bluuebunny/crossref_metadata_2025 huggingface dataset:
Incorporating Subjectivity into Economic Models: A Study on Consumption and Consumer Sentiment in The U.S.
Authors: Yang Zining
Published: June 2024

This study examines the integration of consumer sentiment into economic models to elucidate consumption dynamics in the United States. Drawing on John Maynard Keynes's concept of 'Animal Spirits,' we analyze the relationship between consumer sentiment and consumption, alongside objective economic indicators. While consumer sentiment demonstrates a significant influence on spending behaviors, its significance diminishes when economic fundamentals are considered. This nuanced perspective underscores the multifaceted nature of consumer sentiment and highlights the need to integrate both subjective and objective factors into economic modeling.
Mongolian Education Resource Platform Based on Springmvc+Hibernate+Spring Integration Framework
Authors: Li Xingwang , Shen Yili
Published: June 2024

With the popularization of educational informatization and the advancement of computer technology and multimedia playback, the process of educational networking has reached new heights nationwide. The education networking in Inner Mongolia Autonomous Region is currently in a rapid development stage. In order to provide Mongolian-speaking students with the benefits of educational networking, it is imperative to design and implement a Mongolian language educational resource platform. The designed Mongolian Language Educational Resource Platform in this paper adopts a B/S architecture and utilizes the SpringMVC, Hibernate, and Spring frameworks for overall development. Firstly, the relevant technical knowledge used is introduced, including the B/S architecture, the main frameworks used, and CSS technology, among others. Then, the requirements specification and detailed design plan of the platform are elaborated, including the database design. Finally, the implementation process of the core functionalities of this Mongolian language educational resource platform is described, and unit testing methods are employed to test these core modules. The system in this paper achieves the basic functionalities of the Mongolian language educational resource platform, and the entire platform's functionalities have met the expected goals.
Language Differences between Chinese and Western Cultures
Authors: Li Chenxi
Published: June 2024

Although the general culture has the same basic elements and structure, but different cultural systems have their own different emphasis and the basic spiritual connotation. Culture is the basis of language, language is the carrier of culture, reflecting the culture. The national language behind any culture has kinship terms. Kinship appellation is not only a common language phenomenon, but also a cultural phenomenon, reflecting the cultural spirit and values of different nationalities. This paper will mainly from the perspective of Chinese and English appellation in Chinese and Western languages to explain and compare the differences between Chinese and Western cultures and analyze the reasons.
Machine Learning and Fama-French Three-Factor Model Applications for Analyzing Stock Price in Technology Enterprises
Authors: He Jiaxiang
Published: June 2024

This study endeavors to forecast the stock prices of the leading U.S. technology entities - Google, Microsoft, Amazon, Meta, and Apple - through the application of diverse machine learning models, complemented by the traditional Fama-French three-factor model. The employed models encompass Convolutional Neural Networks (CNN), Long Short-Term Memory Networks (LSTM), Support Vector Machines (SVM), and Decision Tree models. Initially, historical stock price data is utilized to train these machine learning models, enabling the identification of potential price trends. Subsequently, the integration of the Fama-French three-factor model enhances the analysis by scrutinizing the impacts of market risk, company size, and book-to-market value on stock prices. The outcomes illuminate both the effectiveness and limitations of various models in stock price prediction, highlighting the advantages of machine learning methodologies over traditional financial theories. This research provides financial market analysts and investors with a fresh perspective on the amalgamation of machine learning and traditional financial theories for enhanced stock price prediction.
Stock Trend Prediction and Analysis Based on Machine Learning
Authors: Sun Ailin
Published: June 2024

Stock trend prediction is a critically important activity in the financial sector. Investors aim to gain a better understanding of market dynamics, make wiser investment decisions, and manage investment risks more effectively by forecasting stock price trends. This is the focus of our upcoming research. This paper aims to utilize machine learning methods such as Support Vector Machines (SVM), based on spatial interval maximization strategies, Random Forest, based on multi-decision tree parallel learning strategies, and eXtreme Gradient Boosting (XGBoost), based on classification functions, to devise accurate classification function strategies for predicting and analyzing fluctuations in Dow Jones stock prices. Principal Component Analysis (PCA) will then be used to select some suitable features, identifying key factors with the greatest impact and minimal inter-correlation related to stock prices. Through a combination of various classification models, the research aims to forecast the future rise and fall of Dow Jones stocks. It has been observed that performing feature curation through PCA in advance enhances the predictive accuracy of different machine learning methods. Notably, the combination of PCA and XGBoost achieves the highest predictive rate. This approach provides a robust and scientifically grounded method for future stock price predictions and the formulation of trading strategies.
A Scoping Review of Research on English Academic Writing for Chinese Graduate Students
Authors: Xiao Yijun
Published: June 2024

