bluuebunny/crossref_metadata_2025 huggingface dataset:
Nationalism versus Internationalism in International Law in the Field of Cultural Relics Recovery
Authors: Liu Jingyi
Published: August 2024

Cultural relics are indispensable in preserving the unity and identity of nations due to their significant historical, literary, and artistic value. The challenge of recovering lost cultural relics has been a persistent issue not only for China but also for other civilizations with rich heritages. Despite the widespread attention this issue has garnered within the international community, the field of international economic law still lacks a definitive legal instrument that outlines clear measures for the repatriation of cultural objects. This absence of a legal framework has prevented international organizations from reaching a consensus on the conditions under which cultural artifacts should be returned. This paper focuses on the 1995 Rome Convention as the study object to apply comparative and normative research methods in examining the influences of nationalism and internationalism on the restitution of cultural relics. It analyzes the impacts of these two advocates on international law legislation and judiciary process. Based on this, the paper aims to offer recommendations on the stance that international law should adopt concerning the recovery of cultural heritage, thereby contributing to the development of a more coherent and effective legal framework in this domain.
Water Quality Prediction of Liuxi River based on ICEEMDAN-WOA-LSTM Model
Authors: Yong Ke , Wang Lihui , Hao Lei
Published: August 2024

Water quality prediction is a crucial task for ensuring the safety and sustainability of water sources. It supports water resource managers in making informed decisions and taking appropriate actions to prevent water pollution and maintain water quality standards. Considering the non-linearity, latency, and complexity of water quality data, this study proposes a combined model for water quality prediction based on Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (ICEEMDAN) and Long Short-Term Memory (LSTM) networks. The model decomposes and reconstructs variables from time series data to achieve water quality predictions. Comparative experiments with other network models demonstrate superior performance of the proposed model.
Reducing the illegal wildlife trade based on multiple linear regression model
Authors: Qu Yingying , Yuan Xu , Sun Xinyi
Published: August 2024

Illegal wildlife trade has serious negative impacts on the ecological environment and species diversity, and it is of practical significance to propose projects to reduce it for the protection of the ecological environment. By analyzing the problem around illegal wildlife trade, we constructed and continuously monitored and evaluated the improvement model to present the factors, formulate solutions and predict results affecting the illegal wildlife trade. We use EWM to calculate the weighting coefficients of the three organizations in relation to power, resources and interest. Finally we choose the UNEP as our client. 5a sliding window algorithm and social awareness rate formula are developed by us for comprehensive data analysis, ultimately resulting in a strong adaptation of program content to client goals. So as to achieve the goal of reducing the illegal wildlife trade behaviors and protecting the ecological environment. The paper could effectively reduce illegal wildlife trade, enhance public awareness of animal protection, maintaining an accurate level of prediction when responding to unforeseen events.
Personalized Marketing's Role in Shaping Consumer Confidence in Privacy Security within the Sales Sector
Authors: Ma Weiran
Published: August 2024

The impact of personalized marketing strategies on consumer privacy and information security evolved in the sales industry in the era of big data has increasingly become an issue that cannot be ignored in the development process of enterprises in the sales industry. Based on the sales industry, this paper selects consumer trust and consumer participation as mediating variables to study the influence of personalized marketing strategies in the sales industry on consumer confidence in privacy information security. The results of the study show that personalized marketing strategies in the sales industry have a significant negative impact on consumer confidence in privacy information security, and a significant positive impact on the mediating variables of consumer trust and consumer participation. The study also draws a series of conclusions based on the degree of linear influence, such as that personalized marketing strategies are more difficult to win intrinsic consumer trust than behavior trust, and that intrinsic consumer trust leads to greater consumer participation than behavior trust. The paper concludes with recommendations for innovating and improving the privacy protection system, strengthening the whole process of personalized marketing and users themselves protecting the privacy of their own, as well as a prospect for future research to further improve the research system and the model.
Innovation effect of common prosperity within enterprises: empirical evidence from the panel data of Chinese A-share listed companies
Authors: Wang Jingyan
Published: August 2024

This paper discusses the impact of the internal implementation of common prosperity strategy on the innovation effect, aiming to reveal how the fair wealth distribution and opportunity sharing can promote the innovation ability of enterprises. Taking the panel data of a-share listed companies in Shanghai and Shenzhen from 2008 to 2022 as the original sample, this paper empirically tests the influence effect and action mechanism of internal common prosperity on enterprise innovation. The study found that common prosperity within enterprises can significantly increase the innovation output, that is, a significant increase in the number of patent applications. This conclusion remains under a series of robustness tests. Heterogeneity discussions found that the effect of private enterprises and labor-intensive enterprises was more influential. Further mechanism analysis shows that the common prosperity of enterprises alleviates their own financing constraints and information asymmetry degree, and then promotes the improvement of innovation output. Under the background of the in-depth development of the concept of common prosperity, this paper reveals that the common prosperity within enterprises is not only an important way to achieve social equity, but also a key factor to promote the continuous innovation and long-term success of enterprises.
Problems and Solutions in Chinese Agricultural Futures Market
Authors: Chen Boshan
Published: August 2024

