bluuebunny/crossref_metadata_2025 huggingface dataset:
Current Situation, Problems and Countermeasures of the Spirits Sector in the Chinese A Share Market
Authors: Li Chenghao
Published: August 2024

As one of the core sectors of the A-share market, the Chinese spirits sector receives continuous attention since the establishment. In 2023, the Chinese spirits market is becoming increasingly competitive than ever before. In addition, the declining purchasing power level of consumers has led to the inventory of producers and distributors reaching historic high, and a series of problems have led to a significant decline in the sector in the A-share market in 2023. This study shows that there are some problems in the sector, such as different speed of recovery rhythms, stock prices rise and fall rapidly and continuous decline trend, and large trading differences. Therefore, this study puts forward the suggestions of building the company's own characteristics, strengthening the government regulation, optimizing the market strategy, and improving the product and marketing system. This study is of great significance for the sustainable development of sector in China's A-share market.
Research on Automatic Pricing and Replenishment Decisions for Vegetable Commodities Based on Pearson Correlation Analysis and VAR Model
Authors: Chen Jiahe , He Jingwei , Mao Qiyu
Published: August 2024

This paper investigates the automatic pricing and replenishment decisions for vegetable commodities based on Pearson correlation analysis and the Vector Autoregression (VAR) model. By analyzing vegetable sales data, box plots and histograms reveal the sales volume distribution patterns of different categories and individual vegetable products, and Pearson correlation analysis uncovers the intrinsic relationships among them. A VAR model is further constructed to forecast the sales volume and pricing of vegetables, combined with the cost-plus pricing strategy from economic principles to determine the replenishment volume and pricing strategy that maximizes profits. The study demonstrates that the model can effectively guide supermarkets in achieving optimal pricing and replenishment for vegetable products, enhancing the economic benefits.
A Study on the Forms of Trademark Infringement and Prevention in China's Cross-border E-commerce Industry
Authors: Li Zeran
Published: August 2024

This study investigates the prevalent issue of trademark infringement within China's burgeoning cross-border e-commerce sector, examining its forms, underlying causes, and proposing targeted prevention strategies. Amidst the sector's rapid expansion and its critical role in global market integration, trademark infringement emerges as a significant challenge, jeopardizing business integrity and economic growth. Through comparative analysis of international and domestic legal frameworks, alongside a review of infringement cases, this research delineates the primary infringement modalities—trademark squatting and counterfeiting. It emphasizes the need for a multi-faceted approach involving legal reforms, enhanced judicial protection, and proactive risk prevention measures. The findings underscore the critical importance of adapting China's intellectual property laws to the dynamic global e-commerce landscape and fostering a robust trademark protection ecosystem to safeguard and stimulate the country's economic globalization ambitions.
Research on the Ways to Win in a Simple Poker Game
Authors: Xu Anqi
Published: August 2024

Poker is a popular card game as well as the foundation of a number of types of gambling. Since the variability of playing poker is high as a typical intellectual game, and the uncertainty and complexity is significant during the game, ways to win in poker games have always been widely discussed about. The aim of this essay is to use probabilities and statistics to calculate the probability that a player wins in a one-to-one poker game, and analyze the data. Then use methods such as combination and classification discussion to calculate the probability for a player to win as well as testifying the validity of the probability acquired by using different categories of experiments.  Eventually, use the Kelly formula to calculate the percentage of the player's total chips that should be raised, hence to give an instruction to the player to make reasonable decisions during the game in order to maximize the profit. It can also provide methods to solving more complicated poker games and enhance the poker skills.
An In-depth Analysis of Tesla's Growth Deceleration in China's Booming New Energy Vehicle Market: Challenges and Strategic Implications
Authors: Chai Ruiqi
Published: August 2024

