bluuebunny/crossref_metadata_2025_split huggingface dataset:
Examination of the Effectiveness of Fruit Thinning in the Case of Idaho and Gala Must Early Apple Varieties
Authors: Gyalai Ingrid , Tóth Balázs , Nasirov Muhtor , Kholmirzaev Bakhrom , Bahriev Dostonjon , Makra László , Lantos Ferenc 
Published: October 2024

Abstract
Apple (Malus domestica Borkh.) is the most important fruit in the EU. The total yield is more than 11 million tons.year-1, 15% of which is that of the early apple varieties. Several papers have already been published on the efficacy of crown and fruit thinning in the 20th century. Nowadays, hybrid varieties and intensive crown types are used in modernized systems. Our research was carried out in a Hungarian orchard during two cultivation periods. We studied two early apple varieties (Idaho, Gala Must) to determine how fruit thinning affected the quantity and quality of fruits. We found that the effectiveness of non-thinned technology is similar or slightly better compared to fruit thinning, after the second harvest. The average yield of Idaho apples per tree per harvest was 35.9 vs. 24.8 kg, while that of Gala Must was 50.8 vs. 59.2 kg (with thinning vs. without thinning). To assess quality, we measured water-soluble sugars, NO3
-, NO2 and vitamin C content. Immediately, after the harvest, a surprisingly high vitamin C content was found in the fruits (4.4 mg.100 g-1 on average), which, however, decomposed after 3 months of storage. We also determined the pathway of the decomposition of vitamin C.
Antimicrobial Activity of Styrax tonkinensis Essential Oil in vitro and in situ
Authors: Verešová Andrea , Čmiková Natália , Vukic Milena , Ban Zhaojun , Elizondo-Luevano Joel H. , Kačániová Miroslava 
Published: October 2024

Abstract
Among the genera in this family, Styrax is unique in that it yields benzoin resin, a resinous substance. Usually, when sharp items lacerate the bark, this resin is secreted. Because of its fragrant qualities, it has been used for centuries in cosmetics and fragrances all over the world. Additionally, Styrax species have long been employed in herbal remedies for a variety of ailments. The antibacterial characteristics of Styrax tonkinensis essential oil (STEO) were the focus of this study. The antimicrobial activity was compared to bacteria, both Gram-positive (G+) and Gram-negative (G-), using inhibition zones in agar media, minimum inhibitory concentration (MIC) bioassays and in vapour phase on fruits and vegetables model. The findings showed that STEO was very successful in inhibiting bacteria that were G+ (Bacillus sutbtilis subsp. Spizizenii CCM 1999, Bacillus thuringiensis CCM 19, and Priestia (Bacillus) megaterium CCM 2007) as well as G- (Citrobacter koseri CCM 2535, Enterobacter aerogenes CCM 2531, Escherichia coli CCM 3954). The range of maximal inhibition zones and MIC values was determined to be 4.67 to 8.33 mm and 3.49 to 7.71 mg.mL-1, respectively. Furthermore, B. thiriangensis, P. megaterium, and E. coli were all susceptible to the antimicrobial effects of the (STEO) on the fruit and vegetable model. According to research findings, STEO is a valuable source of organic chemicals that have the potential to be innovative antibacterial agents against microbes.
A Study on the Impact of Economic Policies on Consumers’ Behavioral Intentions on Cross-border E-commerce Platforms
Authors: Jiang Meixia , Yu Jing , Zhao Jing 
Published: October 2024

Abstract
Given the expanding high-level opening to the outside world, there is a potential correlation between consumers’ behavioral patterns on cross-border e-commerce platforms and economic policies. This paper proposes a model for extracting consumer behavioral willingness features based on a convolutional neural network with sentence vector improvements, which optimizes the effect of cluster analysis on consumer behavioral willingness. The extraction model is utilized to extract consumer behavioral willingness features, and the outcomes demonstrate that the proportion of consumption and recommendation willingness is 47.65% and 52.05%, respectively, with a positive clustering effect. The regression results show that consumers’ behavioral willingness to cross-border e-commerce platforms increases with their preference for free trade and mixed trade policies, with an impact coefficient of 0.095 and 0.096. The degree of free trade simultaneously influences consumers’ willingness to recommend, with an impact coefficient of 0.154. However, the import substitution policy has an impact coefficient of −0.078, indicating that consumers are less likely to recommend cross-border e-commerce platforms to others.
Optimization of Higher Education Teaching Method System Based on Edge Intelligence
Authors: Wang Sheng , Zhang Shanjun 
Published: October 2024