Based on 16 studies on Chinese graduate students' English academic writing, this paper summarizes the current research trends in China from the aspect of research methods and content. After combing and summarizing, it is found that: (1) most relevant researches in China have adopted three forms of research methods, which are: questionnaire survey or interview survey, classroom observation and text analysis. (2) currently, challenges in the English academic writing process for Chinese graduate students primarily revolve around inappropriate language usage and insufficient writing skills. (3) The solutions proposed at present mainly include improving students' writing ability in practical exercises, implementing new teaching models and introducing new teaching methods. It is helpful to find and summarize the problems existing in the current English academic writing courses in China, as well as the difficulties existing in the process of English academic writing for Chinese graduate students, so as to help them improve their English academic writing ability.
Analysis of the Affective Factors of High School Struggling Students’ English Learning Based on Affective Filter Hypothesis
Authors: Wang Tong
Published: June 2024

The increasing prominence of English parallels the relentless march of globalization. In China’s high schools, it stands as one of the trio of core subjects, a testament to its pivotal role in today’s interconnected world. Yet, despite its undeniable importance, a subset of students grapple with the challenge of learning English and find themselves ensnared by the hurdles they encounter. Turning to the Affective Filter Hypothesis proposed by Krashen, we recognize that motivation to learn, self-confidence, and anxiety are pivotal elements that profoundly impact language acquisition. These three affective factors act as a filter that can either facilitate or impede language learning. This essay will delve into an analysis of an English struggling learner through the lens of Krashen’s Affective Filter Hypothesis, aiming to unearth insights that may guide high school English teachers in supporting their students who face similar educational barriers. By understanding how affective factors influence language absorption, educators can better tailor their instructional strategies and foster an environment conducive to overcoming the linguistic challenges faced by these learners.
Stock Data Analysis of Competing Companies in Competitive Market: The Case of NVIDIA Corporation
Authors: Qi Letian
Published: June 2024

On May 24, 2023, NVIDIA released its impressive first-quarter results, and the stock soared 30% that day, making NVDA the sixth largest company in the world. NVDA has been a heavy player in almost most of the global technology fronts of recent years (cloud computing, cryptocurrency, metaverse, artificial intelligence, etc.). NVDA dominates the AI training space with over 95% market share. Thus, it is extremely important to keep an eye on the NVDA stock market trend because it is not only crucial for the stock market but also a key aspect of how human science and technology will progress in the future. This article mainly analyzes the correlation between the stock market data of NVDA and its competitors (from NVDA's data center, graphics cards, professional visualization, games, and other business aspects) to achieve the purpose of monitoring and predicting the future trend of NVDA's stock market. It is hoped that provide valuable insights for investors and market analysts, enabling them to make informed decisions and predict the trajectory of NVDA's stock market performance.
A Study on the Preferences and Behaviors of College Students Who Shop Online for Clothes
Authors: Wang Sirui
Published: June 2024

In today’s society, e-commerce is becoming more and more popular, ushering in a new era of online shopping. As an emerging mode of consumption, online consumption has brought great convenience to college students’ daily life, but also has a serious impact on the consumption concept of college students whose psychological development is not yet mature, among which the negative impact is undeniable and needs to be taught and corrected in time. As a group with distinctive characteristics among many online consumers, college students can grasp the changing ways of the Internet as quickly as possible and skillfully use online channels to shop. Irrational consumption behaviors such as blind following, excessive, comparison, and impulsiveness are common among college students. In the case of insufficient funds from their families, some college students will even choose to borrow online. How to correctly guide college students to establish a rational outlook on consumption is the biggest problem facing the whole society. Based on the questionnaire survey method and the characteristics of college students’ online clothing consumption behavior in Jiangxi Province, this paper analyzes the main influencing factors of college students’ online consumption behavior by stating the sources of living expenses, consumption platforms, clothing types, and purchase mentality, summarizes their consumption psychological characteristics, and puts forward scientific guidance countermeasures and programs for college students to establish a correct online consumption concept from five levels: government, society, universities, families and individuals.
Comparison of Latest 3D Content Generation Models with Minimal Input Images
Authors: Xie Haoxuan
Published: June 2024