As environmental pollution continues to deepen, people's awareness of environmental protection continues to strengthen, and the penetration rate of new energy vehicles has greatly deepened. Tesla, as a representative of new energy vehicles, plays an important role in the global market. However, in recent years, Tesla's development speed in the Chinese market has gradually slowed down. This paper mainly provides experience and reference for the development of new energy vehicles in China by analyzing the reasons for the decline of Tesla's development speed in China.
Research on the Environmental Risks of China's Overseas Investment under the Background of "Belt and Road"
Authors: Guo Tianyu
Published: August 2024

The ambitious "Belt and Road" initiative has ushered in a new era of global connectivity and economic integration, presenting unprecedented opportunities for Chinese enterprises to expand their overseas investments. However, this rapid expansion has been accompanied by heightened environmental challenges, necessitating a reevaluation of environmental protection strategies to ensure sustainable development. As China's investment footprint widens across diverse ecological and regulatory landscapes, the environmental implications of these ventures have come under intense scrutiny. To achieve the sustainable development of "Belt and Road", this paper analyses the multifaceted environmental risks associated with Chinese overseas investments under the "Belt and Road" framework, identifying key areas where current practices fall short in safeguarding ecological integrity. Through a comprehensive analysis, it highlights the critical need for robust legal frameworks and enhanced corporate environmental governance to mitigate these risks effectively. The study proposes a set of targeted legal strategies and policy recommendations designed to fortify environmental protection measures in Chinese outbound investments. These include the development of specific environmental legislation, the integration of sustainable practices into investment planning, and the strengthening of international cooperation on environmental issues. By addressing the dual objectives of economic growth and environmental sustainability, this paper aims to contribute valuable insights towards achieving a greener "Belt and Road" initiative, offering a roadmap for Chinese enterprises to navigate the complexities of responsible global investment.
The Future of Chinese Variable Interest Entity Structure: Do Recent Policies Have Positive or Negative Effects on It?
Authors: Wu Youli
Published: August 2024

Variable interest entity (VIE) is a solution to China's tight foreign investment policy. At the beginning of reform and open-up in China, the VIE structure brought domestic companies opportunities to have more financial support, and it made investing in Chinese companies an easy thing for U.S. investors. However, both the domestic company and U.S. investors have taken risks with the VIE structure. Recently U.S. and China introduced some policies to deal with the problems. Those policies might threaten the VIE structure’s survival but also provide other safer and more efficient options to Chinese companies and U.S. investors.
Automatic Pricing and Replenishment Decision for Vegetable Products Based on Multiple Linear Regression
Authors: Yu Yongyue , Du Qingkun , Zhang Xiaochen
Published: August 2024

Combining supply-side and demand-side planning with reliable market demand analysis to develop reasonable replenishment decisions and pricing decisions is a challenge for fresh food superstores. In this paper, a model is built based on the sales data of vegetable items to optimize the original sales strategy and develop a sales plan with the maximum gain. Firstly, the original data is pre-integrated to obtain the daily sales volume of each vegetable item, and then the data is analyzed with descriptive statistics. Spearman correlation analysis is performed on the integrated data to make the correlation between each vegetable category. Pre-integrate the data to obtain the average daily selling price, total sales volume, and average cost price of each category of vegetable commodities, and then carry out multiple linear regression to determine the pricing law of each category of vegetable commodities, respectively, and the multiple linear regression equation is the relationship between the total sales volume and the cost-plus pricing. The total sales volume and cost data of the six categories of vegetable commodities are analyzed by ARIMA time series analysis to predict the total sales volume and category cost for the next seven days, which is substituted into the multiple linear regression equation to find the predicted selling price of the vegetable commodities and calculate the profit. Calculate to find the sales price of six types of vegetable goods for the next seven days. Establish an optimization model with the goal of maximizing profit and determine the replenishment strategy for the coming week by considering the daily loss rate of different categories. Based on the optimization model by expanding the constraints to develop a more detailed decision-making scheme. Finally, based on the purpose of improving the replenishment and pricing strategy of vegetable products and trying to meet the market demand to maximize the profit of the supermarket, we provide optimization advice for the data collection of the supermarket from multiple angles, determine more accurate replenishment quantity, cost price and selling price of individual products for the supermarket, and maximize the profit margin of the supermarket, as well as explaining the reasonableness of the data collection for each type of data.
The Impact of High-Speed Rail Construction on China’s Provincial Industrial Structure
Authors: Liu Minghao
Published: August 2024

