bluuebunny/crossref_metadata_2025_split huggingface dataset:
Application of financial management in regional economic development based on VAR modeling
Authors: Li Xiaoyun 
Published: January 2024

Abstract
This paper constructs a vector autoregressive (VAR) model between the level of financial management and regional GDP. Through the Granger causality test, the panel data at the financial management level and regional economic phenomena are studied, and the empirical distributions in the stationary situation are given by combining the stochastic simulation method. The auxiliary regression equations are established separately for constrained and unconstrained conditions, and the test statistic is constructed to determine whether there is Granger causality between the variables. Finally, from the actual data, a one standard deviation shock is applied to LATS and LGDP, and a response model with a lag of 100 periods is chosen to obtain the impulse response of the level of financial management and regional economic growth. The results show that the impact of the regional economy on the level of financial management is zero in the first period and then increases continuously, reaching a maximum response of 0.0233 in the 49th period, which indicates that there is a bidirectional promotional effect between the level of financial management and the regional economy and that the effect is not very strong but lasts for a long time.
Civil and Commercial Jurisprudence Observations on Intelligent Social Governance
Authors: Geng Yanwen 
Published: January 2024

Abstract
The purpose of civil and commercial jurisprudence observation is to realize the intelligent and innovative development of social governance and to improve the efficiency of related cases. This paper develops a civil and commercial jurisprudence case information analysis system that utilizes MVC architecture and intelligent technology. The BERT pre-training model and self-training model are combined for the construction of a civil and commercial jurisprudence legal information extraction model, which helps judicial personnel understand the scope of civil and commercial jurisprudence cases in the process of social governance. Then, the ILJP is used as the basis to combine the fact encoder, the element predictor and the legal cause predictor to carry out the construction of the interpretable legal cause intelligent research and judgment model, which provides an intelligent research and judgment program for the civil and commercial jurisprudence social governance cases. The effectiveness of the civil and commercial law case analysis system is an important guarantee to enhance intelligent social governance, so this paper carries out a test and analysis of its intelligent algorithm and system performance. The results show that the legal information extraction model tends to stabilize after the first 15 iterations of training, and its validation loss value is around 0.173, and the training loss value of the model is around 0.008 when the training of the intelligent research and judgment model reaches 200 rounds. When the information analysis system of civil and commercial law cases reaches 1,000 concurrent users, the average response time of each logical operation does not exceed 3s, and the occupancy rate of CPU and memory resources is over 30%. The information age needs to fully combine technology and social governance in order to deeply mine the information of civil and commercial jurisprudence related cases, improve the efficiency of social governance, and innovate the intelligent development of social governance.
Employee mental health risk prediction and coping management based on neural network
Authors: Chang Lijun 
Published: January 2024

Abstract
In this paper, after dissecting the neural network model, the initial weights and thresholds of the BP neural network are optimized through selection, crossover, mutation and other operations by using the global optimization-seeking ability of the genetic algorithm. The model for predicting employee mental health risks is initially constructed by selecting structural design, structural parameters, and genetic operators. The feasibility of the model in mental health risk prediction was explored based on the indicators of training time, model error and prediction accuracy, and the prediction model was utilized to predict the mental health risk of the employees in Company A and the coping plan for the employees’ mental health risk was established. The results show that the accuracy of the neural network model is 90% and 85%, respectively, during the training and testing processes. The sensitivity and specificity of the training set are 90.00% and 75.06%, respectively, the Yoden index is 0.78, and the Kappa coefficient is 0.69, and the sensitivity and specificity of the test set are 92.00% and 78.05%, which is a good performance, based on which the study is able to predict the risk of mental health of the employees and to guarantee the mental health of the employees in real-time.
Female Characterization and Cultural Characterization of Water Margin Based on Cognitive Mapping Constructs
Authors: LYU Ling 
Published: January 2024