Futures market is an indispensable part of the financial system, especially the agricultural products futures market. China's agricultural products futures market plays an important role in stabilizing agricultural prices, ensuring agricultural stability and national strategic resource security. This study focuses on China's agricultural products futures market, aiming to analyze its current situation, dig existing problems, and put forward targeted solutions. The study shows that China's agricultural products futures market has formed a major exchange framework after more than 30 years of development and has shown a healthy growth trend. However, China's agricultural products futures market is facing a series of challenges, such as limited market size, unreasonable participant structure, and inadequate market regulation. These problems limit the function of the market and affect the healthy development of the market. In this regard, it is suggested to promote market diversification, introduce institutional investors, and improve market rules; strengthen product innovation and marketing to expand influence; improve risk management awareness and modernize tools. These measures proposed in this study are expected to promote the comprehensive development of the agricultural products futures market and enhance its positive role in the global economy.
Comparative Analysis of Idol Industry Development: A Case Study of NINE PERCENT and Seventeen Groups
Authors: Li Mengtong
Published: August 2024

This article points out the current situation of the idol industry in China and South Korea, some basic data and future development trends, and then uses a case analysis method to compare NINE PERCENT of idol groups in China with Seventeen groups in South Korea. The paper presents the advantages and strong development momentum of China's idol industry and analyzes the specific reasons leading to the differences between the two countries' idol industries, which are, respectively, the population base, the length of the idol manufacturing process and the development direction after the debut. Finally, the article puts forward some constructive solutions, the most important is to identify the target market, that is, the Southeast Asian customer group, and then to a certain extent, diversify the idol's business scope and change the idol's operation mode, and increase the communication with fans to expand the viscosity of fans.
Strategy Selection in Extreme Markets: Empirical Analysis and Optimization of Portfolio Performance in the French Stock Market
Authors: Lin Yitong
Published: August 2024

This paper uses a two-phase methodology to explore portfolio optimization strategies for stocks in the CAC 40 index during the COVID-19 pandemic. In the first phase, this paper compared the performance of equal-weighted, maximum Sharpe ratio, and equal-weighted risk contribution (EWRC) strategies, using historical data to analyze their performance in eight different market phases. In the second phase, based on the results of the first phase, the maximum Sharpe ratio strategy was found to be the most effective, and was subsequently refined by integrating the 20-day moving average (MA20) as a tactical component. The results showed that the MA20-enhanced maximum Sharpe ratio strategy outperformed other strategies in terms of risk-adjusted return over most of the evaluated time frames. It can therefore see the potential of technical indicators to aid investment decisions, especially in response to rapid market changes. These insights provide valuable guidance for investors strategizing during periods of market uncertainty, highlighting the benefits of dynamic strategy adjustments to volatile market conditions.
Research on Light Pollution Based on Comprehensive Evaluation Model
Authors: Lu Nan , Wang Tianqi , Zhang Zongkai
Published: August 2024

With the rapid development of technology and economy, the place where live has become more shining and prosperous. But while can enjoy a more technological and modern living environment, it has also caused a lot of light pollution problems. Light pollution is not only harmful to human physiology and psychology, but also destroys the balance of the ecological environment. Therefore, the determination of light pollution risk levels and the development of intervention strategies for light pollution have received our attention. First, the paper screened out 12 indicators from five categories of light pollution indicators as factors affecting the light pollution level by hierarchical analysis, and derived the comprehensive weights of each indicator with the help of entropy weighting method and hierarchical analysis method and combined with related literature. Finally, the scores of the research subjects were calculated and ranked by the Topsis method, which was used as a measure to judge the degree of light pollution in an area. In applying the metric to four different types of locations, adjustments were made in the data of the environmental brightness index, and subsequently the scores of the four locations were obtained along the lines of Model 1.
Problem Solving and Investment Suggestions of China’s REITs Development
Authors: Liu Fengyu
Published: August 2024