Against the backdrop of accelerated globalization and regional economic integration, the rapid development of China's rapid rail transportation system signifies the critical role of modern transportation networks in driving economic growth and adjusting industrial structures. Particularly in Eastern China, high-speed rail not only reduces the distance between cities but also potentially has a profound impact on the transformation of manufacturing facilities in the provinces along its routes. To address this issue, the present research utilizes the Difference-in-Differences (DID) analysis technique, with an emphasis on evaluating the impacts resulting from the development of high-speed railway infrastructure from 2008 onwards on the industrial structure of these provinces, especially in relation to changes in the ratios between industry and services, and resource distribution patterns among capital and labor. By comparing provinces that inaugurated high-speed rail services in 2008 (treatment group) with those that did not have such services between 2009 and 2011 (control group), this research aims to deeply understand the contribution of high-speed rail to the advancement of industrial modernization and economic model transformation in Eastern China. To narrow down the focus of this investigation and make it more precise and informative, the researchers decided to limit it to the East of China, taking into account the fact that there are specific features in the Western region as well.
Evaluation of Geological Hazard Susceptibility in Huixian City Based on AHP-IV
Authors: Qin Maoqin
Published: August 2024

This study presents a systematic evaluation of geohazard vulnerability in Huixian City, employing an informative model based on gully units integrated with hierarchical analysis (AHP-IV) to more accurately depict the geomorphic characteristics of geohazards. Utilizing ArcGIS and SPSS software, this study identified nine key evaluation indices: slope, Melton ratio, gully density, hazard point density, degree of undulation, rock group, normalized vegetation index (NDVI), soil erosion potential index (SPI), and multi-year average rainfall, facilitating a comprehensive assessment of geohazard vulnerability. Results showed that 36.13% of the study area was covered by zones with very high and high susceptibility., exhibiting concentrated geohazard development, while low susceptibility zones harbored fewer geohazard sites, consistent with actual distribution patterns. To validate the assessment results, this paper employed the frequency ratio model and ROC curve analysis. The frequency ratio demonstrated an increasing trend with escalating risk levels, with the very high susceptibility zone exhibiting significantly higher frequency ratios compared to the low susceptibility zone. Furthermore, the evaluation model achieved an AUC value of 0.871, indicative of its high precision and reliability, thus offering robust insights for geological hazard monitoring and early warning systems in Huixian City. This study not only enhances the practicality and guidance of geological hazard assessment but also furnishes a critical scientific foundation for geological hazard prevention and control efforts.
Analysis of Principles and Applications of Chaos Theory
Authors: He Jiarong
Published: August 2024

As early as Aristotle’s period, people were trying to find rules to define nature. Centuries later, there came Newton’s Laws of Motion, it was ‘omnipotent’ in explaining everything under gravitation, up to early twentieth century. Then, Einstein proposed theory of special relativity (responsible for everything else without gravitation), and general relativity (generalizing gravitation and special relativity). Nevertheless, along with order there is chaos. Chaos theory was not explicitly realized until late in the twentieth centuries, and that was when people realized that chaos is also capable of explaining the world. Computers are good with handling large data calculations, which the development of chaos theory benefits from. This study discusses some fundamental ideas of chaos theory, and focus on how they can be used to predict near futures in complex systems such as weather forecasting, stock markets, and transport systems. According to the analysis, there are also limitations, which again relates to computing technologies. However, the future is bright as advanced technologies await in the big data era.
Engineering a Sustainable Future: Evaluating the Multifaceted Impacts of Transitioning to All-Electric Bus Fleets in Urban Areas
Authors: Mao Kewen , Liang Hiu fung , Wu Yanxi , Shi Ruixuan
Published: August 2024

