bluuebunny/crossref_metadata_2025_split huggingface dataset:
Healing Potential of Chitosan PVA Hydrogels on Excised Wound in Diabetic Albino Mice
Authors: Akram K. , Imran S. , Raza A. , Akram K. , Mukhtar A. , Arif A. 
Published: October 2024

Abstract

Objective
This study aimed to evaluate the efficiency of the developed chitosan/polyvinyl alcohol (CS/PVA) hydrogel crosslinked with 3-aminopropyltriethoxysilane (APTES) for its wound healing potential on diabetic wounds in mice models.

Methods
A total of 18 Swiss albino mice were randomly assigned info a control and five treatment groups (CPO, CP50, CP100, CP200, and CP300) based on APTES crosslinker concentrations. After a 13–14 hour fast, an injection of alloxan monohydrate was used to induce type I diabetes. Mice were anesthetized, followed by the creation of a 6 mm dorsal wound using a biopsy punch. Throughout trial, wound size was measured and photographed, and blood glucose levels were monitored.

Results
On day 15, treated groups showed complete wound healing, while the control group was in transitional stage of healing. After therapy, mice were euthanized and blood, skin, graft, kidney, and liver samples were taken for biochemical and histological investigation. Skin graft histology showed complete epithelialization and granulation in all treatment groups compared to controls. CP300 had most skin regeneration. Inflamma-tion and necrosis were observed in the control group. Liver and kidney histological sections showed structural changes, but hydrogel induced minimal toxicity to the organs. The reported effects may have been caused by diabetes rather than hydrogels. Biochemical analysis of liver enzymes exhibited a significant (p < 0.05) increase in bilirubin, alkaline phosphate (ALP), alanine transaminase (ALT) and aspartate aminotransferase (AST) levels, suggesting liver dysfunction. Kidney function tests showed no significant difference in urea and Creatinine concentrations.

Conclusion
The CP300 hydrogel demonstrated an excellent healing response and is recommended as a suitable material for wound dressing.
Research on Modern Art Design Innovation Based on Computer Vision Technology
Authors: Zheng Dongdong 
Published: October 2024

Abstract
Computer vision, as a technical means of “seeing” the world, is applied to modern art design, which can expand the audience’s perception of external reality and re-understand the process of art design. This paper examines the process evolution and creation method of generative art design by analyzing the characteristics of computer vision technology and visual communication design. Based on a capsule network and a generative adversarial network, the C-CapsGAN model for art design image generation has been established. Optimization functions for consistency, style loss, and smoothness loss have been designed. Quantitative analysis and survey research were used to analyze the effectiveness of the C-CapsGAN model in art design image generation. It was found that after the model convergence, the FID value was reduced by 20.36%, and the IS value was improved by 0.482 compared to CCME-GAN on the modern art design image dataset. The mean SSIM value of the six art design images was 0.611, and the subject’s favorite score for the model-generated art design images could be up to 3.715 points. By integrating computer vision technology with modern art design, the diversification of art images can be promoted, and the visual stimulation of art design can be enhanced for the audience.
A Study of English Rhetorical Strategies Based on Neurosemantics
Authors: Ma Li , Cui Xiang 
Published: October 2024

Abstract
In recent years, with the performance improvement of deep neural network models, neural semantic parsing has entered a new stage and has been widely used in many fields such as classification tasks, speech recognition, linguistic annotation and syntactic analysis. In this paper, we design a strategy for recognizing and parsing English rhetorical devices using the neural semantic parsing method. In this paper, we first use the Skip-gram model to train word vectors, and then based on the convolutional neural network model to recognize the platitudes, metaphors, and similes in English text, and apply BiLSTM-Att model to acknowledge the English quoted rhetorics. The prediction accuracies of the CNN recognition model on platitudes, metaphors, and similes are 91.7%, 92.5%, and 90.2%, respectively, greater than 90%, indicating that the model can successfully recognize the platitudes, metaphors, and similes. The model can recognize platitudes, metaphors, and anthropomorphic rhetorical devices. Compared with the CNN+BiLSTM model, the precision, recall, and F1 value of the BiLSTM-Att model are improved by 0.22%, 11.44%, and 7.09%, respectively. Its recognition accuracy of English quotations under different similarity thresholds is very high, with 94% when the similarity reaches 50% and even 98% when the similarity reaches 90%. This suggests that the present paper BiLSTM-Att English quote rhetorical recognition model is adequate. This paper’s neural semantic-based English rhetoric strategy is paving the way for the development of natural language processing technology.
Research on the Mechanism of Dynamic Monitoring of Undergraduate Students’ Learning Situation and Adaptive Adjustment of Teaching Mode--Based on the Perspective of Educational Evaluation Reform
Authors: Zhang Hua , Xiong Feng 
Published: October 2024