Three-dimensional (3D) content generation has become a popular topic in recent years. It can be widely used in movie scene generation, video games 3D modeling, industrial design, and even pharmaceutical 3D structure characterization. Before artificial intelligence (AI), it can be difficult. People need to be trained to use various industrial 3D model applications and spend plenty of time building and refining a model. With the development of virtual reality and artificial reality, the demand for 3D content is rising rapidly. Traditional 3D content production cycles cannot fit the needs. Recently, the Text-to-Image technology has got great success. With the help of artificial intelligence, people can use a limited set of descriptive words to generate images. Typically, the model generates multiple images of the same category for users to choose from. Some fundamental techniques like Neural Radiance Fields (NeRF) and Diffusion Model can generate 3D scenes, avatars, and other 3D content using a couple of images. This progress marks the possibility of creating 3D content using text. Based on the technologies available today, there will be more applications for generating 3D content in the future. Selecting the core technologies will be a crucial issue in this regard. This essay mainly talks about three of the most popular models or technologies that use a minimum number of images to produce 3D content. The goal is to find the most suitable technology based on criteria such as quality, applicability, and other indicators.
Predicting Google Stock Prices Using Machine Learning Models
Authors: Zhao Zixiong
Published: June 2024

Stock price prediction could help investors decide to sell or buy the stock, which returns and minimizes risk. Precise forecasts can bring substantial financial gains, while unprecise forecasts can bring significant financial losses. During the volatile financial markets, a reliable stock price prediction is a valuable source for traders, investors, and financial analysts. The research uses different models to compare and analyze Google's stock price prediction. The research uses machine learning models to predict Google's stock price. The researcher aims to find the best model to predict the stock price using the Mean Square Error (MSE) result. The researcher chose Google as the topic because of Google's importance in technology and the stock market. The research uses Goggle's stock data from 2016-2021. The data includes opening, closing, and high, and low prices. The study used three methods, linear regression, decision tree, and random forest, to predict Google's stock market price.
Research on Intelligent System of Multimodal Deep Learning in Image Recognition
Authors: Xu Ting , Li Iris , Zhan Qishi , Hu Yuxiang , Yang Haowei
Published: June 2024

In this paper, a multi-scale image estimation method based on wavelet transform is proposed, which can effectively remove motion features from multiple videos. Then the autoencoder with sparsity limit is used to adjust the input signal to achieve effective compression. The effective features are extracted and the optimal unique vector is learned. The improved convolutional neural network is used to recognize weak moving objects. Experiments show that the algorithm can achieve high accuracy without large-scale learning samples, and the highest recognition rate is 99.36%. This algorithm has a great improvement over conventional algorithm.
Self-Efficacy and Effect on Blended Learning in Moral Education Course Among Students
Authors: Wu Junping , Casihan Maria Luvimi
Published: June 2024

This study explored the impact of blended learning on self-efficacy in moral education among 414 university students in China. The respondents, mostly female, were primarily freshmen. They experienced blended learning as the dominant teaching format, with face-to-face and online formats also present. The analysis revealed no significant gender-based discrepancies in self-efficacy across most domains, except for notable differences in ICT skills and enlisting peer and social support, pointing to potential gender-specific areas for intervention. The study identified significant correlations between students' self-efficacy and the effectiveness of teaching moral education in blended learning environments. Higher self-efficacy among students was associated with better teaching outcomes in blended learning contexts. These findings highlight the importance of enhancing students' self-efficacy to improve the success of blended learning in moral education. The results suggest that educators could focus on building self-efficacy to optimize the effectiveness and impact of blended learning in moral education courses.
Exploration of Legal Protection of Intellectual Property Rights in Intangible Cultural Heritage
Authors: Shen Jialuo
Published: June 2024

The traditional cultures passed down through generations among various ethnic groups around the world constitute intangible cultural heritage. This heritage is closely tied to the cultural spaces and expressions of people's lives, bearing a myriad of traditional cultures. However, under the influence of rapid globalization and comprehensive digitalization, the ecological environment of intangible cultural heritage in China has undergone significant changes, challenging the inherent protection models of intangible cultural heritage. Due to the current inadequacy of related laws in China, there are many flaws in the legal protection of intangible cultural heritage. Therefore, by exploring the significance, characteristics, and issues related to the legal protection of intangible cultural heritage in China, corresponding measures and solutions are proposed to address the problems encountered in practice.
Comprehensive Introduction and Analysis of the UCB Algorithm in Multi-Armed Bandit Problems
Authors: Hu Kaizhuo
Published: June 2024