The global shift towards electric buses in urban transportation, driven by growing concerns over air pollution and climate change, represents a significant departure from the traditional reliance on diesel buses. However, the transition from fossil fuel-powered to electric buses is a complex process that, if not properly managed, could lead to unintended ecological consequences. To comprehensively assess the environmental impact of transitioning to an all-electric bus fleet, we developed an innovative environmental index model that goes beyond the conventional well-to-wheel (WTW) analysis of pollutants. Our model incorporates a wide range of environmental factors, including greenhouse gases (GHG), soil and water pollution, and waste accumulation, providing a holistic view of the ecological footprint of electric buses. Furthermore, to evaluate the financial viability of this transition, we constructed a break-even point model that considers the initial costs and long-term operational savings associated with electric buses. To enhance the accuracy and reliability of our financial projections, we employed advanced time series models, namely ARIMA and linear regression, to forecast future oil and electricity prices. By integrating these economic forecasts into our break-even point model, we developed a comprehensive framework for assessing the financial feasibility of transitioning to an all-electric bus fleet by 2033. Leveraging this framework, we created detailed ten-year roadmaps for three major U.S. cities – New York, Los Angeles, and San Francisco – outlining the strategic steps required to achieve a sustainable and cost-effective transition to electric buses. Our findings provide valuable insights for policymakers, urban planners, and transportation authorities, empowering them to make informed decisions as they navigate the complexities of adopting electric buses in their cities.
Optimization Study of Momentum Strategy for Tennis Match Based on FINX Evaluation Model and AHP
Authors: Fu You , Zhou Wufan , Wang Youzhan
Published: August 2024

This paper focuses on a comprehensive study of the evaluation of tennis players' match performance, aiming to explore the complex dimensions of momentum in sport by analyzing the comprehensive data set of Wimbledon 2023 and introducing FINX models to analyze and predict match flow and key transitions. Firstly, this paper divides 19 determinants of match results into four groups: off-field factors, internal situations, internal factors and external factors. Secondly, a momentum scoring equation is developed by using entropy weight, hierarchical analysis and TOPSIS methods in the FINX model. Finally, we compare the prediction results of the FINX model with the actual matching results. The results show that the correlation between the prediction accuracy of the model and the actual competition result is 0.826, which shows a strong prediction ability.
Summary of Liquid Loading Law and Liquid Loading Prediction Model in Gas Well Wellbore
Authors: Zhao Hui , Wang Cixun
Published: August 2024

Gas well wellbore effusion is one of the important problems to be solved in the process of gas well development. When the problem of effusion is serious, it will lead to gas well shutdown and water flooding. The key to solve this problem lies in whether the liquid accumulation can be accurately identified and predicted in the early stage of liquid accumulation. This paper summarizes the mainstream methods of liquid accumulation identification, which are mainly divided into droplet model and liquid film model. In terms of droplet model, researchers have proposed a variety of models to predict and identify liquid accumulation in gas wells based on the force balance of droplets in gas flow. The liquid film model analyzes the stability of the liquid film, the change of the thickness of the liquid film and other factors, and establishes a variety of models to predict whether the liquid film will return, so as to determine the location of the liquid loading point and the critical liquid carrying speed. These models are not only widely used in vertical wells, but also studied and applied in complex well types such as inclined wells and horizontal wells. With the advancement of computing technology and the deepening of theoretical research, the application effect of these technologies in predicting liquid loading in gas wells has been continuously improved, which provides important support and guidance for the safe production and operation efficiency of gas wells. At the same time, the challenges faced by the research in terms of data accuracy and method applicability are analyzed. Finally, the summary evaluation of several methods is comprehensively reviewed, and the prospect of future gas well effusion identification and effusion prediction research is discussed.
Analysis and Optimization of HEYTEA's Marketing Strategy
Authors: Huang Xiaoxiao
Published: August 2024

