bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on the Application of Deep Learning in Ball Games
Authors: Chen Hao
Published: June 2024

Deep learning algorithms are widely used in image detection. Ball games, popular in sports, are amenable to data fiction due to their straightforward interaction models. With AI advancements, deep learning (DL) techniques like AlexNet, SSD, and DNN are increasingly applied in ball sports. These models have excelled in image and speech recognition, and their adaptation to ball sports research has led to advancements in ball classification/localization, trajectory tracking, game video analysis, and decision-making in multiplayer ball games. Deep learning models are able to learn complex features and patterns to detect and locate balls more accurately in images. This is very critical for ball detection in sports games, monitoring systems, and other fields, which can improve the accuracy and reliability of detection. Deep learning models can apply knowledge learned from one task to a related task through transfer learning. This makes it easier for the model to adapt to different types of ball detection problems, even with limited training data. The future of DL in ball sports is bright, promising significant changes and improvements in training, competition, and spectatorship.
The Professional Quality and Competency Factors among Double-qualified Teachers
Authors: Wang Jing
Published: June 2024

At present, the construction of the "double-qualified" teacher team in higher vocational education in China is still not perfect, and it is necessary to comprehensively optimize the teacher team system through educational practice. The researchers use that the analysis of the professional quality and competency scale will calculate the mean and standard deviation to gain a sense of the practices demonstrated by "double-qualified" teachers in higher vocational colleges, including the process of collaborative efforts, and the use of talents and perspectives to achieve outstanding results in teaching and research, and suggestions for the development plan of "double-qualified" teachers were proposed. The finding is reflective of the theoretical framework of McClelland summarized to pay careful attention to what to achieve success rather than based on intelligence-based assumptions but to let the test subject reflect the important points of the competency you intend to test, rather than to evaluate and estimate the underlying characteristics and properties through a test.
Comparative Analysis of the Differences in the Education System in China vs Germany
Authors: Huang Ruihan
Published: June 2024

This paper aims to analyze the education systems of China and Germany. While many papers solely focus on the individual nations' education systems, this study compares both countries. It offers comprehensive background information on both systems and statistical data is provided to show an understanding of their structures. As education has become more prevalent today, many discussions are going on about how it should be received. China and Germany are very distinct countries, not only in their history and culture but also in their educational framework. The study also evaluates the strengths and weaknesses of each education system. Furthermore, this study also explores the factors that shape these systems from different perspectives and how they impact societal values and individual aspirations. Moreover, the discrepancies between both education systems are identified, and a future-oriented solution is proposed. The study realizes the need for cross-cultural communication and mutual learning between both countries. Hence, it encourages an exchange of educational practices.
Evaluation of Green Suppliers Based on a Hybrid Weighting Approach and GRA Method
Authors: Li Xinru , Zhao Zhengyang
Published: June 2024

To align with the national dual carbon strategy and facilitate low-carbon production for enterprises, this paper incorporates the concept of green supply chain management and develops a scientifically sound evaluation index system for green suppliers by comprehensively considering five factors: quality, availability, cost, environmental management performance, and technology. The analytic hierarchy process and entropy weight method are employed to assign subjective and objective weights to each evaluation index while the grey correlation degree analysis method is utilized to rank and sort suppliers in order to select the optimal green supplier. Finally, an empirical example is presented to verify the reliability of our model.
Design of 1450-1500nm Bismuth-doped Fiber Laser
Authors: Hua Jinming
Published: June 2024

With the rapid development of information technology, people's demand for the transmission capacity of fiber optic communication networks is increasing. How to broaden the bandwidth of communication systems has become one of the key issues in the field of communication. Researchers have found that the operating bandwidth of amplifiers mainly limits the bandwidth of communication systems. Although multiple solutions have been proposed and implemented to address this issue, there are still many gaps in the design of full-band multi wavelength-related light sources. By studying the three-level system of bismuth ions, the rate equation and power transfer equation of a bismuth ion doped fiber laser are simulated, and the pump power threshold and output power are calculated. Using MATLAB for simulation experiments, the relationship between laser power and pump power, as well as their variation with propagation distance, were ultimately obtained. The simulation results show that under 830 pump lights, the pump light threshold power is 10W. After reaching the threshold power, the pump light power and laser power have a linear relationship, and as the propagation distance increases, the pump light power gradually decreases and the laser power gradually increases. The analysis shows that the power generated by the signal light in this band meets the theoretical standards, which verifies the correctness of the scheme.
The Innovative Role and Practical Exploration of Virtual Simulation Driven by Artificial Intelligence
Authors: Li Xinyi
Published: June 2024