This article commences with a review of the fundamentals of reinforcement learning, encompassing a detailed overview of its key models and algorithms. It then juxtaposes these concepts with traditional machine learning paradigms, offering a comparative analysis. Subsequently, the focus shifts to the background and developmental landscape of recommendation systems. It systematically categorizes and describes the commonly employed recommendation algorithms. The core of the discussion centers on the utilization of reinforcement learning in recommendation systems. Beginning with practical case studies, the article delves into the strategies for integrating reinforcement learning with recommendation systems, addressing current challenges and envisaging future directions for development. Insightful reflections and comparisons between reinforcement learning and traditional machine learning are also provided, elucidating the differences and applicable scenarios for each approach. In essence, this article serves as an extensive guide to the intricacies of reinforcement learning and recommendation systems. It aims to equip readers with the knowledge required to understand and effectively apply these technologies. As technological advancement and research progress, it is anticipated that reinforcement learning will increasingly infiltrate the operations of recommendation systems, offering more personalized services and enhanced user experiences.
Optimizing Movie Recommendation Systems with Multi-Armed Bandit Algorithms
Authors: Jian Yaosheng
Published: June 2024

In the current digital era, with the proliferation of online content, users are often overwhelmed by an abundance of digital advertisements, a consequence of the lower costs associated with digital channels compared to traditional media. Amidst this information deluge, recommendation systems have become pivotal in offering tailored suggestions to users. The Multi-Armed Bandit (MAB) problem, rooted in reinforcement learning, presents an effective approach for addressing the exploration-exploitation trade-offs inherent in recommendation systems. This paper specifically examines the implementation of MAB algorithms within the context of movie recommendation systems. A thorough literature review is conducted, focusing on the synergy between reinforcement learning and MAB algorithms, their role in recommendation systems, and an overview of fundamental MAB algorithms. To assess the efficacy of these algorithms, an experimental approach is designed, leveraging real-world datasets. This approach encompasses the formulation of the problem, data collection methods, selection of hyperparameters, and analysis of empirical results. The findings from these experiments indicate that Thompson Sampling stands out as the most effective MAB algorithm in the context of the studied datasets. The results of this study suggest that MAB algorithms have considerable potential to enhance the effectiveness of movie recommendation systems. Furthermore, the methodology and framework proposed in this paper offer valuable insights for integrating and combining multiple algorithms in complex decision-making scenarios.
Preface: 5th International Conference on World Trade and Economic Development (WTED 2024)
Authors: Huggins Veronica , Zhang Nongfu
Published: June 2024

We want to present the 2024 5th International Conference on World Trade and Economic Development (WTED 2024) held in Miami, USA during May 11-12, 2024. This conference was held both on-site and online. In general, there are two sessions, namely plenary and parallel. The plenary session was given to three keynote speakers, which ends with a Q&A session. Parallel session is for authors who present their papers and is carried out in four groups.
As a scientific forum, the WTED 2024 was attended by 56 participants from researcher, scholar, students, teachers, engineers, and practitioners who participate either as presenters or as participants. The main aim of this conference is to share ideas and knowledge and build collaboration with each other. We received many papers that will be selected to be published with the scope of world trade, economic development, and related area. In this volume, we accept a small number of papers for publication after meeting the scope, checking originality, and performing peer review.
We are hoping that this event will become a foothold of thinking in welcoming global developments. The organizing and editorial committee of WTED 2024 hopes you enjoy reading this volume. Besides, we would like to fully respect keynote speakers and all the presenters for providing their valuable contributions for this proceeding and the reviewers for their constructive recommendations to improve the presented articles. We, on behalf of the committee, would like to thank all parties for their participation in supporting this publication.
WTED Organizing Committees
Miami, USA
Research on the Image Shaping of Members of the Communist Party of China in Red Star over China from the Perspective of the Other
Authors: Tang Huifang , Liu Xinyu
Published: June 2024

The Red Star Over China written by Edgar Snow is the first book written by a foreign author to record the Red Army in the Soviet area. This book not only truthfully and objectively portrays the image of the communists during the Yan'an period through Snow's perspective as the other, but also serves as an effective medium for propagating the real Chinese Communist Party and its members from the other's viewpoint during the period of the Anti-Japanese War. From the perspective of others, Snow used the transformation of narrative perspectives and contrast to show the characteristics of CPC members in political ideology, military affairs, daily life, and other aspects, and creates a series of unique communists who are different from the old and other parties. Male CPC members are firm in faith and invincible in courage, female CPC members are as powerful as men, "red devils" have strong self-esteem and strong ability, and leaders are both wise and brave and empathic with their subordinates. Snow, because of his own unique characteristics and value judgment, creates an objective, real and vivid three-dimensional image from the perspective of the other.
Research on the Influence of Free Trade Agreement on Our Digital Product Trade
Authors: Gao Xiaoyan
Published: June 2024