Chinese tea culture is the culture of making and drinking tea in China, which has a long history. The extensive and profound traditional tea culture includes not only material and cultural levels but also profound spiritual civilization levels. With the development of society, conventional tea products were hard to meet consumers' demands and needs as the audience is not extensive, and thus the flexible form of tea drinking has gained a broad space for development. Therefore, people create a variety of new tea-drinking brands with new characteristics through the collision of creativity and tradition, and the key point that determines whether a product could have a selling point or not is the marketing strategy of the brand. This paper will analyze the brand positioning, 4Ps marketing strategy, and existing problems of HEYTEA, explore the deep-seated reasons and shortcomings behind its success, and put forward optimization suggestions to break through the current homogenized competition situation.
Prediction and Analysis of Carbon Emissions in China Based on ARIMA-BP Model
Authors: Jin Zhenyang , Huo Weiji , Deng Huo
Published: August 2024

Based on the energy consumption data of 30 provinces in China from 2000 to 2021, this paper estimates and predicts the total carbon emissions of 30 provinces in China from 2000 to 2035 using ARIMA model and BP neural network model. ArcGIS and standard elliptic difference are used to visually analyze the spatio-temporal evolution characteristics, and LMDI model is further used to decompose the driving factors affecting carbon emissions. The results show that: (1) China's total carbon emissions increased year by year from 2000 to 2035, but the growth rate of carbon emissions decreased gradually; The carbon emission structure is "secondary industry > residents' livelihood > tertiary industry > primary industry". the growth rate of carbon in secondary industry and residents' livelihood is relatively fast, while the change trend of primary industry and tertiary industry is relatively small. (2) the spatial distribution of carbon emissions in China's provinces presents a typical "eastern > central > western" and "northern > southern" distribution pattern, with the carbon emission center moving to the northwest; (3) The regions with higher development level of digital economy, industrial structure and new quality productivity have relatively less carbon emissions, with significant group difference effect; (4) Energy consumption intensity effect is the main factor to drive the continuous growth of carbon emissions, per capital GDP and energy consumption structure effect are the main factors to curb carbon emissions, and the impact of industrial structure and population size effect is relatively small. Based on the research conclusions, policy suggestions are put forward from the aspects of energy structure, industrial structure, new quality productivity and digital economy.
Comparison and Analysis of the Differences in Real Estate Financing Models Between Vanke and Sunac
Authors: Chen Yalei
Published: August 2024

In recent years, with the influence of the epidemic, the development of the real estate industry has slowed down, facing a series of problems. Under the new situation, it is crucial to consider the issues for each real estate company in how to choose financing strategies to broaden financing channels and solve the problem of expensive financing difficulties in financing. In this study, Vanke Co., Ltd. and Sunac China Holdings Co., Ltd. are selected in the real estate industry leading enterprises as the object of the case research. Based on the financial data from 2020 to the first half of 2023, the actual situation of the real estate industry under the impact of the epidemic is impacted. Combined with the existing financing model of Vanke and Sunac. The differences in the financing model of the two are compared and analyzed, and the relevant conclusions are obtained the relevant methods are summarized in order to provide a reference for similar real estate companies in China.
Titanic Survival Prediction Based on Machine Learning Algorithms
Authors: Zhang Yuming
Published: August 2024