This paper discusses the innovative role and practical application of artificial intelligence (AI) and virtual simulation technology in the field of art design. The article first outlines the impact of AI on art designers, including data analysis and prediction, adaptive optimization and independent innovation and creation. The application advantages of virtual simulation technology in art design are discussed, such as intuitive preview effects and freer creative space. The article further analyzes the development prospects of the integration of AI and virtual simulation technology, including the intelligent, immersive experience and intelligent creation of art design.AI has broad application prospects in art design, which can shorten the design cycle, provide personalized design optimization solutions, and reduce the cost of trial and error through simulation and prediction. Virtual simulation technology brings an immersive experience to users through a three-dimensional interactive environment, and combined with the personalized adjustment of AI,it can further enhance the user experience. Finally, the article looks forward to the future of AI and virtual simulation technology in art design, indicating that art design will develop in a more intelligent and humanized direction, bringing more innovative and personalized experiences to designers and users.
Multi-Armed Bandit Algorithms: Innovations and Applications in Dynamic Environments
Authors: An Lei
Published: June 2024

This paper delves into the fundamental concept of the Multi-Armed Bandit (MAB) problem, structuring its analysis around two primary phases. The initial phase, exploration, is dedicated to investigating the potential rewards of each arm. Subsequently, the exploitation phase utilizes insights from exploration to maximize returns. The discussion then progresses to elucidate the core methodologies and workflows of three principal MAB algorithms: Upper Confidence Bound (UCB), Thompson Sampling, and Epsilon-Greedy. These algorithms are meticulously analyzed for their unique approaches and efficiencies in handling the MAB problem. Expanding the scope further, the paper spotlights three practical applications of MAB algorithms. The first application involves Dynamic Resource Allocation in Multi-Unmanned Aerial Vehicle (UAV) Air-Ground Networks, leveraging the K-armed Bandit framework. This is followed by an exploration of Product Pricing Algorithms grounded in MAB principles, offering innovative solutions for dynamic pricing strategies. Lastly, the paper examines a cost-effective MAB algorithm tailored for dense wireless networks, addressing the complexities and demands of modern network infrastructures. This comprehensive study not only highlights the versatility of MAB algorithms but also underscores their growing importance in diverse real-world applications.
Research on the Path of Rural Revitalization Enabled by Digital Economy
Authors: Wu Tongyu , Jiang Jiahong , Yang Feiyan
Published: June 2024

First of all, this paper introduces the background of rural revitalization strategy and the development of digital economy, and then analyzes the mechanism of rural revitalization enabled by digital economy. Secondly, the paper deeply analyzes the main challenges faced by digital technology entering rural industries, including infrastructure, talent shortage, policy environment and innovation level, and discusses how to deal with these challenges and realize agricultural transformation and upgrading. Finally, the paper puts forward a targeted realization path and a set of systematic path framework, covering multiple dimensions such as infrastructure construction, talent cultivation, policy support and industrial integration.
The Economic Impact of Sustainable Marine Development on The Aquaculture Industry
Authors: He Siyu , Lou Hanxi , Mei Xirui , Wang Jiaqi
Published: June 2024

With the growth of the global population and economic development, aquaculture has become an important source to meet the increasing demand for food. However, this industry also faces many challenges, including environmental pollution, resource shortage, biosecurity, and other issues. Therefore, achieving sustainable Marine development is crucial for the future development and survival of the aquaculture industry. This paper aims to investigate the economic impact of sustainable Marine development on mariculture. First, we will introduce the sustainable development of the ocean, and at the same time explain the impact of global warming and seawater pollution on the ocean, highlighting the need for sustainable development of the ocean. Then we will introduce the concept and definition of the aquaculture industry, and mariculture industry with the highest correlation with the ocean, and analyze the economic impact of ocean changes on mariculture based on the research status. Finally, based on the problems revealed above, the development mode and prospects are put forward. Through this study, we can draw the following conclusions: the sustainable development of the ocean is positive for both the economy of the aquaculture industry and the overall ecological environment of the ocean, but the joint efforts of the government, enterprises, and individuals are needed to achieve the long-term sustainable development of the ocean.
Impact of Technology in Dance Sports: How Digital Tools are Changing Training and Performance
Authors: Huang Peng
Published: June 2024