The purpose of this study is to deeply explore the impact of free trade agreement on China's digital product trade. With the deepening of global trade and the rapid development of digital technology, free trade agreements are playing an increasingly significant role in promoting trade in digital products. By analyzing the characteristics of free trade agreement and combining with the current situation of China's digital product trade, this paper expounds the opportunities and challenges brought by free trade agreement to China's digital product trade. On this basis, this paper further discusses the strategy to enhance the international competitiveness of China's digital product trade, in order to provide a reference for China to gain greater advantages in the international trade.
Navigating the Energy Storage Landscape: A Comprehensive Analysis of Lithium-Ion Batteries and Improvements
Authors: Chen Xin
Published: June 2024

Lithium-ion batteries (LIBs) are the cornerstone of the transition to renewable energy and can power a wide range of devices such as smartphones as well as electric vehicles, although they face some major challenges such as resource scarcity, safety risks and thermal runaway. This paper provides an insightful discussion on the mechanism of operation of LIBs, their applications, and its limitations, emphasizing that LIBs, while widely used in electric vehicles and portable electronics, have certain limitations, like thermal instability. The paper also explores new alternatives, including solid-state and lithium-metal batteries, which have higher energy densities but also suffer from problems such as dendrite growth, for which it cites improvement strategies, such as innovative cathode and negative electrode materials and electrolyte additives, with which to increase the lifetime, safety and performance of the batteries. At the same time, the paper also considers the issue of resource constraints and proposes a scalable and sustainable approach to energy storage needs with a multi-pronged strategy necessary to overcome existing barriers.
Comparative Analysis of Shandong Free Trade Zone and Liaoning Free Trade Zone
Authors: Guan Xu , Li Minxuan , Wang Yuzhuo
Published: June 2024

Free trade zone is a trade-oriented reform based on its functions and positioning by regional characteristics. To build free trade zones, China began to promote the reform of free trade zones, and since then various free trade zones have been established in succession. This paper is based on the effectiveness of the Liaoning Provincial Free Trade Zone and Shandong Provincial Free Trade Zone, from the three aspects of the Regional Comprehensive Economic Partnership’s national trade initiatives, cross-border funds facilitation of financial policies, and the East and West Avenue Golden Hub. According to analyzing and comparing the policy initiatives and the case effectiveness of the free trade zones in the two provinces which have similar target positioning and concerning the problems in the above three aspects, it is important to give three suggestions as follows. First, put forward a proposal to solve the problem of foreign investment enterprise. Second, expanding the trade scope of the Belt and Road. Third, opening up cross-border funds. And last, there are also some corresponding prospects about the above three problems.
Thermal Cycling Stability of Ti-Zr-Nb-Al Shape Memory Alloy
Authors: Qu Wentao , Huang Sizhu
Published: June 2024

Shape memory alloys, as a novel class of intelligent materials, possess substantial application potential in the field of petroleum engineering at elevated temperatures. However, the complex downhole environment necessitates the alloy to endure alternating cycles of cold and heat, demanding both a high phase transformation temperature and excellent thermal cycling stability. This study focuses on a quaternary Ti-Zr-Nb-Al shape memory alloy, examining the thermal cycling stability of the Ti-20Zr-10Nb-xAl (x=1, 2, 3, 4 at%) alloys after subjecting them to 50 thermal cycles. Results indicate that the alloy composition, post 50 cycles, transitions from a single martensite α'' -phase to a duplex microstructure comprising α''-phase and β-phase. Changes in Al content did not significantly affect the phase composition of the alloy in its thermally cycled state. As Al content increases, both the tensile strength and shape memory effect of the alloy initially improve before declining. In terms of shape memory properties, the Ti-20Zr-10Nb-2Al alloy sample exhibits the most favorable thermal cycling stability, characterized by a tensile strength of 692 MPa, an elongation of 6%, a shape memory effect of 0.96% under 4% pre-strain, a shape memory recovery rate of 38%, and a Vickers microhardness of 381 HV.
Evaluation of the Economic Growth Effect of the Policy of Migrant Workers Returning Home to Start Businesses
Authors: Liu Dong , Jiang Ling
Published: June 2024

The policy of migrant workers returning home to start businesses plays an important role in promoting rural economic development and urban-rural integration. Starting from the economic perspective, this paper explores its impact on economic growth and puts forward relevant suggestions to promote the better implementation of the policy and economic growth.
Research on optimization of Dispatching System of Military Disaster relief Material Transport Vehicles
Authors: Shao Shuai , Li Congli
Published: June 2024

