Two Scientometric software applications (CiteSpace 5.7 and VOSviewer 1.6.15) were used to perform bibliometric and knowledge-map analysis, generate network maps, and identify research trends and top keywords, authors, co-cited authors, institutions, countries, journals, and references.ResultsThe search identified a total of 2,882 papers in 466 academic journals by 13,895 authors from 4,072 organizations in 67 countries/regions. Physiology teaching reform-related publications increased rapidly over time. Arango-Lasprilla and Rivera published the most papers, while Moseley had the most co-citations. Active collaborations among physiology researchers were noted. Advances in Physiology Education published the most papers on physiology teaching reforms and was also the top co-cited journal in the Medicine/Medical/Clinical, Psychology/Education/Health, and Neurology/Sports/Ophthalmology fields. The United States and University of California published the most physiology teaching publications in the search criteria. Ten references (research articles and reviews) on mechanisms and diseases were identified as the knowledge base. The mainstream research directions were education, Alzheimer’s disease, performance, physiology, and risk factors. Mental health and emotion regulation are increasing in significance and may become new hotspots. The research trend to move from the field of pain pathogenesis to the field of neuropsychiatry has become increasingly clear. This tendency away from peripheral system-based disorders to central system-based orders is inextricably linked to further developments in physiological understanding of the brain.ConclusionThis study analyzed the research hot spots and frontiers of teaching reforms on in physiology using bibliometric and visual methods. Based on the results, rehabilitation, neurosciences, and infectious disease are hot topics in physiology. In particular, the pathogenesis of neurological diseases, treatment strategies, and technology updates have gradually become research hotspots. We predict that this trend is closely related to the implementation of brain research programs in various countries. These findings provide helpful references for scholars focusing on physiology education.

Robust carbon cycle science and effective carbon market governance depend on accurate monitoring, transparent modelling and credible representation of climate–economic feedbacks. Integrated Assessment Models (IAMs) such as RICE provide a long-standing framework for linking carbon emissions, climate dynamics and economic development and are widely used to inform mitigation pathways, carbon pricing and international climate policy. However, traditional IAMs rely on hand-calibrated parameters, simplified damage functions and fixed ethical assumptions, limiting their ability to integrate observational data, quantify uncertainty and support evidence-based carbon management. We build on recent advances in machine learning for climate policy and introduce RICE-N-JAX, a fully differentiable implementation of the multi-region RICE-N model (Zhang et al., 2025). RICE-N extends classical IAMs with multi-agent reinforcement learning to model strategic interactions and international climate negotiations. Our JAX-based reimplementation makes the entire climate–economic simulation fast and differentiable, including carbon emissions, climate response, production, trade, mitigation decisions and negotiation dynamics. Differentiability enables a new class of hybrid, data-driven climate–economic models. Our current research focuses on two key directions. First, we develop non-parametric hybrid damage functions in which the traditional analytical damage formulation is replaced by neural or spline-based surrogates trained on empirical and scenario data. This allows the damage–temperature relationship to be learned directly from data. Second, we perform inverse modelling of ethical and behavioural parameters, such as regional risk aversion, time preferences and mitigation bias, by calibrating the model against emissions, GDP and temperature trajectories from the Shared Socioeconomic Pathways (SSPs). This enables the recovery of latent normative assumptions embedded in scenario narratives and provides a data-informed basis for policy analysis. Finally, differentiability supports gradient-based calibration, uncertainty quantification, and sensitivity analysis of carbon price trajectories, mitigation pathways, and long-term climate impacts. We demonstrate a proof-of-concept end-to-end calibration of climate damage functions and show how parameter uncertainty propagates into future economic and emissions outcomes. By bridging process-based climate–economic theory with hybrid, knowledge-guided machine learning, RICE-N-JAX provides a foundation for fast and data-driven carbon-cycle modelling. The framework supports policy-relevant applications ranging from carbon pricing and climate clubs to carbon market design, illustrating how hybrid ML can strengthen the scientific basis of carbon management and climate mitigation.

Research trends and hotspots in biologics for plaque psoriasis: A bibliometric study from 2004 to 2023