This research examined demographic characteristics, techniques of incorporating technology, disparities in evaluation, and obstacles encountered by coaches. The results of our study indicate that a significant proportion of participants are women (61%), aged between 18 and 20 (62%), and are spread throughout several academic years. Participants sometimes use technology into their training, mostly with dance technology and software. Although there are no notable disparities in terms of sex, age, or academic year, there is a substantial difference between first-year and third-year students in terms of their technology integration evaluation. The influence of technology on performance remains consistently mild across several aspects like as technique, timing and musicality, posture and alignment, frame and connection, choreography, style and creativity, and showmanship. The challenges encountered by coaches in technology integration include restricted availability in rural regions, financial difficulties, shortages in technical expertise, language obstacles, and managing restrictions related to competitiveness. The presence of resistance to change among athletes also presents a difficulty. The consequences indicate a need for customized training programs and resources to improve the technological proficiency of coaches and participants. Suggested measures include the establishment of technology resource centers, provision of specialized training platforms, and cultivation of cooperation with technology specialists.
Analysis of Build Your Dream's Marketing Strategy
Authors: Guan Yuxuan
Published: June 2024

With the continuous progress of science, environmental pollution is becoming more and more serious. Environmental problems are paid more and more attention by people. Under the premise of actively advocating new energy vehicles and green development, BYD (BYD) new energy vehicles in the context of green development, people began to gradually pay attention to the energy issues of the automotive industry. At the same time, the goal is to replace the traditional energy vehicle industry. However, China also strongly supports the development of the new energy vehicle industry. China has ambitious goals for developing new energy vehicles. At present, the Chinese government's subsidies for new energy automobile enterprises are very large, so the subsidies for new energy automobile enterprises within 1, BYD enterprise performance is particularly outstanding, it can be said that China's new energy leader. The research goal of this paper is to analyze the marketing strategy of BYD Company and get the research results that BYD is a seed player in China, with many uninspiring potential. The increase in green travel also makes environmental protection more advanced.
A Brief Analysis of the Musical Background and Playing Skills of "Overlord of Western Chu"
Authors: Shi Ke
Published: June 2024

Guzheng is also known as Han Zheng, Qin Zheng, Zheng Yao, Luan Zheng, Zheng instrument is the Han nationality traditional instruments, which belongs to the stringed instrument. It is one of the unique and important national musical instruments in China. It sounds beautiful, wide range, playing skills and rich, has the very strong expressive force, so it by the love of the broad masses of the people. There is now a small portable mini guzheng, guzheng, guzheng, half zither, koto, twelve average modulation zheng. Zheng is an ancient culture with Chinese, ancient folk instruments in this fertile native on the Loess plateau. Is plucked string instrument structure by a panel, the wild goose column (some area is also known for Zheng code), strings, Qian Yue Shan, string nail, tuning box, Qin foot, after Yue Shan, a side plate, the sound of opening, a bottom plate, a wear string hole composition.
Machine Learning-Based Prediction of Carbon Dioxide Emissions from Automobiles and Influencing Factors
Authors: Liu Yuxin
Published: June 2024

In recent years, the number of automobiles has been increasing globally, further leading to an increase in carbon dioxide emissions year after year. Carbon dioxide emissions from automobiles have become an important factor in global climate change and have attracted global attention. Firstly, the data were analyzed for missing values all duplicates were removed, and the main discrete random variables were converted into continuous random variables; then, the correlation coefficients of Pearson correlation coefficients were used to analyze the correlation between each automobile characteristic, and heat maps were drawn to remove the influencing factors with weak correlation; finally, the prediction models were established based on multiple linear regression and the Random Forest method, respectively. The results show that in both models, Fuel Consumption Comb is the most important factor influencing the growth of automobile carbon dioxide emissions; the random forest model is better than the multiple linear regression model and can effectively predict automobile carbon dioxide emissions.
Research on the Incentive Suggestions for the Performance Assessment of University Teachers
Authors: Liu Hongye , Kong Chuilong , Yin Xiaoshuang
Published: June 2024

In the context of developing new quality productivity, universities should give full play to the role of comprehensive performance appraisal incentives, and lead performance appraisal through positive incentives to guide teachers to grasp key tasks and promote the high-quality development of university education.However, there are still some outstanding problems in the current performance appraisal incentive work of college teachers, such as incomplete coverage of performance appraisal incentive objects, imbalance between performance appraisal teaching and scientific research incentives, weak performance appraisal results incentive feedback, performance appraisal incentives ignoring teaching career development, etc.Therefore, this paper takes the performance appraisal incentive of university teachers as the main content of research, combines with their work problems, puts forward some feasible suggestions to help university teachers improve their teaching and scientific research ability, and mold the high-quality image of moral cultivation and soul cultivation.
Research of Photodetectors Based On Two-Dimensional Materials
Authors: Wang Pengzhi
Published: June 2024