The real estate industry has an important position in the national economy. In recent years, with the increasing growth of the real estate economy, the real estate financing model, which is mainly based on traditional bank loans, has started to gradually accept REITs (Real Estate Investment Trusts), and REITs have begun to develop in the Chinese market. This paper analyses the current situation, history, investment targets, and structure of China's REITs market in the context of both risks and opportunities, combines the performance of the market with the problems and solutions arising from the development of REITs, and provides constructive investment advice to investors. This paper indicates that although the scale of China's REITs market is relatively small and the product structure still needs to be optimized, with the continuous growth of China's economy, the increase of policy support, and the continuous improvement of the market system, there exists a huge development potential and investment value in China's REITs market.
Enhanced Feynman-Kac Formula for Nonlinear Uncertainty Quantification Problems
Authors: Xu He , Li Xueting , Cai Wendi
Published: August 2024

Uncertainty qualification (UQ) issues and partial differential equations (PDEs) are becoming hot topics in the fields of physic and engineering. There are a various number of strategies for handling unknown linear PDEs, including Monte Carlo and the polynomial regression approach. Nevertheless, nonlinear issues could not be effectively solved using existing approach. This paper focuses primarily on a novel method, an enhanced Feynman-Kac formula with a Least Squares Monte Carlo approach. Numerical experiments were conducted in our research to verify its efficacy and convergence. This paper discovers that the enhanced approach exhibits strong performance regarding nonlinear PDE and UQ scenarios with high accuracy and strong performance of convergence. In the future, this technique might be efficiently applied in the fields of engineering and finance in real-world scenarios.
Adaptive Neural Network Architectures for Cross-Domain Generalization
Authors: Friedman David , Sadler John , Churchill Tomas
Published: August 2024

Cross-domain generalization remains a critical challenge in the field of machine learning. Traditional models often struggle to maintain performance when applied to new, unseen domains due to the variations in data distribution, known as domain shift. This paper proposes adaptive neural network architectures that dynamically adjust their structure based on the domain of the input data. Our approach leverages dynamic routing, attention mechanisms, and modular neural networks to enhance the model's adaptability and robustness. The dynamic routing mechanism enables the network to select different paths for different inputs, allowing it to adapt its processing dynamically. Attention mechanisms help the model focus on the most relevant parts of the input data, enhancing its ability to generalize across domains. Modular neural networks consist of multiple independent modules that can be selectively activated or deactivated based on the input domain. We also develop a dynamic adaptation mechanism that adjusts the network structure in real-time based on domain-specific input features. Experimental results on multiple benchmark datasets, including NEU-CLS and Lithium Electronic Surface Defect Classification (IESDC) datasets, demonstrate the effectiveness of our method. The proposed approach shows significant improvements in cross-domain performance compared to state-of-the-art models, achieving higher accuracy and robustness. Ablation studies confirm the contribution of each component to the overall performance enhancement. The findings highlight the potential of adaptive architectures in addressing the challenges of domain shift in machine learning applications.
Research on Submersible Safety Operations Based on the Basic Information 3D Motion Trajectory and Entropy Weight Method Models
Authors: Li Guanlin , Deng Derong
Published: August 2024

This research outlines a strategy to enhance ocean exploration safety, using the Ionian Sea as a case study, by integrating theoretical and practical methods. It develops a comprehensive model that predicts submersible locations, optimizes search operations, and manages multiple units simultaneously, ensuring efficient and safe underwater tours in various challenging marine environments. The model simulates the submersible's trajectory using a three-dimensional Cartesian coordinate system, accounting for propulsion power, communication status, and environmental factors such as time-variant ocean currents, position, velocity, temperature, and density. Outputs include a 3D motion trajectory char, providing visual representations of the submersible's path. Additionally, the model addresses the selection and evaluation of search and rescue equipment using the Entropy Weight Method, which calculates the weights of evaluation indicators leading to a Continuous Variable Model that enhances decision-making. This aids in choosing the optimal combination of equipment based on cost, reliability, efficiency, and service life, maximizing search efficiency within a budget.
Dynamic Network Modeling of Optimal Water Level Control Based on RMOBM and DMOWN
Authors: Li Yuke , Chen Keyu , Zhao Zhuojun
Published: August 2024