Abstract
Dynamic monitoring of undergraduate learning is a tool for the accurate pulse of education and teaching, and an in-depth study of the quality monitoring data of students’ learning can discover the hidden problems and shortboards in education and teaching. The article utilizes information technology to build a dynamic monitoring platform for undergraduates. Then, it establishes an accurate teaching model for undergraduates with the assistance of this platform. The SHAP interpretable model is used to obtain the online learning behavior characteristics of undergraduates, and the LSTM autocoder is used to construct the time-varying feature sequence of undergraduates’ learning behavior, which is inputted into the LSTM model to establish the undergraduate learning situation early warning model. Taking the data of students’ online behavioral characteristics as an example, the validation of the importance of undergraduate learning behavioral characteristics and early warning is carried out, and the effect of the precise teaching model is also analyzed. The SHAP value of undergraduate students taking online tests is 0.969, which significantly impacts their online learning behavior. The accuracy of undergraduate students’ learning alert was 0.822, which was about 3.53% higher than the FWTS-CNN model with sub-optimal performance, and the results of the learning adaptability retest were 3.24 points higher than the initial test results. From the perspective of educational evaluation reform, combining undergraduate students’ learning dynamic monitoring data can enable adaptive adjustment of teaching content and mode.
Study on the Development Path of Agricultural and Rural Modernization in the Context of Rural Revitalization Strategy
Authors: An Qiaozhi 
Published: October 2024

Abstract
Achieving agricultural and rural modernization is the fundamental goal of the rural revitalization strategy. Scientific assessment of the development level and obstacles of agricultural and rural modernization make up for the short boards of development and is of great theoretical and practical significance for exploring the realistic path of innovation and development of China’s agricultural and rural modernization in the new era. This paper elaborates on the five construction principles of the evaluation index system for the development level of agricultural and rural modernization. It proposes the measurement methods of entropy weight method and multiple weighted comprehensive evaluation methods for the development level of agricultural and rural modernization, as well as the obstacle degree model for assessing the obstacle factors to the development of agricultural and rural modernization. Henan Province’s agricultural and rural modernization development status from 2014 to 2023 is examined as an example. The overall development of agricultural and rural modernization in the sample within the study area shows an upward trend, but the enhancement effect is not evident in terms of economic development, social development, and grassroots governance. The main obstacle factors affecting the development of agricultural and rural modernization in Henan include the agricultural output growth rate, the contribution rate of agricultural scientific and technological progress, and the education level of the agricultural labor force. The obstacle degree of agricultural output growth rate is 0.1745, 0.3327, and 0.4294 in 2014, 2018, and 2023, respectively. At present, it should be based on the task of promoting high-quality development in China’s new stage of development and closely grasp the main aspects of the development of modernization of agriculture and rural areas in accordance with the requirements of the political direction, industrial integration, the main driving force, the ideological leadership, and the digital and intellectual empowerment. Moreover, solidly promotes the development process of modernization of agriculture and rural areas.
Research on Intelligent Improvement Strategies of Administrative Management in Colleges and Universities Supported by Big Data Technology Support
Authors: Bian Xu , Bian Chen 
Published: October 2024

Abstract
Big data technology continues to catalyze the informatization and intelligence of education and teaching in colleges and universities while accelerating the difficulty of information management. This paper aims to discuss the development and utilization of information resources, as well as security and protection issues in college administration, through the integration of network technology and the college administrative management system. To address the development limitations of administrative management in colleges and universities, this paper proposes key technologies for the construction of intelligent administrative management in these institutions and analyzes the interrelationships between these technologies. The objective of experimental platforms 1 and 2 is to evaluate the ability of BIM models to render buildings of different sizes in real time. Compare the security performance of the fully homomorphic encryption algorithm proposed in this paper and combine the classical encryption algorithms (DES algorithm, AES algorithm, RSA algorithm, ECC algorithm). Examine the students’ perceived attitudes toward intelligence improvements and the overall effectiveness ratings of the school administration staff. The compressed, custom-rendered files used in this paper’s cloud service significantly improve the user experience by reducing the loading time by approximately half. The overall student perception ratings were no less than 4.13, and the effectiveness ratings of faculty and staff were all in the range of 3.5-5.0, indicating that school administration is effective. The intelligent improvement direction and improvement scheme proposed in this paper is feasible and merits further promotion.
Exploring the Change of Literary Narrative and Reader Interaction Mode in the New Media Environment
Authors: Fang Xiaofeng 
Published: October 2024