With the discovery of graphene, people have discovered that two-dimensional materials have unique properties and significance. Therefore, two-dimensional material-based photodetectors are also very valuable for research. This article first discusses the excellent properties of photodetectors based on two-dimensional materials, including high sensitivity, high modulation frequency, and wide spectral response capability. Then, recent research results on two-dimensional SnSe2/GaP type-II heterostructure photodetectors and photodetectors utilizing two-dimensional WSe2 were introduced. Additional representative studies, including two-dimensional layered materials-based valanche photodetectors and two-dimensional tin (II) sulfide (SnS) nanoflakes-based photodetectors, were also shown. The prospects and challenges of photodetectors based on two-dimensional materials were also discussed at the end of the article. They can be applied in fields such as video imaging, gas sensing, biological imaging, safety, night vision, optical communication, and motion detection. The issues of device stability, mass production, cost, and uniformity need to be addressed and find their more ideal commercial applications.
A Study of Tennis Score Evaluation Based on Logistic Regression and LSTM Neural Networks
Authors: Cao Yuhao
Published: June 2024

In order to study the performance of athletes in the competition, this paper establishes a comprehensive evaluation mechanism and prediction model through mathematical modeling. Firstly, this paper uses the clustering algorithm to categorize the data and establishes a score evaluation model according to the weights. Then, a momentum evaluation score calculation function was constructed and compared with the results of logistic regression algorithm. Finally, a multi-indicator data system was established to predict the results of the game using the LSTM neural network model. The experimental results show that the model proposed in this paper has a good prediction effect and provides suggestions to the participants.
Exploration of the Path of Visualized Rhythm Animation Applied to the Cultivation of Young Children’s Musical Rhythm Sense
Authors: Chen Yanping
Published: June 2024

In order to understand the current situation of cultivating young children’s sense of musical rhythm in kindergartens and teachers’ cognition and use of visual rhythm animation, a self-administered questionnaire was used to conduct questionnaire surveys and interviews with teachers in five kindergartens. The research found that kindergarten teachers have a positive perception of cultivating young children’s sense of music rhythm, but some teachers do not pay enough attention to cultivating young children’s sense of music rhythm; some teachers’ perception of visual rhythm animation is biased and the usage rate is low, and there is a single form and way of teaching organization; and there are various difficulties for teachers in cultivating young children’s sense of music rhythm. The heavy workload in kindergartens, teachers’ lack of musical literacy and digital awareness and ability affect the development of children’s sense of rhythm. Based on this, the following improvement paths are proposed: Facing up to the value of young children’s sense of rhythm in music and raising the importance of cultivating young children’s sense of rhythm in music; Responding to the requirements of digital transformation for preschool education, empowering visual rhythm animations with numbers to cultivate children’s sense of musical rhythm; Correctly understand visual rhythm animation and its role, promote diversified teaching organization forms and approaches; Implementing the concept of individualized teaching and promoting the development of musical rhythm among all young children; Improve the teaching process of cultivating children’s sense of music rhythm, play the role of evaluation, and optimize the path to develop children’s sense of music rhythm, improve the quality of music rhythm teaching, and promote the digital transformation of preschool education.
12C6+ Irradiation Mutation for the Selection and Breeding of High-Cholesterol-Lowering Lactobacillus
Authors: Liu Guoqiong , Wang Shuyang , Xu Fuqiang , Xun Xisi , Guo Fangzhu
Published: June 2024

A high-throughput screening method for the selection of lactic acid bacteria with high cholesterol-degrading ability was established using the 12C6+ beam irradiation mutagenesis technique. This study aimed to breed excellent strains with high cholesterol-degrading capability and explore the mechanisms of cholesterol degradation by these strains. The mutated strains JMR-01 (Lactobacillus reuteri) and SN-2 (Lactobacillus rhamnosus) after irradiation were primarily screened for high cholesterol-degrading strains by optimizing the KENJI culture medium with colony diameter as an indicator. The primary screened strains were further screened using ammonium ferric sulfate method. The mechanisms of cholesterol degradation by lactic acid bacteria were further investigated by determining the total cholesterol degradation rate, the cholesterol degradation rate through co-precipitation and absorption. The results showed that after primary and secondary screening, four mutant strains with high cholesterol-degrading ability (JMR-01-1, JMR-01-2, SN-2-1, SN-2-9) were selected. The cholesterol-degrading ability of strain JMR-01-1 was increased by 9.7% compared to the original strain JMR-01 (P<0.05), and the cholesterol-degrading ability of strain SN-2-1 was increased by 11.5% compared to the original strain SN-2. The total cholesterol degradation rate, co-precipitation, and absorption of cholesterol degradation rate of the four mutant strains showed no significant difference in the co-precipitation effect on cholesterol compared to the original strains, but the relative absorption rate was significantly increased. This study optimized the screening method for cholesterol-degrading strains and demonstrated through the exploration of different cholesterol degradation pathways by lactic acid bacteria that this screening method can select strains with high cholesterol absorption capacity.
Analysis of Economic Development in Urban Agglomerations by High-Speed Rail Network: Taking Beijing-Tianjin-Hebei City Cluster as an Example
Authors: Tong Zichen , Xu Yifan , Zhu Yidan
Published: June 2024

