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To deeply analyze the performance of paper-cutting elements in interior space design, this paper explores the artistic expression of paper-cutting elements. The BIM model is constructed based on the TVL algorithm, and a noise-reducing style migration method with an additional total variable loss function is used to fuse the texture features of a specific paper-cutting style so that the paper-cutting texture is generated in the target object area more intensively. The algorithm is supplemented with a U-shaped network structure to obtain the mask map of the target object, modify and expand the ScanNet training data set, and input a content map and a style map to generate the stylized paper cutout image automatically. The results show that compared with other elements, the stability of paper-cut elements reaches 96.31%, the image smoothness reaches 89.34%, and the retention of significant regions reaches 93.26%. In modern design, the peak signal-noise of paper-cut elements improved by 13.418d on average, the structural similarity also improved by 0.34807, and the recognition rate of paper-cut elements in the furnishing category reached 95%. Applying paper-cut art in interior space design can give interior furnishing design better visual effects, provide inspiration and ideas for interior space design innovation, and contribute to improving aesthetics.

The study of metadiscourse word resources is an important way to reveal academic knowledge constructs and genre features in English papers. This paper selects intra- and interdisciplinary English academic papers as data samples, and the text representation is based on the vector space model. The text similarity is calculated using the word movement distance model to complete the clustering based on the density peak, and then the semantic annotation of metadiscourse verb patterns is performed using the conditional random field. Then, the intra- and interdisciplinary metadiscourse annotations are compared to analyze the variation of verb patterns. The intra-disciplinary variation of metadiscourse verb patterns was mainly found using attitude markers, where the log-likelihood ratios of 48.56, 30.25, and 35.64 were obtained for affirmative, critical, and critical declarative attitudes, respectively. In interdisciplinary studies, basic disciplines preferred to use verb patterns as transitions, while applied disciplines preferred to express the author’s point of view. The study of metadiscourse verb patterns effectively enriches the linguistic resources in academic English teaching and deepens the understanding of the characteristics of disciplinary essay genres.

To solve the problems of fuzziness, nonlinearity and complexity of economic factors and environmental factors in the evaluation of ecological economic benefits of enterprises are studied. Based on the theory of environmental-economic benefits (EEB), this paper defines the value of environmental resources and economic benefits of enterprises, and puts forward the indicators of environmental and economic benefits. The evaluation model of enterprise EEB based on the analytic hierarchy process and fuzzy set algorithm is constructed. By establishing the hierarchical structure model of index system, the intuitive fuzzy judgement matrix is obtained, and the final score of enterprise environmental benefits is calculated by consistency test and weight analysis. After verifying the model, the evaluation method of enterprise EEB proposed in this paper is accurate and reliable, which is helpful to deeply analyse the hidden order and adaptation mechanism of complex adaptation system of enterprise environmental management.

In order to conform to the development of the times and effectively promote the reform of vocal music education in colleges and universities, this paper proposes an innovative path of diversified vocal music education reform in colleges and universities under the modern advanced educational concepts that are steadily gaining utilisation and popular acceptance in China and the West. In this paper, the passive collective behaviour of biology is introduced in the teacher stage in the basic TLBO algorithm, and then the feedback stage is added after the student stage to increase the effectiveness of students’ learning methods, maintain the diversity of students and make available a system the deployment of which would swiftly bring students with poor grades to the attention of teachers; to this end, the algorithm is made to perform a local fine search, and the optimisation accuracy of the algorithm and its global search ability are improved. Finally, based on the numerical simulation of the standard test set and compared with the existing optimised TLOB algorithm, it is concluded that 92% of the solutions in the ETLBO are dominated or not dominated by the solutions in the non-dominated solution set of the optimised TLBO, while only 2% of the solutions in the non-dominated solution set of the optimised ETLBO are dominated by the non-dominated solutions of the TLBO. Centralised solutions dominate or do not dominate each other. It is concluded that the optimised TLBO algorithm has the best solution ability and also has practical application significance.

In digital rural governance, the effective integration of accounting and rural development is crucial for maximizing rural economic benefits. This paper uses CiteSpace software and LDA modeling to examine the current state and hot topics in rural accounting research from 2018 to 2022. The study was visualized by analyzing valid literature and using perplexity to determine the best effect of topic extraction. The results show that the number of annual publications in this field continues to grow, and the number of universities and institutions publishing relevant papers is also increasing yearly. Regarding research hotspots, the keyword “rural” appears most frequently, reaching 122 times, followed by “financial management” with a frequency of 106 times. The keyword with the highest centrality is “rural revitalization”, with a centrality as high as 0.38. The research keywords are mainly divided into rural revitalization and financial management, with the financial management group being the most dominant. However, the number of studies on rural revitalization has been increasing yearly, and the gap between them has been narrowing. The importance of accounting is growing in promoting rural revitalization and improving rural economic efficiency.