With the rapid development of informatization, a more efficient dispatching system is needed in the process of military logistics and transportation management to provide guarantee for emergency needs. From China’s point of view, in the face of natural disasters, the military’s participation in rescue is a common guarantee task. How to optimize the effective vehicle scheduling in the process of specific disaster relief material transportation is of great significance to promote the timeliness and effectiveness of rescue. This article establishes a vehicle scheduling model based on time windows by combining the characteristics of emergency transportation, in order to function by the time function, and can be solved by using genetic algorithm, according to the example analysis algorithm in overcome the problem of convergence time, can effectively promote the transportation vehicle scheduling, relief materials transportation scheduling decisions about the army have corresponding reference value.
Employ Mathematical Modeling to Summarize, Analyze, And Predict the Relationship Between Carbon Dioxide and Temperature, Location, And Other Factors.
Authors: Xie Yuheng , He Yanxi , Ye Yufei , Liu Chenfei
Published: June 2024

Fluctuations in the amount of greenhouse gases (GHGs) are affected by a variety of factors, both natural and artificial. Natural factors, such as volcanic eruptions and changes in the intensity of solar radiation, can cause fluctuations in greenhouse gases. However, in recent years, human activities have surpassed natural factors and have become a major driver of climate change. During the industrial revolution, the widespread use of fossil fuels, large-scale deforestation and emissions from factories caused irreversible damage to ecosystems. Rising global temperatures are destroying natural ecosystems around the world and are a potential threat to human survival. In this paper, we systematically examine and analyze the main sources of greenhouse gas emissions, explore the factors contributing to air pollution, and evaluate the specific impacts of these changes on global warming. We analyze the relationship between global warming and different factors (economic development, clean energy, and CO2 emissions) by using both one-way linear regression models and multiple linear regression models. A quadratic linear regression model shows that solar energy is the most promising renewable energy source. Meanwhile, using the global GDP as a criterion, we have shown that economic growth contributes to CO2 emissions. However, due to the governments having valued economic development more, the upward growth trend of the economic development curve is intensified, while the downward growth trend of the global average temperature is slowed down. Finally, we developed a multivariate linear regression model to evaluate whether using new energy sources could help mitigate global warming. Based on the previous analysis, we focus on the factor of CO2 emission. By using the linear regression model, we obtained the projected values of CO2 emissions, clean energy usage and global GDP in 2050, and the CO2 emissions in 2050 are 36.59439 billion tons, which meet the goal of carbon neutrality.
Exploring the Styles of Peasant Painters in the Netherlands: A Case Study of Bruegel Pieter the Elder
Authors: Zhou Sirui
Published: June 2024

This section discusses the origin and main types of development of the Renaissance. It gradually developed from Italy to the whole of Europe. Artists find inspiration from ancient Greek works and use scientific techniques such as perspective in their paintings, resulting in works that are full of volume. At the same time, the styles of southern and northern Europe are also different, especially in the southern region of the Netherlands where Bruguel is located. This is the birthplace of humanism, which has made the civic class the main force on the path of the Renaissance. It is precisely because of spiritual liberation that art has become a tool for ordinary people to showcase their thoughts and feelings. This article focuses on the peasant painter Peter Brueghel the elder of the Renaissance. And Bruegel was the last painter in this region after the Renaissance. He is also the founder of the Dutch painting school. Most of his works are inspired by farmers and his own life, as he chose to use art as a weapon to praise virtue and hope for national independence. He is a true 'farmer painter'. At the same time, his creative techniques are also changing over time.
Analysis of Principle and State-of-art Implementations of Heisenberg’s Uncertainty
Authors: Shao Yinuo
Published: June 2024

As a matter of fact, the Heisenberg’s uncertainty principle has important significance and extensive application in microcosmic particle science, is one of the cornerstones of quantum mechanics, proposed by Heisenberg in 1927. The uncertainty principle means that it is impossible to measure a particle’s speed and position at the same time. The uncertainty of particle, i.e., the product of uncertainty of position (∆Q) and uncertainty of momentum (∆P), is inevitable greater than or equal to Plank’s constant, it expresses the inconsistency between particle behavior in microcosm and macroscopic substance. This study is going to set forth the uncertainty meaning, the research progress of uncertainty principle from the angle of physics, and further exploring the physical significance of Heisenberg’s uncertainty principle. According to the analysis, the state-of-art applications will be demonstrated as well as the current limitations and prospects will be discussed. Overall, these results pave a novel path for further investigation in regarding to Heisenberg’s uncertainty.
Application of Steel Slag Asphalt Mixture in Road Engineering
Authors: Yang Wangyiling
Published: June 2024

As a by-product of the steelmaking process, steel slag has gained increasing attention and application in road engineering due to its excellent physical properties and abundant resources. This paper systematically analyzes the physical characteristics, chemical composition, and environmental impact of steel slag, explores the preparation process of steel slag asphalt mixtures, and investigates their mechanical properties and durability. Through actual engineering cases, the superior performance of steel slag asphalt mixtures in road base and surface applications is verified. The paper also comprehensively evaluates the economic, environmental, and social benefits of steel slag asphalt mixtures, highlighting their development trends and future research directions in road engineering. Finally, it identifies potential issues in the application of steel slag asphalt mixtures and proposes corresponding countermeasures, aiming to provide theoretical support and practical guidance for their promotion in road engineering.
Assessment and Enhancement of College and University Art Programs
Authors: Cai Xianghong
Published: June 2024