In this paper, the optimal water level of the Great Lakes and their connected waterways in North America is studied by using the multi-objective bargaining model based on water level risk (RMOBM model) and the dynamic multi-objective basin network (DMOWN model). First of all, we established the RMOBM model, taking into account the influence of rainfall, snowfall, evaporation of lake water and surface leakage on water level, and carried out multiple rounds of bargaining with the objective function of maximizing economic benefits and minimizing the probability of flood occurrence, and obtained the optimal water level results by using MATLAB software. Secondly, based on the RMOBM model and the maximum flow target value, we considered the flow regulation effect of Moses-Sanders Dam project and Cornwall County in the DMOWN model, obtained the maximum flow value through the Ford-Fulkerson algorithm, and then output the optimal lateral flow results of five major water level nodes. These studies provide a scientific basis for the management of North America's Great Lakes and their associated waterways and help develop effective planning and management strategies.
The Impact of Industrial Agglomeration on Urban Economic Development in the Context of Digital Economy
Authors: Gao Shan
Published: August 2024

Digital economy is the main economic form after agricultural economy and industrial economy, and is the core element of national strategic guidance. As a bridge connecting the development and application of digital economy, emerging technologies are closely related to the optimization and upgrading of industrial structure. In the new era, it is of practical significance to seize new opportunities for digital development, expand new space for economic development, promote industrial agglomeration construction with digital empowerment, and create high-quality and high-end industrial clusters. This paper analyzes the effects of emerging technologies on different industrial agglomeration in the digital economy, and then studies the impact of industrial agglomeration on urban economic development under digital empowerment from the aspects of economic resilience, industrial competitiveness, and green innovation. Through the comparative analysis of literature, it is concluded that digital economy positively promotes urban economic development through industrial agglomeration. At the same time, this paper also analyzes the negative externalities of the digital economy and puts forward corresponding policy recommendations.
Performance Evaluation and Analysis in Tennis: A Case Study of Wimbledon 2023 Final
Authors: Wang Yilei , Zhang Chengyu , Zhang Chengyu , Yiming Gulinisha , Yu Yening
Published: August 2024

This study employs comprehensive performance evaluation techniques to analyze the Wimbledon 2023 final match between Carlos Alcaraz and Novak Djokovic. Data preprocessing involves categorizing evaluation metrics into two categories and applying normalization methods. This paper describes the fuzzy comprehensive evaluation model to transform qualitative evaluation into quantitative evaluation for comprehensive evaluation. The entropy weight method determines the index weight to increase the credibility of the model. Wavelet analysis is used for signal denoising and performance comparison. Results show variations in player performance over time, highlighting factors influencing match outcomes.
Submersible Position Prediction Model Based on HMM and Six Degrees of Freedom Motion
Authors: Yuan Shaobo , Chen Jiaxu
Published: August 2024

The mysterious deep sea has an unrivalled attraction for scientists worldwide, and the use of submersibles provides us with a clearer view of the seafloor and helps us gather information more safely. We must monitor the position information of the submersible in real time to ensure the safety of both the diver and the submersible. In this paper, we use the six-degree-of-freedom motion model and HMM to predict the motion state of the submersible, propose to replace the complex numerical simulation process of seawater motion with a stochastic process and estimate the parameter of the HMM by using the Baum-Welch algorithm. After the data analysis, the paper verified the model's applicability in the sea area and predicted the motion position of submersibles very well as the position prediction model of submersibles in the complex oceanic situation affected. Combined with the previous research results on the motion of the submersible, this paper provides some references for the research of the submersible motion prediction model.
Reform and Innovation of Higher Education Management Models in the New Era
Authors: Zhu Lu
Published: August 2024

In the context of the new era, the rapid development of technology and profound changes in social structures have rendered traditional higher education models inadequate for contemporary societal needs. Traditional education models, constrained by inherent thinking patterns, are relatively rigid, which not only limits further development of universities but also affects students' personal growth and employment competitiveness. Therefore, university administrators and related staff must keep pace with the times, aligning with market demands for talent by focusing on cultivating students' innovation capabilities and comprehensive skills. Simultaneously, improving educational quality should be a key aspect of innovating education management models, upholding the principle of fair education to achieve sustainable development, and providing strong support for future educational reforms. This paper first analyzes the importance of reforming and innovating higher education management models, identifies problems with previous management models, and proposes targeted innovation strategies to meet the needs of continuous development in the current era.
Evaluating the Role of GDP Per Capita in Shaping Internal Migration Patterns in China: A Spatial Econometric and Regression Analysis Approach
Authors: Ke Heming
Published: August 2024