Abstract
Literature in the new media environment breaks the boundaries of the industry and reflects the Internet thinking of openness, sharing, and interaction. Starting from the study of interactive narrative phenomena in digital media art, this paper systematically explores the narrative style and characteristics of digital media art. X literary reading platform is selected as a representative, and through correlation analysis and regression analysis, the relationship between the reader interaction of the platform users, the readers’ perceived platform availability, and the readers’ perceived social interaction is explored. The study found that 0.2215 of the reader interactions in the reader interaction patterns of Platform X were social interactions, which are a type of social interaction mediated by the network, and that reader interaction had a significant positive effect on readers’ perceived platform availability and social interactions. The contribution of the study lies in the measurement of readers’ perceived social interaction through the definition of social interaction, while the mediating mechanism of platform availability reveals how readers perceive social interaction in their interactions with online literature. To enhance user services and narrative art changes in the online publishing of literary works, it is crucial to enhance the social interactions that readers of online literature perceive during the reading process.
Big data analysis methods and cultural value mining for the historical research of ceramic art
Authors: Fu Linfei 
Published: October 2024

Abstract
Chinese ceramic art occupies an important position in the world of ceramic art and is an important component of Chinese traditional culture. This study uses crawler technology to collect relevant text data of ceramic art history, then vectorize the text, extract and analyze the keywords of ceramic art history based on TF-IDF and word co-occurrence model, and then combine with the text sentiment analysis model based on Seq2seq model to realize the value mining of ceramic art history and culture. Ceramic art in history is mostly characterized by artistic diversification, design diversification, appearance design, and situational integration with rich colors. China (818 frequency), development (781 frequency), and culture (752 frequency) are the most frequently used keywords. The history of ceramic art is closely united with the traditional Chinese culture in its development, and at the same time, the culture of ceramic craft also has a high technical content, reflecting the aesthetic value and technical value of the history and culture of ceramic art.
Research on the Optimization Model of Semantic Coherence and Fluency in Language Translation
Authors: He Yuanxiu 
Published: October 2024

Abstract
Traditional Transformer machine translation cannot effectively deal with translation errors due to the lack of an explicit evaluation mechanism for the correctness of the target language text, which not only hinders the improvement of the translation quality of the target language but also makes the decoding process highly complex. This paper constructs a model for language translation based on decoding optimization. The problem of choosing the number of decoding rounds is transformed into a Markov decision-making process, and a reinforcement learning algorithm is used, which is based on the translation quality of the target-language translation and the number of decoding rounds obtained from the translation. The appropriate number of decoding rounds is selected according to the different complexity of the source language text to be translated, so that the translation model can achieve a balance between the translation quality of the target language translation and its corresponding time consumption. The optimization of the traditional Transformer machine translation algorithm has finally been achieved. The optimization effect is examined on the dataset. It is found that when the dimension is 1024, the number of parameters of the optimized model decreases by 16.03%, the average reasoning time is under 55 seconds, and the decoding time is always lower than that of the Transformer baseline model. The convergence trend of its Loss is similar to that of the Transformer model but with a faster and better convergence speed. On the six Chinese-English bilingual datasets, the average BLEU score of this paper’s model is 64.586. On the five Chinese-German bilingual datasets, compared with Transformer’s average BLEU value of 44.078, the score of this paper’s model is still the first one, which is 18.29% higher than that of the traditional Transformer model’s BLEU value, and it has a good language translation performance. The language translation model based on decoding optimization in this paper provides a useful exploration for machine translation optimization in terms of improving translation quality, enhancing Loss convergence speed, reducing the number of parameters, and improving decoding speed.
A Critical Study of the Structural Change of the Capitalist Socio-Economic Structure by Combining Marxism and Modern Information Technology
Authors: Huang Haimin 
Published: October 2024