With the increasingly fierce competition for talents in society this year, the cultivation of comprehensive ability of students in colleges and universities has become particularly important, and the cultivation of art majors in colleges and universities, as one of the important components of college education, has an important role in promoting the enhancement of students' innovative ability and aesthetic ability. This paper will focus on the actual start of art education in five colleges and universities in Guangzhou City, Guangdong Province, China, combined with the law of art education, analyze the current situation and problems in the development of art professional education in Chinese colleges and universities, sort out the experience gained and lost of art talents in colleges and universities, and explore the challenges, coping strategies, and enhancement plans that colleges and universities are facing during the process of implementation of the art profession.The last section is about the conclusion of the study, which is derived from the results of the survey that the surveyed schools have offered courses in art majors, an outcome that has become an important part of the school's development. Various aspects of the arts curriculum have been implemented, but additional effort activities should be actively pursued to help one's optimal development and achievement, and targeted strategies for improvement will help guide the implementers to achieve the desired facilitation in realizing the set goals of arts education in China in the new era.
Operational Performance Evaluation of Iron and Steel Industry in China under the Background of Digital Transformation – An Application of Data Envelopment Analysis
Authors: Cui Cancan , Lyu Rongbin
Published: June 2024

This paper aims to study the operating performance of iron and steel enterprises under the background of digital transformation, using the DEA-Malmquist model to carry out static and dynamic analysis of the data from 2018 to 2022, which is divided into four parts. Generally speaking, most of the selected companies have good operational performance, but there is still room for improvement. This paper aims to establish a more comprehensive and objective evaluation system that aligns with the actual development of the steel industry, in order to fulfill the operational performance assessment needs of listed steel enterprises within the context of digitalization.
Meaningful Work, Job Anxiety, and Work Engagement of Chinese College Teachers: Strategies for Enhanced Work Engagement
Authors: Li Huihui
Published: June 2024

The study employed a descriptive-comparative-correlative research design that mainly investigated the current situation of meaningful work, job anxiety, and work engagement of Chinese college teachers. The findings showed that the purposively respondents drawn from varied population of respondents manifested minimum variants across profile. The profile variables such as sex, age, work status, job title provide ideal samples to objectively assess basic work characteristics for this study. The domains of meaningful work, job anxiety and work engagements are vital to the assessment of current context of teachers’ work characteristics that can be validated for various dimensions. The comparative assessment of the respondents’ based on profile on the meaningful work, job anxiety and work engagements selectively, such as job title influence their assessment of meaningful work. Likewise, vigor, dedication influence their work engagement. Therefore, it can be inferred that those teachers who find work meaningful, are those teachers who are more engaged at work. That teachers with more significant work engagement are more likely to experience a sense of meaning in their work and less likely to experience job anxiety. Thus, the study recommends replication of the current study to validate its findings.
Neuroscientific Prediction Model of Mouse Brain Activity Patterns
Authors: Zhang Jinxi
Published: June 2024

This study presents a neuroscientific predictive model, developed using a subset of data collected by Steinmetz et al. (2019), which records neural activity in mice during a visual discrimination task. Leveraging advanced data analysis techniques, including logistic regression, Principal Component Analysis (PCA), and k-mean clustering, the model aims to predict trial outcomes- success or failure - based on the patterns of neural activity and the visual stimuli presented to the mice. This predictive model is designed to address the challenges of interpreting complex neural datasets. It emphasizes the relationship between neural responses and behavioral outcomes. The logistic regression framework was chosen for its proficiency in binary classification, while PCA and k-means clustering facilitated dimensionality reduction and data segmentation, respectively. These methodologies enhance the manageability of this neural data. Upon analysis, the model displayed moderate predictive accuracy, indicating areas for further improvement such as random forests or support vector machines, which might offer improved performance in handling the dataset’s intricacies.
Review and Reflection on the Construction of Ecological Moral Education in China and Abroad
Authors: Wang Wenbin
Published: June 2024