With the increasing impact of the opening of high-speed railway on the inner city, many indicators within the city have changed significantly, which plays an important role in the impact of the city's economy. Therefore, this paper explores how the high-speed railway network affects intra-city economic development based on the changes in three indicators of city size, per capita disposable income of residents and the structure of the three industries, as reflected by the population flow in the Beijing-Tianjin-Hebei city cluster. It is found that the opening of high-speed railway has led to a "siphon phenomenon" in the Beijing-Tianjin-Hebei urban agglomeration, which has both advantages and disadvantages for the development of large cities and small and medium-sized cities; it has a positive effect on the increase of disposable income of the residents; and it also has a positive effect on the development of tertiary industry.
Agricultural Land Suitability Assessment Based on GIS at the County Scale in Yibin, China
Authors: Xu Juan , Jiao Cuicui
Published: June 2024

As agricultural land resources scarce, food security has emerged as a pressing global concern. Conducting a suitability assessment of agricultural land is crucial for agricultural resources and food security. To establish an evaluation index system, we incorporated land, water, climate, and society four dimensions of 16 indicators. And we incorporated Entropy Weight Method (EWM), an objective method, with integrated evaluation model to assess agricultural land suitability in Yibin. Based on actual agricultural production, areas of land of urban construction, rural settlement and mining and water are subtracted. The Findings found that agricultural land suitability in Yibin presented a significant spatial heterogeneity. Areas with suitability and relative suitability accounted for 57.61% of Yibin’s land areas, which suggest Yibin has an abundance of agricultural land resources. Regions moderately suitable predominantly lie in the western and southern areas, covering 32.22% of the land area. Generally suitable areas accounted for 10.03% of Yinbin’s land areas, spatial distribution of which is similar to moderately suitable regions. Moderately and generally areas are potential areas for agricultural production. And regions for unsuitable accounted for only 0.14% of land areas. Overall, results mentioned above indicate that Yibin's agricultural land resources are in good condition. Considered terrain and water sources, this study revealed that the spatial distribution of topography and annual precipitation in Yibin closely mirrored both suitable and relatively suitable regions.
Research on the Impact of Social Media on the Decision-Making of Young Consumers in the Context of Clothing Choices
Authors: Dai Ziqiao , Wang Jingwei , Yang Xinyi , Zhou Peixian
Published: June 2024

To improving markets’ responsiveness towards consumers and then optimizing marketing strategy, it is of the essence to analyze how young consumers’ intentions are affected by social media and how the fashion industry develops and changes. To make the study more understandable and authoritative, the authors use the case of Zara, a well-known brand of casual wear, to reveal the background of fast fashion expansion and then provide a role model for position and target market, as well as a special marketing strategy. Afterward, a hand-conducted questionnaire by authors was carried out, specifically underlining the effectiveness of closing recommendations and driving purchasing decisions among young consumers. Leveraging influencers and utilizing user-generated content are approved to increase brand engagement and build brand loyalty. On the one hand, the shopping experience has been changed by technological convenience and transparent information. On the other hand, fake information and consumer privacy security are bringing risks currently. Simultaneously, competition on social media is intensifying. To solve these problems, governments and enterprises are responsible for fact-checking, verification, monitoring, reporting misinformation, and encoding data. Also, users are suggested to use private tools and raise security awareness. For companies, they can focus on creating unique consumer experiences and advocating ecologically conscious practices to increase competitiveness. In conclusion, the authors provide an analysis of social media and young consumers’ preferences, suggesting improvement and drawing a blueprint for the development of casual clothing.
Exploiting Convolutional Neural Networks for Galaxy Classification
Authors: Gao Chao
Published: June 2024

Galaxy classification is an important work in the field of astronomy. The efficiency of manually solving this problem is too low, and deep learning provides many methods for image classification. Using deep learning methods to automatically classify galaxies can greatly improve the efficiency of this task. Therefore, this paper uses mature Convolutional Neural Networks (CNN) models and self-designed simple CNN models, and compares their performance on the Galaxy10 DECals Dataset. In the experiment, the Inception network performed best, with an accuracy rate of 0.63 on the test set, but the training time was as long as about 2 hours. The simple CNN model ranked second, with an accuracy rate of 0.54, and the training time was only 20 minutes. The accuracy of other models is about 0.5, and the training time also takes 2 hours. The result performance of the model is worse than expected, which may be due to the less data used. The result of Inception is much ahead, and its solution to the problem provides a solution for the task of dealing with small data sets.
Research on Reliability Prediction Methods for Dynamic Networks Based On Deep Neural Networks
Authors: Zhang Shiyun , Wei Jianhua
Published: June 2024