Abstract
Nowadays, educational information technology is widely used in higher education teaching, but various teaching resources are not reasonably utilized and effectively managed. In order to solve such problems, this paper introduces edge computing in the basic cloud computing environment to innovate and optimize the multimedia teaching mode of higher education, proposes a VR edge cloud classroom teaching mode, and proposes a collaborative transmission and resource allocation strategy based on DIBR vision synthesis technology to optimize the teaching experience. The VR Edge Cloud Classroom teaching model is designed from three aspects: teaching methods, teaching content, and teaching evaluation. Through practical teaching, students believe that the advantages of this teaching mode are mainly rich in learning resources, conducive to learning-related knowledge and that they will achieve gains in expanding their knowledge, improving their independent learning ability and cultivating their analytical and problem-solving ability. Comparing and analyzing the teaching effect of VR edge cloud classrooms with the traditional teaching effect, there is a significant difference between the two in terms of the achievement of the total objectives (P=0.015<0.05). The teaching effect of a VR edge cloud classroom is significantly better than that of a traditional classroom.
Simulation study of military command and control system based on system dynamics
Authors: Ha Da 
Published: October 2024

Abstract
The command and control system, as the “central nervous system” of the military combat forces, directly affects the combat effectiveness of the troops and plays a vital role in the success or failure of the combat. Based on the characteristics and requirements of military command, this paper constructs a simulation control system for military command based on a system dynamics model. It discusses the setting of relevant essential parameters. Simulation system analysis results show that the red side uses the simulation system for command business processing times to obtain an advantage in military combat. The military combat victory was achieved by losing about one-third of the combat force (333C) on the 29th day. In addition, the rate of military coordination in the simulation system is positively proportional to the number of correctly arranged combatants, and the rate of military intelligence collection has a more significant impact on the completeness of the development of military command programs in the initial period. The simulation system proposed in this paper can meet the needs of military command and control systems.
Research on the Model of Shooting Probability in Basketball Sports Competition
Authors: Chen Guining 
Published: October 2024

Abstract
This paper combines the regression model based on nonlinear least partial squares and the decision tree model to more comprehensively excavate the influencing factors of the shooting percentage of basketball games from the perspective of both basic data and higher-order data. It also calculates the weight coefficients and comprehensive scores of the indicators of the four teams’ shooting techniques in the restricted area through the fuzzy comprehensive evaluation method and studies the hitting rate of different shooting methods. After analysis, the regression coefficients of core strength training and core strength training time are 1.325 and 1.086 in the basic data and high-order data, respectively, which have a significant positive influence on the winning and losing of the tournament, and the decision tree intuitively demonstrates that the core strength training is a key factor in the hitting rate of the game shooting. The weight coefficient of “rebound” is the highest, with a weight coefficient of 20.0271, which has the greatest influence on the shooting percentage, and “traveling backhand shot” has the least influence on the shooting percentage.
Research on the Quality Improvement of Automatic Tone Adjustment Technology for Movie Images Using Computer Vision Algorithms
Authors: Cui Bingshuoshi 
Published: October 2024

Abstract
Color plays an indispensable role in the formation of movie style, and hue, as an important part of color, plays a pivotal role in the study of the quality of movie pictures. The study is based on the basic theory of the color and color space of the movie picture, equalizing the histogram of the movie picture, and then combining the HistoGAN network and Laplace algorithm of computer vision algorithms to realize the enhancement of the hue of the movie picture, and then adjusting and improving the quality of the movie picture automatically. Taking 10 comedy movies by Wes Anderson as an example, the movie tones are measured and counted. According to the results, the movie screen tones adjusted have a strong ability to convey image details and have better contrast and clarity enhancement effects while maintaining image fidelity. As the year progresses, the brightness of the adjacent period in Wes Anderson’s comedy movies becomes more frequent and larger after the movie screen hue is adjusted. The overall of his movies is the color matching law of warm tones with larger saturation with cooler tones with smaller saturation, and the hue adjustment gives the movie screen a more advanced sense of beauty.
Using Big Data Analysis to Study Pedagogical Strategies for Conjunctive Bisyllabic Verb Errors in Chinese Second Language Learners
Authors: Song Jingjing , Zhang Xinying 
Published: October 2024

Abstract
Conjugate diphthongs are a class of words with specific metrical morphology and stylistic features in the written formal corpus of modern Chinese, which need to be combined with a disyllabic constituent in the bare-bones form to form the syllable pattern of “double+double,” which has been under-attended by the teaching community. Within the framework of metrical grammar and stylistic grammar, we statistically analyze the usage bias of conjunctive bisyllabic verbs in the HSK Dynamic Composition Corpus and find that these kinds of words, due to their metrical patterns, stylistic functions, and relatively abstract semantic features, cause a large proportion of metrical syllabic biases that are easy to gather. The bias is caused by both the difficulty of vocabulary acquisition and issues with textbooks and teaching, as well as subjective reasons like learning strategies. In this regard, it is suggested that existing textbooks should be adapted, teachers’ teaching methods should be improved, and learners’ morphological awareness should be enhanced.
Study on the effect of dissemination of Luo and Yue rice culture in multimedia technology-assisted rural cultural revitalization
Authors: Mou Lian 
Published: October 2024