There is a close relationship between abnormal lipid metabolism and tumor malignant behavior, and abnormal lipid metabolism plays a crucial role in developing malignant tumors. Based on BiLSTM model, combined with Transformer Encoder and CRF decoder, the article successfully constructed a joint extraction model of medical literature, and with the help of Neo4j technology, built the knowledge graph of lipid metabolism abnormality and tumor occurrence and development. The study used data sources from WOSCC, CNKI, Wanfang, VIP, and other databases as data sources. It used bibliometric analysis and tools like CiteSpace and VOS viewer to visualize and analyze related studies in-depth. The study results showed that Oral Oncology in the UK ranked first in abnormalities of lipid metabolism in the number of publications, with a total of 301 related papers and an impact factor of 5.118. The number of studies related to oncology increased from 11 in 2010 to 414 in 2023, with a growth of more than 36.64 times. By comprehensively analyzing the current situation of abnormal lipid metabolism and tumorigenesis and development, this paper provides new ideas and perspectives for the study of cancer prevention, diagnosis, treatment and mechanism. It helps to promote the in-depth research and development of related fields.

In-depth research on landscape art interrelating with interior and exterior space design is still relatively limited. In this paper, we use gray correlation analysis to investigate the connection between landscape art and indoor and outdoor space design to better understand and apply the potential of landscape art in design. In this paper, we investigate the application of landscape art in indoor and outdoor space design, including the Use of landscape gardening techniques and landscape formation types. The study constructed an evaluation index system, including 16 indicators for road landscape, site landscape, green landscape and other types of landscapes, which were screened and weighted according to systematicity, operability, participation, dynamism and the combination of qualitative and quantitative indicators. We used AHP to determine the indicators’ weights and gray correlation analysis to calculate comprehensive scores for different design solutions. The best indoor and outdoor design solutions were determined by comparing and ranking the evaluations of various design solutions through case studies and statistical analysis. The method facilitates the scientific assessment and selection of indoor and outdoor design solutions to enhance the quality of design and the comfort of the human environment.

Since the birth of Bitcoin, blockchain technology has been widely used in many fields, such as finance, supply chain management, smart contracts, etc.and has been highly valued for its decentralized and tamper-proof characteristics. With the expansion of application scenarios, blockchain faces inefficient data processing challenges, particularly in event sequencing and processing. Developing efficient event sequencing algorithms is a research priority to enhance the performance of blockchain systems. This study addresses the efficiency problem in blockchain event sequencing by introducing a high-dimensional multi-objective differential evolution strategy to improve blockchain technology’s performance in various fields. This paper uses the NSGA-III-WA algorithm to efficiently sort blockchain events by combining differential evolution strategies. Compared to the traditional sorting algorithm, this algorithm reduces latency by 30% and improves memory usage by about 20% when dealing with events of the same size, ensuring sorting accuracy. By optimizing the weight vector adjustment strategy, the convergence speed and distribution uniformity of the algorithm and the solution can be optimized. In this paper, the algorithm can effectively improve the efficiency and performance of blockchain event processing, which is critical in optimizing blockchain systems.

Substation network security is the key to maintaining the stable operation of power systems. In the face of growing threats of network attacks, traditional security protection measures have been brutal to meet the needs of modern power systems. Research on substation network security, situational awareness strategies, and remote operation and maintenance of equipment is essential to improve network defense capability and ensure the continuity and reliability of power supply. This study explores effective security situational awareness methods and remote operation and maintenance techniques to provide new solutions for substation network security. This paper builds an efficient network attack detection model by introducing linear discriminant analysis (LDA) and radial basis function (RBF) neural networks. The experiment uses the KDD Cup99 dataset, which is preprocessed to provide the model training and testing data. The LDA-RBF model in this paper outperforms the traditional RNF neural and BP neural networks regarding recognition rate. Specifically, the recognition rate reaches 90.2% for the Smurf attack and 100% for the Ipsweep attack. The proposed model of the study also performs well in terms of leakage and false alarm rates, with an overall recognition rate of 97.00%. This study proposes a network security situational awareness strategy and equipment remote operation and maintenance method that can effectively enhance substation networks’ security and operation and maintenance efficiency.

Global carbon emissions and climate change are of increasing concern. As a critical indicator of the carbon efficiency of economic activities, carbon productivity has improved, resulting in a relative reduction in carbon emissions and output growth. As an essential part of the national economy, foreign trade profoundly impacts carbon productivity by promoting technology exchange, industrial upgrading, and structural adjustment. The carbon emission impact of foreign trade is not uniform, and there are noticeable differences between countries and regions. This paper examines how foreign trade affects carbon productivity and through which mechanisms, and further analyzes regional and industrial differences in these effects to provide a basis for the formulation of relevant policies. According to the study, there is a significant time lag effect on foreign trade’s impact on carbon productivity, and there are differences between industries and regions. Promoting foreign trade in this paper results in technological progress and improved carbon productivity, with an average improvement of 5.2%. By optimizing and adjusting industrial structure, carbon productivity is promoted better, with an increase of around 4.3%. High carbon emission industries have a relatively weak positive effect. Foreign trade positively impacts carbon productivity by promoting technological progress and industrial restructuring, but it is necessary to have differentiated policies for different industries and regions.