In reality many networks, such as information storage networks, can be modelled as a multi-state stochastic flow network. The reliability of an information storage network is the probability that the network is able to deliver the required amount of information data to the specified server, and its an important metric to assess the performance of an information storage network. Most existing multi-state network reliability assessment algorithms are calculated using very small capacity vectors. However, calculating the reliability of such a network requires reuse of algorithms and is inefficient when the network size, demand, etc., changes rapidly, resulting in managers not making timely decisions accordingly. In order to obtain reliability metrics quickly, this paper proposes a dynamic network reliability prediction model based on deep neural networks (DNNs), which allows the corresponding reliability to be obtained quickly even when the network is changing rapidly. Finally, a local information storage network is used as an example for validation to illustrate the feasibility of the prediction model.
An Analysis of the Impacts of Interaction using Social Media Platforms on Stock Liquidity
Authors: Dong Yukun
Published: June 2024

Social media platforms have developed into a way for more and more investors to interact with each other, and investors are interacting more and more frequently on social media platforms. The study looked at the association between the number of forum posts in the Oriental Wealth stock bar as a measure of social media interaction and stock liquidity as a measure of turnover rate is examined through a panel fixed-effects model, and the analysis results suggest that the number of bar posts has a significant positive effect on stock turnover rate, which indicates that the interaction on social media platforms affects the liquidity of stocks, and the more frequent the interaction is, the higher the liquidity of stocks is. This study provides empirical evidence for the field of investors' social media interactions and stock liquidity, while individual stock companies and regulators should also pay attention to investors' interactions on social media platforms, and do a good job of communicating with investors in a healthy way to avoid abnormal fluctuations in the stock market.
Current Situation of College Students' Mental Health and Countermeasures
Authors: Liang Shujuan , Feng Zhenxi
Published: June 2024

The purpose of this paper is to discuss the current situation and countermeasures of college students' mental health in China. Firstly, by analysing the types, causes and effects of college students' psychological problems, it is found that college students' psychological problems are mainly related to anxiety, depression, interpersonal relationships, etc., and the causes include academic pressure, employment pressure, personal character, etc., which have a negative impact on college students' study, life and future development. Secondly, this paper puts forward countermeasures to solve the psychological problems of college students in terms of preventive measures and intervention strategies, such as improving psychological quality, strengthening mental health education, establishing a sound psychological support system, and psychological counselling and treatment.
Vegetable Product Pricing Replenishment Strategy Based on WOA
Authors: Wang Zhiyuan , Liang Jiachang , Zhang Jiaxing
Published: June 2024

In fresh food superstores, the freshness date of general vegetable commodities tends to be relatively short, and the quality of vegetable commodities will deteriorate with the delay of the sales time. Therefore, how to allow supermarkets to ensure that the daily replenishment of the amount of market demand for various types of vegetable products while trying to meet the premise of maximizing their profits has become an urgent problem, this study aims to propose an innovative vegetable product prediction model based on big data, which adopts the SARIMA model to accurately predict the daily replenishment amount of each type of vegetable product in supermarkets. Meanwhile, based on the replenishment amount, the WOA model takes the addition coefficient and sales of different vegetable products as the dependent variable, and the final profit as the independent variable. The corresponding pricing strategy is formulated to maximize the profitability of the supermarket. Through solving the model, it is found that the maximum profit of the supermarket's vegetable products in the next week is 3,649.65 yuan.
Synergies and Challenges in the Integration of Cloud Computing and Deep Learning: Current Status, Interconnectedness, and Future Directions
Authors: Yang Zihang
Published: June 2024

This article reviews the status and recent developments in the integration of cloud computing and deep learning, as well as the interrelationship between these two technologies. The paper explores the intersection of cloud computing and deep learning in addressing cybersecurity challenges. Amidst the rapid expansion of the worldwide public cloud services market, the vulnerability to cyber-attacks and breaches in data management is on the rise. Different intrusion detection systems use different deep learning techniques to improve the effectiveness of intrusion detection in cloud computing environments. Additionally, the use of encryption technology and the corresponding deep learning retrieval technology further improves the security of cloud data. Moreover, the paper deeply studies how the scheduling mechanism of deep reinforcement learning can optimize the performance of cloud services by efficiently allocating resources and solving the problem of slow cloud service speed. It also derives the optimal energy strategy through deep neural networks to address the energy consumption challenges in cloud computing data centers. This article also reviews the five emerging architectures of cloud computing and explores the role of deep learning within these frameworks. Finally, it analyzes some of the challenges facing the future of cloud computing and deep learning, including the security and confidentiality of cloud computing, as well as low latency and high throughput optimization in the field of deep learning. In summary, this article provides insight into current trends, challenges, and future prospects for the evolving integration between cloud computing and deep learning.
Role of Ozone Hole on Life on Earth and Countermeasures
Authors: Zhang Junye
Published: June 2024