Abstract
Modern information technology networks have changed people’s production and lifestyle, leading to new changes in the economic structure of capitalist society and bringing new challenges to the use of Marxism to criticize capitalism. Based on the knowledge of Marxist economics, this paper provides a critical overview of the changes in the economic structure of capitalism from two aspects: the changes in the forms of capital exploitation and the expansion of capital exploitation relations. Using the complex network theory in modern information technology, a capitalist socio-economic model is constructed to perform a critical quantitative analysis of the structural changes in the capitalist socio-economic structure. A case study of capitalist socio-economic structure is conducted in conjunction with the previous model. The results show that the entropy of capitalist wealth E is decreasing in the case that the parameters of N = 1000, m = 6, and M = 40 are determined, and the traditional labor distribution system and production mode will be eliminated by history in the end. Through a critique of capitalist economic mechanisms, it deepens people’s knowledge of capitalist economic structure.
Construction of an Intelligent Management Model for Ideological and Political Education in Colleges and Universities under the Internet of Things Environment
Authors: Mi Mi 
Published: October 2024

Abstract
The new generation of information technology represented by the Internet of Things, big data, and cloud computing has a great impact on human society, and the integration of the new generation of information technology into ideological and political education is of great significance. This paper focuses on the application of Internet of Things technology in the management of ideological and political education in colleges and universities and builds an intelligent management model of ideological and political education in colleges and universities relying on the campus network. The model mainly includes school registration management, student attendance management, student computer management, and educational resource management. Based on the deficiencies of the existing educational resource management, we refer to the label information, locate the target information, protect and share the extracted resource data through private cloud technology, and complete the design of the sharing system of the Civic and Political Education resources. This paper’s Civic and Political Education Resource Sharing System has a smoother operational effect and a lower operational interference rate than the current system, as demonstrated by the experimental results. Taking A university as the experimental object, the proportion of students whose ideological and political education evaluation results are excellent after adopting intelligent management is 65.42% of the total number of students, which indicates that the intelligent management model can effectively improve the effect of students’ ideological and political education.
Research on teaching innovation of new energy vehicle testing and maintenance technology professional course by integrating online and offline teaching mode
Authors: Cai Yu 
Published: October 2024

Abstract
Integrating online and offline teaching is a new direction for the new energy vehicle testing and maintenance technology professional course, which is conducive to improving the limitations of teaching venues and facility conditions. In this paper, the two paths of optimizing the collision algorithm and designing the virtual simulation teaching software achieve online-offline integration teaching. In order to optimize the authenticity of the operation of automotive parts in virtual simulation teaching, a distributed enveloping box collision detection algorithm is proposed, and the parts that need to be accurately gridded for collision are screened by the OBB algorithm, so as to improve the performance of collision detection. Design virtual simulation teaching software using text, video, sound, and other multimodal information for online and offline integration. The experiment shows that the optimized collision detection algorithm has good performance, and the experimental class score is 6.33 points higher than the control class, indicating that the fusion of online and offline teaching modes has an obvious effect.
Engineering Mechanics Methods in Stability Studies of Bridge Structures and Innovations in Future Bridge Designs
Authors: Fu Cuiying 
Published: October 2024

Abstract
With the development of science and technology and transportation, high pier and large-span bridges are rapidly rising. Due to the increase in span diameter and pier height, nonlinear and stability problems of bridges become more and more important. In this paper, the stability of large-span steel box-girder suspension bridges is investigated using engineering mechanics methods. Based on the finite element analysis method to solve the bridge structure of the first type of stability problems and the second type of stability problems, the use of the response spectrum method for bridge seismic response. Taking “Xiling Yangtze River Bridge” as the engineering background, the seismic response is analyzed by establishing a finite element model. The axial force of the bridge tower generated by the downstream earthquake is larger than that generated by the transverse earthquake. In the transverse direction, the bending moment MZ is larger than the bending moment MY in the transverse direction, and the bending moment of the pile foundation is larger than the bending moment of the pile foundation in the longitudinal direction. The Xiling Yangtze River Bridge plays a dominant role in transverse seismicity, and its downstream seismic excitation plays a dominant role in longitudinal seismicity. However, the energy-demand ratio corresponding to the transverse moment MY is only 1.83, and the strength of the pile section needs to be further improved. For the future innovation of bridge design, a high-performance bridge structure based on UHPC is an important direction for future development.