At present, China is vigorously promoting the formation of new quality productive forces that will enable high-quality development, and the new quality productive forces themselves are green productive forces, which translates into the field of education, where the greening of education is to be promoted. Moral education is located in the first of the "five educations" in Chinese education, and it is undoubtedly of great significance to expand moral education from interpersonal moral education to ecological moral education. The main problems facing the construction of ecological moral education include lagging in the new direction of "big moral education," insufficient exploration of the mechanism of educational articulation, and imperfect construction of the relationship structure of various elements of moral education in schools. Based on this, we review the development and research on the construction of ecological and moral education in China and foreign countries and reflect on the implications for the construction of ecological and moral education in China and foreign countries to strengthen the government's implementation and supervision of ecological, moral education, to enrich and improve the construction of ecological, moral education curricula in schools, and to set up a platform for cooperation on "big ideology and politics" in order to promote the popularization of ecological, moral education.
Human Resource Management Practices and Organizational Performance: Towards a Proposed Employee Engagement Program
Authors: Zhang Keli , Villanueva Lizelle Eugenio-
Published: June 2024

The management of human resources in education is crucial, and failing to do so could have dire repercussions. This is due to the fact that education professionals are a key tool for attaining educational objectives and, as a result, contributing to national development. This study assessed the human resource management practices and their effect on organizational performance at School C in Shanxi Province, China. The researcher used adapted questionnaires that assessed the HRM practices in their school in terms of Compensation and benefits, training and development, and performance evaluation. Additionally, they assessed the performance of the organization based on their perceptions of its organization and governance, academic programs and curricula, institutional resources, and quality assurance. The participants in this study were 212 non-teaching employees from the various departments at School C in Shanxi Province, China. The goal of this research was to propose an employee engagement program designed to boost employee engagement, enhance HRM practices, foster a positive work environment, and ultimately improve overall organizational performance.
I Design and Material Selection of Single-Phase Transformers
Authors: Han Tingxuan
Published: June 2024

Transformers are indispensable appliances in our lives and play an essential role in the production, transport, and distribution of electricity for living and working purposes. An apparatus that uses electromagnetic induction to modify voltage is called a transformer. Therefore, this paper focuses on analyzing the basic working principle of a transformer, a detailed disassembly of the transformer, briefly analyzing the structure of the transformer, calculating the core parameters and coil parameters, selecting the appropriate model, and accounting for the results based on the rated power of the given conventional transformer. The goal is to successfully design a small single-phase transformer supplying power to resistive loads. Through a series of calibration calculations, it is finally determined that the selected iron core meets the operating standards and achieves the design purpose.
Research on Influencing Factors of Illegal Wildlife Trade Based on Multiple Linear Regression Model
Authors: Chen Yuemin
Published: June 2024

This study aims to explore the influencing factors of illegal wildlife trade and assess the role of key indicators such as technology, law, and international cooperation in reducing this type of trade. By integrating Spearman's correlation analysis and multiple linear regression models, we conducted an in-depth analysis of China's wildlife trade data. Initially, Spearman's correlation analysis revealed significant positive correlations between education, public awareness, technology, law, and international cooperation with the reduction of illegal wildlife trade. Subsequently, we constructed a multiple linear regression model to quantify the specific impact of these indicators on the reduction of illegal wildlife trade. The model results indicated that technology and law are the main drivers in promoting the reduction of illegal trade, while international cooperation also plays an important role. Furthermore, we conducted sensitivity analysis to evaluate the impact of changes in model parameters on the predictive outcomes, ensuring the robustness of the model. This research provides a scientific basis for policymakers, emphasizing the importance of increasing technological investment, improving legal regulations, and deepening international cooperation in combating illegal wildlife trade. The findings not only contribute to the protection of biodiversity but also offer strategic guidance for achieving harmonious coexistence between humans and nature.
Risk Assessment on Banks under Rising Interest Rates
Authors: Cheng Cihang
Published: June 2024

This paper explores the critical role of the banking sector in the economy and society, with a focus on various risk dimensions affecting this industry. These dimensions include liquidity risk, credit risk, market risk, and systemic risk. The paper underscores the banking sector's significance for the national economy and financial stability, defining and explaining these risks' impact. The liquidity risk section delves into the definition, causes, and implications of liquidity risk, examining policies and measures taken by banks, especially in response to the challenges posed by the COVID-19 pandemic. Credit risk is explored through a case study of Credit Suisse, discussing the definition and consequences of credit risk and its potential role in bank bankruptcies. Market risk is analyzed with a focus on interest rate changes and their effects on banks, using the case of Silicon Valley Bank to illustrate how market risk can lead to bank failures. Systemic risk is explained, emphasizing its definition, causes, and significance to banks while also suggesting measures to avoid it. This paper concludes by summarizing the impact of these risks on the banking sector and offers recommendations for risk management and the future direction of the industry. Through case studies, it highlights the complexity of these risk dimensions and their crucial role in maintaining banking sector stability and overall economic well-being.