Abstract
The Water Margin portrays many typical female images, and different female character images make the characters more fleshed out so that the readers will never forget them. In this paper, we construct cognitive mapping based on the cognitive mapping of female characters in Water Margin. In order to more intuitively display female characters and their embedded cultural characteristics, we choose a multilayer perceptual machine to learn the representation of emotion score vectors and combine the temporal and semantic relationships in the text with long and short-term memory networks to construct an emotion dictionary of female characters. GAN is utilized in female characterization to provide a foundation for thoroughly analyzing the cultural characteristics of female character roles. The method given in this paper was validated and analyzed in terms of female characterization and cultural characteristics. The results show that on the EmotionROI dataset, the classification accuracy of the emotion lexicon is 9.34% higher than that of the GOSR algorithm, and the classification accuracy of various emotion categories reaches more than 70%. The image generation quality of the GAN method is 63.96% on the BLUE-4 dataset, and the final CIDER index score on the MSVD dataset tends to be 1.15%. The image of female characters in Water Margin mainly conveys a variety of different images such as heroic, ugly and complex, which represents the real state of women at the bottom of society in the feudal period of the late Yuan and early Ming Dynasties, and provides a certain reference for understanding the cultural traits under the feudal society.
The Path of Digital Construction of Civics and Politics in Professional Course Curriculum of Higher Vocational Colleges and Universities Based on the Concept of OBE
Authors: Liu Yanwen , liu Shuiqing , Zhang Junxian , Wang Gang , Wang Shurun 
Published: January 2024

Abstract
This paper explores the principle of deep reinforcement learning algorithm application and constructs the digital teaching model of Civics through the recurrent neural network, Markov decision process, Actor-Critic algorithm and collaborative filtering recommendation algorithm. On this basis, the state representation model and decision-making model are invoked to improve the diversity optimization recommendation of the deep reinforcement learning algorithm. Aiming at the problems existing in the practical application of the OBE concept, the model constructed in this paper is utilized to propose a multi-platform integration of the Civics digital learning model. The objective of empirical and simulation experiments is to confirm the model’s implementation and recommendation effects, respectively. In the validation of hyperparameter d and N values, the DQN model achieves the optimal recommendation effect when the d values are 65 and 63 on the HetRec and MovieTweetings datasets. During the implementation of the digital teaching evaluation of the course Civics, more than 60% of the students rated the teacher’s feedback session higher. Overall, the 6 dimensions were rated higher, and the number of students who chose to be fully compliant and conforming was more than 200.
Cultivation of e-commerce management talents based on F2C model in the context of scientific and technological development of agriculture
Authors: Yang Yi 
Published: January 2024

Abstract
Based on the LISEREL model and the characteristics of ordered categorical variables, this paper establishes a structural equation model with ordered categorical variables to study the cultivation effect of e-commerce management talents under F2C mode. The measurement model and structural model are constructed using the content and cultivation effect of e-commerce management talent training and e-commerce sales performance, and the degrees of freedom of exogenous observation variables, endogenous observation variables and parameters in the model are estimated. Path analysis was utilized to determine the degree of influence of the F2C talent cultivation model on e-commerce management talent competency and management performance, as well as the effect size. The results show that all the dimensions of e-commerce talent competence under F2C talent cultivation mode are between 3.5 and 4.5, and the relationship between F2C talent cultivation mode on e-commerce talent sales performance is significant at the level of P-value 0.001, and the path coefficients of talent cultivation and sales performance are between 0.1-0.3, and that the F2C cultivation mode is beneficial for the enhancement of e-commerce managerial talent competence.
Agricultural products industry chain construction based on multiple regression analysis on the innovation of rural management mode
Authors: Wu Lili 
Published: January 2024

Abstract
This paper constructs a multiple regression analysis model of the agricultural industry chain with rural environment and economic management and estimates the model parameters using the least squares method. The linear correlation between the variables is analyzed based on the variance expansion coefficient, standardization coefficient, complex correlation coefficient and other indicators, and the regression problem is analyzed for significance. Then the antidifferential Kalman filter optimization method of least squares and the threshold denoising optimization method based on wavelet decomposition and reconstruction transformation are introduced to optimize the model parameters to improve the model performance. Finally, the impact of agricultural industry chain construction on the rural environment and economic management is analyzed based on the model. The correlation coefficients between the three dimensions of agricultural product industry chain management and the performance of rural economic management are 0.318, 0.468, 0.416, and the correlation coefficients between them and the performance of rural environmental management are 0.297, 0.528, and 0.529, respectively, which indicates that rural agricultural product industry chain construction can promote rural management.
Optimization of Diversified Teaching Mode of Vocal Singing in Colleges and Universities by Integrating Audio-visual and Multi-sensory Senses
Authors: Zhang Yanlin 
Published: January 2024