This article demonstrates the links between immigration and the economy in China. It aims to uncover the complex interdependencies between GDPs per capita, education, and healthcare. Therefore, it is important to inform public discourse, develop evidence-based policies, and contribute to a more complete understanding of the impact of immigration on the economy. To complete this essay, Firstly, I surfed on some research programmes such as Jstor and Google Scholar; I found some essays about immigration trends in China in the dimension of provinces. In the main body of the research, I utilized some bar graphs and statistical strategies to demonstrate the relationship between the economic factors influencing the immigration trend, whether it is positive or negative. firstly, the graphs are used to illustrate the significant GDP difference between the top provinces and the ones that are poor in GDP per per capita. In the following graphs, I used the regression analysis to indicate the relationship between GDPs per capita and internal immigration (capital per inflow into provinces in a year).
An Exploration of Momentum Changes in Tennis Players Based on CART Decision Regression Trees
Authors: Huang Junjie , Li Qiwei , Luo Lisha
Published: August 2024

As the sport of tennis is booming, the study of players' technical and tactical level and game status is becoming more and more important. For this reason, for the sake of the research of imposing changes. First of all, from the six tennis technical and tactical evaluation indexes of scoring change, error change, serve-receive scoring change, technical change, momentum change, and streak change, this paper derives the four characteristic indexes that are most relevant to the target variables, i.e., serve-receive scoring change, technical change, scoring change and streak change, through the CART algorithm. Among them, the correlation between the change in serve-receive score and the change in momentum was the greatest. Then, a decision regression tree model based on the CART algorithm was established. Then the appropriate decision tree model parameters were obtained after 10 rounds of data validation by the 10-fold cross-validation method. Among them, the depth is 5 and the minimum number of leaf nodes is 20. Meanwhile, to prevent the model from overfitting, this paper carries out a pre-pruning operation on the decision tree model. That is, estimation is performed before each node division, and if the division of the current node cannot bring the decision tree generalization performance improvement, the division is stopped and the current node is labeled as a leaf node to improve the applicability of the model. Finally, through the mean square error (MSE) and coefficient of determination (R-squared) test, it is found that the mean square error (MSE) is very close to 0, and the coefficient of determination R-squared is very close to 1, which indicates that the model has good prediction effect.
Walmart Sales Prediction Using Multiple Linear Regression
Authors: Lin Anting
Published: August 2024

The sales of Walmart are often considered to be related to many factors, and indeed this is the case. This study aims to examine the impact of objectively observable independent variables on Walmart's weekly sales. The paper employs the Z-score standardization technique to normalize the dimensions and utilizes linear regression analysis to process data from 6,435 weekly sales records of Walmart. The model is derived after preprocessing and standardizing the data in this paper. The findings reveal that most variables have either a minor or significant effect on sales. Notably, temperature and Fuel Price exert a certain influence on sales, while Holiday, Consumer Price Index (CPI), and Unemployment rates have a substantial impact. This investigation into the objective factors affecting Walmart's sales will benefit the management by providing insights to refine strategic planning through environmental surveys, thereby aiding in the enhancement of the shopping atmosphere and customer experience, ultimately aiming to boost sales revenues.
Research on the Problems of the A-share Market in China and Analysis of Countermeasures
Authors: Zhang Xueyang
Published: August 2024

The Chinese A-share market experienced considerable turbulence from late 2023 to early 2024, exerting substantial adverse effects on its stability and investor confidence. In response to this phenomenon, this paper conducts a comprehensive review of the developmental trajectory of the Chinese A-share market. It seeks to elucidate the multifaceted reasons contributing to the pronounced market volatility and instability during the specified period. Specifically, the study investigates issues such as information asymmetry, deficiencies in market exit mechanisms, and the composition of investor structure. By critically analyzing these factors, the paper aims to shed light on the root causes of the observed market fluctuations and propose viable solutions. The proposed remedies encompass enhancing transparency in market information dissemination, refining market exit mechanisms to ensure efficient market functioning, and addressing structural issues in the investor base. Through its rigorous analysis and evidence-based recommendations, this study provides valuable insights for policymakers, regulators, and market participants seeking to address the intrinsic challenges facing the Chinese A-share market and foster its long-term stability and resilience.
Integrating Blockchain and Deep Reinforcement Learning for Secure and Efficient Supply Chain Management in Tertiary Institutions
Authors: Welt Jasper , Zhang Yu
Published: August 2024

The rapid adoption of blockchain technology has led to its increasing use in various domains, including supply chain management. However, the integration of blockchain into supply chain systems poses challenges related to security, efficiency, and regulatory compliance. This paper presents an analysis of a blockchain architecture for file sharing and management in tertiary institutions. The proposed framework combines the Soft Actor-Critic (SAC) deep reinforcement learning algorithm with prioritized experience replay for inventory optimization and a blockchain-based zero-trust mechanism for secure supply chain management. The SAC algorithm learns adaptive policies under demand uncertainty, while the blockchain architecture ensures secure, transparent, and traceable record-keeping and automated execution of supply chain transactions. An experiment using real-world supply chain data demonstrated the superior performance of the proposed framework in terms of reward maximization, inventory stability, and security metrics. The paper also discusses the evidentiary significance of blockchain records and the procedural implications of integrating this technology into the U.S. judicial system. The framework offers a promising solution for addressing the challenges of modern supply chains by leveraging blockchain, deep reinforcement learning, and zero-trust security principles.
Market Reaction to Enterprise's Equity Carve-out Listing on the STAR Market - A Case Study of Tianneng Power
Authors: Wang Zenan
Published: August 2024