Abstract
Algorithmic recommendation is an important means of using multimedia technology for cultural dissemination and helping rural cultural revitalization. In order to realize the effective dissemination of Luo Yue rice culture, this paper constructs a hybrid recommendation algorithm that recommends videos about Luo Yue rice culture according to user preferences, which uses the cultural content relationship derived from LDA to replace the recommendation list generated by collaborative filtering and crosses it with the historical rating recommendation list to solve the problems of recommendation accuracy and cold start. The analysis of the dissemination effect shows that the average MAE value of this paper’s algorithm is 0.671, the proportion of users who watch relevant videos “occasionally” and more frequently has increased by 5.84%, and users recognize the recommendation method. The algorithm proposed in this paper has a good recommendation performance and helps to disseminate rural culture, as demonstrated by the above results.
Impact of combining party building activities and digital transformation on distribution system performance
Authors: Zhang Hui 
Published: October 2024

Abstract
How to effectively combine modern digital technology and the results of the experience accumulated in the traditional party building work, effectively solve the problems existing in the traditional party building work, so that the party building work carried out transparently and efficiently has become a new issue and challenge. In this paper, the overall framework of an intelligent party building system is designed based on the necessity of digital transformation of building activities and performance requirements. The system is divided into four modules: party building management, service management, statistical analysis, and system management, and the functions of each module have been designed and integrated. Based on the principles of database design, a conceptual structure design is proposed, and the association rules and FP-growth algorithm are utilized to perform association mining on party-building activity data. The results of the association rule mining test show that the fluctuation range of confidence and support is between [0.9148, 0.9587] and [0.9048, 0.9348], respectively, and the system passed the association rule mining test. The majority of people believe that using the party building information platform is beneficial for conducting party-building activities. 80% of the users think that the party building system platform is better and meets their needs for use.
An analysis of the impact of content-generation-based AI design tools on the visual arts
Authors: Pan Bo , Ke Yukai 
Published: October 2024

Abstract
With the development of artificial intelligence, the use of generative adversarial networks in deep learning can generate good visual art based on content, and at the same time, it can reduce the problems of noisy texture, transition migration, and image distortion that exist in content-based image generation. The article proposes a multi-view image generation architecture (DrawGAN) based on generative adversarial networks and builds an AI design tool on this basis to explore the effect and analysis of the design tool for content generation based on generative adversarial networks on visual art. Through experimental testing, the model proposed in this paper, after the constraints of the relevant loss function, the generated image content is compatible with the input image, the style is consistent with the style of the target image, and the image generated by the base DrawGAN has a high degree of reproducibility. In addition, the average score of visual art images generated using the model proposed in this paper is 8.25, which is 2.26 points higher than that of images generated by traditional methods. To sum up, the DrawGAN model proposed in this paper is a valuable tool in the generation of visual art images.
Research on Innovation and Entrepreneurship Talent Cultivation Mode Innovation with Artificial Intelligence Technical Support
Authors: Guo Xiaochun 
Published: October 2024

Abstract
With the rapid development of artificial intelligence technology, colleges and universities pay more and more attention to innovation and entrepreneurship education. The path of artificial intelligence technology is proposed to empower the high-quality development of innovation and entrepreneurship education in colleges and universities from multiple perspectives. An optimization strategy is proposed for an innovation and entrepreneurship education resource-sharing platform based on a collaborative filtering algorithm. The proposal is for a collaborative filtering recommendation algorithm (CFUR) that is based on user feature weight confidence. Finally, experiments have shown that the EP value of the improved algorithm in this paper is significantly higher than that of other recommendation algorithms. Through teaching practice, students’ satisfaction with the educational resource-sharing platform based on the improved algorithm outperforms that of the traditional teaching method, and the mean value of test scores for innovation and entrepreneurship ability surpasses that of the traditional teaching class by 17.07. It shows that the optimized resource-sharing platform has a significant impact on students’ innovation and entrepreneurship abilities, which helps to cultivate innovative and entrepreneurial talents.
Deep reinforcement learning based reactive power regulation and its optimization in power grids
Authors: Zhou Yi , Zhou Liangcai , Sheng Xu , Gu Dongjian , Shen Weijian , Chen Qing 
Published: October 2024