Abstract
To cultivate students’ perception of music culture through audio-visual multi-sensory methods in college vocal singing teaching is a new way to understand music works and cultivate music culture consciousness. The flipped classroom is the basis for this paper, which aims to innovate the teaching of vocal singing in colleges and universities. The linear prediction of Mel’s cepstral coefficient is used to extract the auditory features of the music symbols of the vocal singing video in the flipped classroom so that the students can master the relevant skills and pronunciation of vocal singing. To help students understand vocal singing in its specific context, the time-frequency diagram is utilized to analyze the singer’s movements in the vocal singing video. The self-attention mechanism is used to fuse auditory and visual features, which is validated and analyzed for its effectiveness, teaching effect, and satisfaction. The results show that when the added noise signal-to-noise ratio reaches 50dB, the recognition rate of the LPMFCC algorithm for vocal singing music signals is above 80%. Utilizing the flipped classroom for vocal singing teaching, the average score of students’ vocal singing increased to 9.71, and more than 80% of the students believed that the flipped classroom teaching mode could enhance their independent learning ability. The flipped classroom teaching mode, which integrates audio-visual and multi-sensory teaching methods, can enrich the teaching methods of vocal singing in colleges and universities and further enhance students’ interest in vocal singing.
A neural network-based prediction model for cultivating skilled personnel in higher vocational education
Authors: Zhang Li , Wang Zhengqiang 
Published: January 2024

Abstract
In this paper, the neurons in the BP neural network are used to represent the skill-based talent cultivation feature vectors, and the feature vectors are trained on the network to obtain the vector transformation function. On the basis of the vector transformation function, after constructing the technical talent cultivation prediction model by using the backpropagation algorithm, the data indicators are determined according to the requirements of skill-based talent cultivation, and the initial data are normalized by overfitting for the technical talent cultivation prediction results. The empirical research on the synthesis of technically skilled talents in higher vocational education is designed by means of questionnaires, and the data analysis software is used to analyze the examples of skilled talent cultivation in vocational education under the background of big data technology. The results show that from 2015 to 2020, the predicted values of the number of technically skilled talents demanded in a province are 92,130, 105,396, 160,946, 225,045, 232,313 and 216,150 respectively, and the relative error values are less than 0.05 compared with the actual demand values of technically skilled talents in the same period, indicating that based on the BP neural network-based technical talent cultivation prediction model outputs a good fit between the extrapolation test prediction value and the real value. This study guides the cultivation of skilled talents in higher vocational education.
The application of printmaking art elements in visual communication design
Authors: Hu Weiguo , Zhou Xueyuan 
Published: January 2024

Abstract
Visual communication design and printmaking art are two independent art disciplines, but they have many similarities in graphic design, color matching and other aspects. This paper demonstrates the extraction of printmaking features using the improved LBP algorithm. The method of color histogram and color space is used to complete the color extraction of the image, and the texture features of the image are described by combining signal processing and statistical analysis. The LBP algorithm is used to locate the center pixel of the image to form a binary bit string, and the pattern value is obtained by multiplying each binary bit by the corresponding weight and summing up. The efficiency of image texture acquisition is enhanced by adding neighborhood gradient multiscale to the LBP algorithm. To obtain printmaking art elements and propose a direction for integration with visual communication design, image feature extraction is applied to printmaking art element extraction. The performance of texture classification for images has been significantly improved by the improved LBP algorithm, as shown in the results. On the Outextc10 texture dataset, DLBP5 achieves the highest classification accuracy of 92.19% by extracting colors, textures and shapes in printmaking and applying the features with elements of printmaking to visual communication design. Under the direction of integrating printmaking art style elements with visual communication design, users selected {unique, packaging design}, {vivid, branding design}, and {sharp, advertisement design} with higher satisfaction gradients, with ratings of 4.62, 4.17, and 4.36, respectively, which are all greater than 4.
A study of the effects of different sports programs on psychological stress and mental toughness of college students in the Internet era
Authors: Qi Junqing 
Published: January 2024