Since the 1980s, numerous European and American companies have opted for a capital operation strategy involving carve-out and listing to facilitate healthy development and concentrate on their core businesses. In China, however, carve-out listings only commenced relatively recently, and the development process has been somewhat slower than in other countries. In response to the growing sophistication of China's capital market, the China Securities Regulatory Commission (CSRC) introduced a set of regulations governing the carve-out of subsidiaries of listed companies on the domestic A-share market in 2019. Since the inception of the A-share market and the issuance of the relevant rules, many eligible listed companies have announced their intention to undertake a carve-out listing. This has been particularly prevalent among technology and manufacturing companies. Consequently, carve-out listings on the STAR Market may emerge as a novel focal point for investment in China's capital market. As a pioneering enterprise in China's new energy power battery industry and a listed company on the H-share market, Tianneng Power's approach and trajectory towards carving out its subsidiary Tianneng Battery and listing it on the STAR Market serve as a paragon for other enterprises in the industry. This article examines the specific motivations of Tianneng Power to carve out its subsidiary and list it on the STAR Market. The event study method was employed to analyse the short-term market reaction of the listed company within 10 trading days before and after the issuance of the first carve-out announcement. The results indicate that the market responded favourably on the day of the event, with the stock market and investors displaying a positive attitude towards Tianneng Power's carve-out behaviour.
Research on Concentrated Solar Thermal Power Efficiency Based on Solar Elevation
Authors: Wang Xiaomo
Published: August 2024

This paper explores the impact of solar elevation on the reflective efficiency of heliostats in solar thermal power systems. By assuming heliostats as ideal mirrors and using detailed mathematical models, it calculates the cosine efficiency, shadow obstruction, and truncation efficiencies across different months. The study reveals how variations in solar elevation angles throughout the year affect the optimal tilt of heliostats, significantly impacting their efficiency. It also addresses the mutual shading and shadows cast by the absorber tower, proposing a model to estimate the obstructed area when heliostats are positioned vertically. The results highlight the necessity for precise positioning of heliostats to maximize solar capture and minimize losses, providing crucial insights for optimizing the layout of solar heliostat fields to enhance overall energy production and field efficiency. This research underscores the importance of strategic planning in the design of solar thermal power systems to adapt to seasonal changes in solar elevation.
Research Progress of Urban Ecological Evaluation Methods Based on Remote Sensing Indexes
Authors: Wu Yikai
Published: August 2024

Urbanization and the ecological environment have a long-standing, mutually constraining relationship. A healthy ecological environment is the natural basis for human society's survival and an important indicator of urbanization. Therefore, an accurate assessment of urban ecology is of vital significance. Remote sensing technology has natural advantages over traditional urban ecological quality assessment methods, such as high efficiency, timeliness, and comprehensive coverage. This paper aims to introduce the application of remote sensing technology in urban ecological evaluation, focusing on both single and comprehensive indices. The method for processing remote sensing indices involves combining captured electromagnetic waves with specific bands to form remote sensing indices. These indices are then analyzed to evaluate urban ecological conditions, including monitoring urban vegetation and evaluating urban development. The research trend of optimizing data sources and improving index construction is also discussed. This paper demonstrates the feasibility of using processing method of remote sensing index for urban ecological evaluation. It provides decision makers with valuable information and offers technical support for promoting sustainable urban development.
The Application and Performance of Momentum Strategy in A-shares and U.S. Stocks
Authors: Mai Yuhuan
Published: August 2024

Momentum strategy, a widely accepted approach in the investment field, is the focus of this study. This paper selected the constituent stocks of the Shanghai and Shenzhen 300 Index and the S&P 500 Index as representatives of their respective stock markets. The study found that the cross-sectional factor momentum strategy performs poorly in the A-share market, while it exhibits better performance in the U.S. stock market. This study summarized the potential reasons for the observed results, such as the different trading rules, the U.S. stock market operates on T+0, while the A-share market operates on T+1. This indicates that the factor momentum strategy can be better implemented in the U.S. stock market, and also reveals the necessity and importance for investors to choose different strategies in two different stock markets. This research can provide beneficial references for investors to make more informed investment decisions in different market environments and achieve a better return.
The Mystery Hidden in the Sex Ratio
Authors: Che Songtao
Published: August 2024