The purpose of this paper is to investigate the protection of the ozone layer and the extensive effects of the hole diffusion on the life on Earth. First, the ozone layer is a layer in the atmosphere that absorbs ultraviolet radiation from the sun and protects life on earth from ultraviolet damage. UV radiation is destructive to living organisms and can cause health problems such as skin cancer, eye damage and even genetic mutations. Therefore, the existence and health of the ozone layer is directly related to the survival and health of organisms on Earth. Next, we will study the formation and diffusion of the ozone hole. The hole in the ozone layer is caused by the destruction of the ozone layer caused by human activities such as the release of chemicals such as chlorofluorocarbons (CFCS). When these destructive factors enter the atmosphere and are irradiated by ultraviolet light, they break down into active free radicals, which destroy ozone molecules. Over time, these destructive factors accumulate in the atmosphere, causing the ozone layer to gradually thin and eventually form the ozone hole. Finally, we will discuss in detail the effects of these ozone holes on life on Earth. The existence of the ozone hole allows ultraviolet radiation to reach the Earth's surface, posing a direct threat to living organisms. Studies have shown that UV radiation can cause problems such as stunted plant growth, death of Marine life, and skin damage to animals. In addition, ultraviolet light can accelerate the Earth's climate change, causing more extreme weather events, such as floods, droughts and storms, which will have a broader and far-reaching impact on Earth's life. Through the discussion in this paper, we can clearly understand the impact of the ozone hole diffusion on the earth's organisms. In order to protect our home and biodiversity, we must take active measures to reduce the damage of human activities to the atmosphere in order to maintain a healthy and stable ozone layer. This requires our global efforts to take scientific and effective measures to solve this problem. Only in this way can we ensure that life on Earth can continue to live healthy and safe on the blue planet.
The Impact of School Climate on Teachers’ Self-efficacy Towards a Comprehensive Program for Professional Development
Authors: Yang Haina , Villanueva Lizelle Eugenio-
Published: June 2024

This study evaluated the school climate and the teachers' self-efficacy with a goal to propose a comprehensive program for teachers' professional development. Based on the findings, the researcher concluded the following: (1) The majority of teacher respondents are female, aged 31 to 40, holding Master’s degrees, and collectively possess over ten years of experience across all school departments. (2) School climate, especially student interactions, was highly manifested among the four indicators evaluated by teachers. Teacher relations ranked second, followed by leadership and decision-making. Attitude and culture were rated lowest but still assessed as highly implemented. (3) Teachers expressed highest self-efficacy in digital literacy, followed by instructional strategies, student engagement, and classroom management, indicating confidence in various teaching aspects. (4) School climate significantly impacts teachers' self-efficacy, influencing empowerment, motivation, and confidence in engaging students and using instructional methods effectively. (5) A proposed teacher professional development program aims to enhance teachers' self-efficacy through targeted initiatives focused on school climate improvement. Based on the study's conclusions, the following recommendations are suggested(1) Focus on raising awareness of attitude and culture within the school through initiatives like cultural competence training and diversity workshops. (2) Encourage collaboration among teachers from different departments to enhance understanding of teaching practices and promote a unified school climate. (3) Provide ongoing support and resources for integrating technology into teaching practices, including training on new tools and effective digital resource incorporation. (4) Foster cross-departmental collaboration among teachers to enrich teaching experiences and promote a sense of shared efficacy. (5) Execute a comprehensive teacher professional development program to cultivate a positive school climate, promote collaboration, and empower educators for an enriched teaching environment.
Photo-Responsive Materials for Drug Delivery System
Authors: Jiang Hao
Published: June 2024