Abstract
The study applies the Markov game to grid reactive power regulation based on deep reinforcement learning theory, constructs the Markov game for grid optimization problems, and optimizes it using the HAPPO algorithm to explore real-time grid optimization strategy based on multi-intelligence body reinforcement learning. On the basis of the optimization strategy, the grid power management method based on deep reinforcement learning is explored through the Markov decision process and the improved deep deterministic policy gradient method, and the grid operation optimization model based on deep reinforcement learning is constructed. The model is then examined in terms of arithmetic cases. The maximum error of the model in this paper is less than 5%, and the accuracy of the fitting is high. The node voltage has a maximum voltage offset of 0.0025, resulting in high voltage quality. The real-time optimization solves for an average voltage offset that is 97.9% lower and a maximum voltage offset that is 75.4% lower compared to the long-term scale reactive power optimization. The average running cost and standard deviation of the model increase with greater communication impairment. The model approach in this paper performs the best in terms of optimization cost, reducing it by 1.12%, 6.67%, 10.93%, and 0.94% compared to the other four approaches.
The Influence of Folk Sports Tourism on the Construction of City Brand Image
Authors: Zhang Xuchang , Wu Wenqiang 
Published: October 2024

Abstract
Folk sports, as a carrier of inheriting and promoting national culture, can not only show the unique charm of the city but also enhance the city’s popularity and reputation, providing a new opportunity for city brand building. To explore the relationship between folk sports tourism and city brand image, this paper uses the factor analysis method to extract the male factors that affect the city brand image. The model is validated through various validations, and finally, the components of the brand image of the tourism city are determined. Among them, “city tourism function image” and “city culture” are closely related to the development of folk sports tourism. Based on the Stimulus-Organism-Response (S-OR) model, we constructed a model of the influence mechanism of folklore sports perception factors on city brand image and city brand identity. Relevant hypotheses are proposed to explore the relationship between the four factors: folk sports perception factors, immersion experience, city brand image, and city brand identity. Finally, the research findings are rationally explained in the light of reality, and relevant suggestions are put forward for the construction of a city’s brand image.
Role Analysis of the Construction and Application of Folk Dance Knowledge Graph in Cultural Transmission
Authors: Zhou Wenjing , Chen Weigen 
Published: October 2024

Abstract
This paper first introduces ontology construction, knowledge extraction, and graph database in the process of knowledge graph construction based on folk dance. Secondly, the semantic similarity algorithm is used as the basis to construct the conceptual similarity (MD4) model, and the five types of similarity algorithms in the MD4 model are introduced. After that, based on this model, we will conduct a comparative study on the number of folk dance publications, keywords, and hotspots in China and abroad. Finally, suggestions are made for creating a knowledge graph that is based on folk dance. The annual volume of folk dance research published in China is generally increasing. In contrast, the amount of foreign publications on folk dance is generally low, and its maximum number of publications is only 67. In China, 1021 keywords finally got 156 nodes, and the total link strength of the total number of occurrences was 3942. 1352 keywords finally got 137 nodes, and the total link strength of the total number of occurrences was 1983. Among all the keywords in China, the top three co-occurrence-ranked keywords and hot words were folk dance, value, and development status, with a number of 817, 633, and 607, respectively. The foreign countries include folk dance (453), value (233), and performance (146). The cultural inheritance of folk dance can be greatly impacted by the knowledge map’s ability to summarize the development of folk dance.
A Study on the Dual Benefits of ESG Practices on Corporate Sustainability and Investment Returns Based on Big Data Analytics
Authors: Shen Wangqi 
Published: October 2024

Abstract
With the development of the green economy and the increasingly serious global ecological problems, the ESG concept is rapidly emerging. This paper proposes an evaluation model of corporate ESG sustainable development performance and investment efficiency based on big data analysis, which provides an in-depth discussion on the dual benefits of corporate sustainable development and investment return. Based on big data, the weights of corporate environmental E, social responsibility S, and corporate governance G rating values are defined, and the evaluation index system of corporate sustainable development performance is constructed through machine learning modeling technology to establish the corporate ESG portrait model. Based on the DEA evaluation model, input and output indicators are selected to construct the investment efficiency evaluation index system. The ESG sustainable development performance scores of enterprises in different industries have obvious differences, with the difference between the largest and smallest values being greater than 60 or more. In 2019-2023, listed companies in China had a sustainable development performance of 0.32, 0.37, 0.41, 0.37, 0.44, which showed an upward trend. Except for 2019, the annual investment returns of companies under ESG practices in 2020-2023 outperformed the CSI 300 index, reaching 17.75%, 28.32%, and 36.27%, respectively.