In order to unravel the secrets hidden within the gender ratio of lampreys, we proposed several models to simulate the cascade of effects on ecosystems. Firstly, we established a Logistic model-based food chain model. We found that as the gender ratio increases, the predator population rises while environmental resource levels decline, and the lamprey population initially increases before decreasing. Simultaneously, habitat utilization rate was considered as an indicator affecting the ecosystem. Through modeling, we discovered a positive correlation between habitat utilization rate and the gender ratio of lampreys. Secondly, we developed a Game Evolution Model based on the Moran process. We defined a payoff matrix to simulate competition between male and female lampreys. We assumed that gender ratio and environmental resource levels influence reproductive success, finding that an intermediate gender ratio results in higher reproductive success, considered an advantage. When the gender ratio approaches 0 or 1, reproductive success decreases, considered a disadvantage. We also defined a function for resource utilization rate concerning gender ratio, concluding that higher gender ratios lead to higher resource utilization rates.Thirdly, we defined an ecosystem evolution model based on the Logistic model. Three interaction modes between organisms and lampreys were established: competition, independent coexistence, and parasitism. We discovered that when the gender ratio approaches 0.64, the stability of the ecosystem is highest.Through entropy weight method, we determined the weights of each factor, and observed the stability of the comprehensive index at different gender ratios, finding that a gender ratio closer to 0.64 corresponds to a more stable ecosystem. Finally, utilizing the previously established game evolution model, we introduced parasites. In this model, by reducing the punishment for parasites choosing betrayal and increasing the probability of parasites choosing betrayal. Ultimately, we found that deviating from a gender ratio of 0.64 provides an advantage for parasites.
Research On Copyright Ownership of Products Using Artificial Intelligence
Authors: An Yue
Published: August 2024

Artificial intelligence technology is booming in the digital economy era. In view of the legal attributes of the subject and object of artificial intelligence, there have been many controversies in the theoretical and academic circles. For example, some scholars advocate that products involving artificial intelligence ought to be covered under copyright from the standpoint of "objectivism". However, some scholars think that copyright protection should not be given to them from the perspective of "subjectivism". The copyright ownership of artificial intelligence products is currently debated in three mainstream theories: "producer theory", "creator theory" and "user theory". In fact, the "user theory" is more reasonable from three aspects: the composition characteristics of works, the social significance of legal protection and the principle of unity of rights and obligations. Therefore, at the institutional level, we should try to clarify the status of artificial intelligence products and the copyright subject of artificial intelligence products is artificial intelligence users, in order to achieve legal protection, an artificial intelligence declaration system must be established.
Analysis of Real Estate Impact on Credit Risk for Financial Institutions
Authors: Liu Qihan
Published: August 2024

As a matter of fact, the real estate market plays a pivotal role in China's economy, directly affecting the credit risk of financial institutions. As the economy has rapidly developed, the real estate sector has become a cornerstone, significantly contributing to the Gross Domestic Product (GDP), which plays a core role in evaluating the economy. However, the rapid fluctuations in the market pose serious credit risks to financial institutions, highlighting the need for a comprehensive understanding of how these fluctuations impact borrowers' repayment capacities, collateral values, and financial institutions' lending decisions. On this basis, this research focuses on the intricate relationship between the dynamics of the real estate market and the credit risk faced by financial institutions. According to the analysis, the specific effects of real estate of China on credit risk for financial institutions are evaluated. Overall, these results shed light on guiding further exploration of various dimensions and factors that shape this relationship.
A Study on the Impact of High-Quality Education Resources on Urban Housing Prices: An Empirical Study Based on the DID Model
Authors: He Mengyang
Published: August 2024

In the actual operation of high school enrollment in China, house purchase and household registration transfer have become the strategies that many families must adopt to obtain high-quality education resources. Due to the urgent need for housing in these families, it has undoubtedly had a significant impact on the urban housing prices. To further study this phenomenon, this paper selected three cities with outstanding education quality in Hubei Province, and adopted the difference-in-differences (DID) model to analyze how the housing price of these cities was affected by high-quality education resources before and after the reform of the high school enrollment system. The research results show that the reform policies have indeed promoted the change of urban housing prices, providing empirical support for the premium phenomenon of "school district housing". This research proposal aims to promote the equitable distribution of educational resources to mitigate the societal impact of this phenomenon. This study not only reveals the impact of high-quality educational resources on urban housing prices, but also makes feasible suggestions to promote the achievement of educational equity. This is of great significance to the healthy development of China's education and the sustainable development of cities.
Investment Analysis of BYD’s Value in the New Energy Sector
Authors: Deng Jianuo
Published: August 2024