Recently, much research has focused on photo-responsive materials since the responsiveness of materials is convenient to control. The application of photo-responsive materials in drug delivery is widely reported. The o-nitrobenzyl group and coumarin group are two common functional groups that can respond to lights. The o-nitrobenzyl group is photo-cleavable and responds to 365 nm UV lights, while the coumarin group is both photo-cleavable and photo-dimerizable and responds to lights with various wavelengths. The dimerization process of the coumarin group is reversible. Materials based on these two groups are also easy to be prepared. In this review, photo-responsive materials for drug delivery systems are introduced. The whole delivery strategy for each work will be described in detail. All delivery systems show good drug-releasing ability in light stimuli in vitro. Due to limited experiment data, the effectiveness of the delivery system in vivo cannot be determined. The near-infrared ray responsive coumarin group-based materials are more recommended due to the better penetrability of near-infrared rays.
The Impact of Digital Infrastructure Development on the Consumption Upgrade of the Population
Authors: Shao Tingyin
Published: June 2024

Building new infrastructure, which is embodied in digital infrastructure, has a major influence on China's economy's quality of development while also having a major effect on the upgrading of citizens' consumption. This paper uses the entropy weight method to synthesize the composite index of residents' consumption upgrading and the composite index of digital infrastructure construction based on panel data from 31 Chinese provinces from 2011 to 2020. Then, it applies the two-way fixed effect model to study and analyze the relationship between residents' consumption upgrading and the development of digital infrastructure. The results of the study show that, firstly, the construction of digital infrastructure is conducive to enhancing residents' consumption upgrading, and passes the stability test and endogeneity test. Second, the mediating effect analysis shows that digital infrastructure construction promotes residents' consumption upgrading through industrial structure upgrading and increasing income level. Third, the promoting effect of digital infrastructure construction on residents' consumption upgrading is more significant for residents with lower levels of population aging, higher levels of innovation, and residents in the western region. Given this, it is recommended that digital infrastructure development is further developed to optimize the impact of digital infrastructure development on residents' consumption upgrading and to promote residents' consumption upgrading.
Evaluation on the Level of Functional Movement Screen (FMS) and Functional Training VIS-À-VIS Sprint Performance of College Track and Field Athletes
Authors: Pan Juqian
Published: June 2024

This study selected 56 sprint student-athletes from the track and field team of Hechi University in Guangxi, China, as test subjects. Before the experiment, all athletes were assessed with the Functional Movement Screen (FMS) test, and a detailed analysis and comparison of the athletes' FMS scores were conducted from an objective perspective. After 12 weeks of functional training intervention, a second FMS test assessment was carried out on the participating athletes. The survey results showed that before the training, the movement quality and functional movement ability of the student-athletes were average. Among them, the scores for core stability, lower limb explosive power, and multi-joint movement tests were evaluated as 3 points, showing excellent core stability and lower limb strength. However, the scores for agility, upper limb coordination, and the 100-meter test were rated as 2, which was average. Before and after training, the overall average score of the Functional Movement Screen (FMS) for the student-athlete respondents increased from 15.4500 to 18.1786, and the t-value was -14.140, indicating a significant difference in functional movement levels before and after training. Participants showed noticeable improvements in flexibility, stability, and overall movement quality after the training intervention. Data from the 100-meter test showed that the average score before training was 2.3571 and post-training was 2.9464, with a calculated t-value of -8.883, indicating a significant difference in sprint performance before and after the training. Therefore, introducing this new theory of FMS into future sprint teaching and training practice can not only help correct athletes' physical function deficits and cultivate correct movement patterns, but it can also serve as an effective complement to track and field training methods, providing a theoretical basis for scientifically-informed coaching.
A Decision Model for High School Students' Summer job Choices: a Study Combining Hierarchical Analysis and Entropy Power Methods
Authors: Zhu Jingkai , Li Guochen , Zhang Jingyao , Liu Hangyu
Published: June 2024

As summer vacation approaches, high school students face an annual opportunity: choosing a summer job. These job opportunities not only provide a way to earn money, but also help students explore their career interests, develop key skills, and prepare them for future educational and career paths. However, high school students often have difficulty in finding the right job. To solve this, we have constructed a decision model that combines the hierarchical analysis of hierarchy (AHP) and entropy weighting method, aiming to find the best match among the many choices for high school students. The problem is essentially a multi-criteria decision-making problem that involves a number of decision-making factors, which need to be taken into account, along with the job characteristics and the applicant's profile and preferences. In our research, summer jobs are evaluated on a total of eight criteria: income, safety risk, job purpose, working conditions, and work. The model takes into account the job characteristics and the user's profile/preferences, and is therefore able to recommend the best job that matches the user's profile/preferences. In this paper, the AHP is used to determine the relative importance of these criteria for each individual, while the entropy weighting method is used to determine the relative importance of these criteria from an objective perspective. The model works as expected by validating it against nineteen types of job and ten fictional characters. Not only can we recommend the best jobs with the highest scores, but we can also rank all candidate jobs according to the calculated priority, providing users with a wider range of job options.