Abstract
There are differences in the effects of different groups of sports on mental health factors, and this paper analyzes the effects of different sports on psychological stress and mental toughness based on logistic regression and clustering. By exploring the association between sports and psychological quality, the mediating effect model of sports benefits on mental health was constructed. Logistic regression was used to analyze the test results of different health factors among college students, and the dimensions of psychological stress and mental toughness were divided by combining the methods of cluster analysis. The results showed that after soccer, the student’s life stress decreased from 31.8 to 28.6, and after badminton, the students’ developmental stress decreased from 23.4 to 21.6. The students’ developmental stress before basketball was 23.8, and the students’ developmental stress after basketball was 20, which was a decrease of 3.8.The test of students’ mental toughness presented the soccer>track and field>basketball>Unsports results. The students’ resilience increased from 3.01±0.45 to 4.12±0.74 after the soccer intervention.
Research on the Dynamic Synergy Mechanism of Industry-Education Integration and Science-Education Integration in the Construction of a Strong Educational Country
Authors: Chen Rongjuan 
Published: January 2024

Abstract
The purpose of this paper is to combine the integration of industry and education with the fusion of science and education and to promote the acceleration of the construction of a strong educational country under the perspective of collaborative governance. On the basis of exploring the traditional genetic algorithm, combined with the synergistic relationship between the integration of industry and education and the integration of science and education, the cooperative co-evolutionary genetic algorithm (CCGA) is selected to analyze the synergistic optimization of the two. Combined with the CCGA algorithm process, the synergistic efficiency and cooperative stability of the two are explored, and the coordination degree of the two is measured using the method of example analysis. Among them, the island model genetic algorithm and CCGA algorithm are selected for function testing to verify the superiority of this paper’s algorithm. The data shows that the synergy degree of elevator installation, repair, and maintenance majors in School Q is 0.48, ranking first. 0.44 For construction, 0.27 for electromechanical. 0.06 for agriculture, and the integration degree of other majors is lower than the average of 9 majors. The degree of synergy between industry, education and science in this university needs to be improved, and the connection between the education chain and the industrial chain needs to be strengthened.
Deep learning-based high performance liquid chromatography for food analysis
Authors: Lin Yuan , Yan Wang 
Published: January 2024

Abstract
This paper presents a study on the determination of synthetic pigments using high performance liquid chromatography (HPLC) method combined. A retention value qualitative approach, combined with an uncertainty assessment algorithm for the determination of pigment content, was used for the simultaneous determination of nine synthetic pigments, namely, lemon yellow, amaranthine red, indigo, carmine, sunset yellow, brilliant blue, seductive red, erythrosine, and seductive red, in foodstuffs by reversed-phase high-performance liquid chromatography (RP-HPLC). The sample pretreatment method was optimized, and the chromatographic conditions were set to investigate the UV determination wavelength, mobile phase, column temperature, and wavelength of synthetic pigments. Under the same mobile phase and column conditions, the results indicated that the components’ retention times did not significantly fluctuate with the change in column temperature. The results showed that the chromatographic response signals of lemon yellow, sunset yellow and seductive red were higher at the UV determination wavelength of 254 nm, so 254 nm was finally determined as the UV detection wavelength in this experiment. Mobile phase A: methanol, B: ammonium acetate (0.02mo/L) using gradient elution, the separation degree R>1.5, and the symmetry and stability of the chromatogram were better. The separation of the components was good, and the peak shape was sharp and symmetric when the column temperature was 35 ℃, so the column temperature was chosen to be 35 ℃, and the establishment of the chromatographic conditions was thus completed.
Specific implementation strategies for rural revitalization strategies to help agricultural and rural economic development
Authors: Liu Guanqin 
Published: January 2024

Abstract
This paper constructs an evaluation index system for the development level of rural revitalization strategy and gives an evaluation index system for the development level of agricultural and rural economy. The index weights are solved by using layer-by-layer vertical and horizontal slotting methods combined with the “entropy value” nonlinear programming method, and the TOWA-GA hybrid operator is used to downgrade the evaluation value of rural revitalization level and agricultural and rural economic development level of each region and each year in the dimension of time, so as to reflect the equilibrium of the development process and the authenticity of the evaluation results. An empirical model of the influence factors of rural revitalization strategy on agricultural and rural economic development was constructed on the basis of the PVAR model, and the specific influence factors of rural revitalization strategy contributing to the development of agricultural and rural economy were verified through actual data. The results show that the index of rural revitalization development level and the increment of agricultural and rural economic development level between the western region and the eastern region in 2019-2019 reached 144.94% and 40%, respectively, and one unit of change in rural revitalization development level will cause 0.518 units of change in agricultural and rural economic development level. The implementation of the rural revitalization strategy can promote the rural areas to increase the opening up to the outside world, realize the coordinated development of urban and rural areas, increase the income of farmers’ industries, and thus enhance the level of agricultural and rural economic development.