This investment value analysis focuses on BYD, a pivotal player in the new energy sector, amidst the global challenges posed by climate change and the pressing need for carbon emission peak and neutrality. The study examines BYD’s strategic position within the context of China's "two-carbon" strategy, which aims for a comprehensive green transition, influencing economic, social, and technological facets to steer towards a sustainable, low-carbon global future. The research assesses BYD’s innovative contributions to carbon neutrality through advancements in new energy vehicles, battery technology, and renewable energy solutions, emphasizing the company's commitment to reducing transportation emissions and enhancing energy efficiency. The analysis provides a comprehensive review of BYD’s financial health, including solvency, profitability, and the challenges it faces, such as dependence on government subsidies and the battery technology barrier. The study's objective is to furnish investors with detailed insights to facilitate informed decision-making and to stimulate further interest in the sustainable development of the new energy industry. The findings suggest that despite current profitability concerns, BYD’s long-term development strategy and market optimism indicate significant potential for future profit growth. The study anticipates that BYD will play a more substantial role in the new energy vehicle market, contributing to sustainable long-term growth, as the global emphasis on low-carbon environmental protection intensifies.
Optimization Model of Remanufacturing Reverse Logistics Network Based on the Impact of Green Environment Protection and Carbon Tax
Authors: Tian Fu
Published: August 2024

With economic development, human development of resources intensifies, leading to natural resource tension and environmental problems. As an important part of the remanufacturing industry, the reverse logistics network has a significant impact on helping enterprises reduce the cost of each transportation link and reduce energy loss. This paper proposes a mixed-integer linear programming model based on the optimization of the existing remanufacturing reverse logistics network, with the aim of minimizing the sum of the investment in remanufacturing logistics sites, operating costs, and transportation costs in each link.
The Role of Social Policies in The Development of Electronic Games in The Field of Public Opinion
Authors: Huang Xin
Published: August 2024

With the development of video game, the status of video game in society has been rising. On the one hand, the value of video game does contribute to the development of society, but on the other hand, there have been many problems with the development of game like the impact of violent games on teens and Gaming addiction. According to the "Statistical Report on the Development of the Internet in China", as of December 2018, the number of people addicted to games in China has reached 27.5%. Therefore, how to develop game has become a topic of great concern for the government and game makers. This study tries to find the relationship between social policy and video game development in the field of public opinion through the case study method. Provide policy theoretical support for how to develop video game. The study found that social policy does work in video game development in the field of public opinion by changing people’s perception of video game.
The Analysis of Counter Urbanization in Yichun, Heilongjiang
Authors: Zhan Ruiqi
Published: August 2024

The level of urbanization has become one of the measurements of the comprehensive strength of a country. While China is on the road to urbanization, the opposite process is taking place in Northeast China, abolishing some sub-districts and establishing towns. This paper focuses on Yichun, a city in Northeast China, to analyze the reasons and effects of the policy based on the Yichun Government Statistical Bulletin. The counter urbanization happening in Yichun is caused by population loss and economic decline due to over-dependence on forestry resources. Recommendations for the further development policy are provided at the end. Current research focuses on the urbanization process and the type of urbanization in Northeast China. There is not much research on the counter urbanization policy set in Northeast China.
Environmental Policy Changes Over Time – A Comparative Analysis
Authors: Ren Yuanchun
Published: August 2024

Through this paper, the historical evolution of the environmental policy in New York State has been discussed, to bring to light the general environmental policy orientation and progress of the state. The strategy emphasizes the analysis of representative regions and countries (such as China and Germany), and identifies the best policies and innovative practices that are suitable for New York State policymaking through the comparative study. This research carefully defines the past and current complexities of the state policy regarding the environment, and points out the efficacy of the main legislation, such as the Environmental Conservation Law (ECL), and the role of significant historical events of the U.S. and the world like the Deepwater Horizon oil spill and Superstorm Sandy. The scoping review method extracts a wide set of guidance and thought experiments that reveal underlying strategies suitable for adoption for sustainable development and conservation actions in New York State, such as sustainable development projects, protected areas policies, renewable energy laws, and environmental justice considerations. To sum up, this paper tries to clarify the multifaceted challenges of the environmental policy in New York State, and also provides a complete analysis of its historical context, modern standards, and innovative solutions needed to make a benevolent and sustainable environment in New York State.