This report is aimed at demonstrating the application of machine learning techniques for predicting the survival of passengers who boarded the Titanic. After analyzing the Titanic dataset, which includes variables Pclass, Sex, Age, SibSp, Parch, Fare, Ticket, and Cabin, two machine learning algorithms, Logistic Regression and Random Forests Model, are used to give survival predictions. Models are compared to find an accuracy difference, and the magnitudes that each factor has on survival are also identified. Data preprocessing is the essential technique that will be used to adjust the data set. Before this process, correlations between variables are analyzed to give directions for feature engineering. And for feature engineering, data conversion and vacancy filling are first implemented. Afterwards, features are selected while new features are gained for model implementation. In understanding the final outputs of the model, new features, like name length, combine to give insight into more implicit survival factors that have been previously ignored.
Cauchy Mean Value Theorem in Hyperbolic Plane
Authors: He Yiyang , Liu Lanxin
Published: August 2024

A Hyperbolic number is a generalization of real number. It is a commutative ring with zero factor generated by two real numbers. It is of great value in practical application. Differential mean value theorems play an important role in real analysis, one of which is Cauchy mean value theorem. By studying the correlative properties of hyperbolic numbers, this paper extends the Cauchy mean value theorem in real analysis to the hyperbolic plane, obtains the hyperbolic mean value theorem, and gives a strict proof. Hyperbolic Cauchy mean value theorem lays a further theoretical foundation for the development of hyperbolic analysis, injects new impetus to hyperbolic analysis, and improves the practical application value of hyperbolic analysis.
A Study on Elderly-friendly Park Landscape Design with an Emphasis on Emotional Healing
Authors: Wang Xiaohan
Published: August 2024

With the growing trend of population aging, parks, as an essential part of urban green space play an increasingly significant role in the daily lives of the elderly. Parks are not only good places for the elderly to take leisurely walks, but also important venues for social, cultural, and physical activities. Therefore, a deep understanding of the elderly’s expectations and needs for park landscapes is crucial for optimizing park design and enhancing the quality of park services. This article aims to study the design of elderly-friendly park landscapes with an emphasis on emotional healing. By analyzing the psychological needs of the elderly and combining park landscape design concepts, it explores how to create park landscapes that are in line with the characteristics of the elderly’s life and have emotional healing functions. This study adopts a combination of literature review and case study methods, analyzes the current issues in park landscape design, and proposes corresponding optimization strategies. The research results show that elderly-friendly park landscape design with an emphasis on emotional healing can enhance the quality of life and happiness of the elderly, which is of great significance for building an elderly-friendly society.
Analysis of the Impact of Interest Rate Level on the Real Estate Industry
Authors: Sun Yumo
Published: August 2024

As a matter of fact, interest rate level is one of the key indicators in financial fields especially in recent years, which has a strong effect on domestic economy as well as global economy. Among various affected fields, the real estate industry is one of the most influenced industries on account of its intrinsic features of financing as well as highly relevant on the cash flow. With this in mind, this study will systematically analysis the impacts of interest level on the real estate industry based on the data analysis of several situations and cases. To be specific, the interest rate shock effects will be evaluated at the same time. According to the analysis, the mechanism will be demonstrated based on the evaluations from the demand as well as supply sides. Following the analysis, corresponding suggestions as well as strategies will be proposed accordingly. Overall, these results shed light on guiding industry, governments as well as consumers to aware the impacts and pave a path to propose solutions.
Comparison of Cournot Duopoly Model and Stackelberg Model
Authors: Tan Leqing
Published: August 2024

As a matter of fact, the game theory is a kind of mathematical study of economic interactions. The Cournot Duopoly Model and the Stackelberg Model are the two widely used concepts in the oligopoly market. Both are similar but different in firms’ order of making decisions. Firms in the Cournot Duopoly Model announce the quantity of production simultaneously, which is different from the Stackelberg Model where the leader makes decisions first then the follower responds to the leader’s plan. Therefore, the profits of firms are unequal in the two models. Firms in the Cournot Duopoly Model earn the same profits while the leader gains more advantage than the follower in the Stackelberg Model. This study aims to compare the two models and explain the difference between the two models is due to the order of announcing plans. It points out that the two models should consider the external factors that affect the outcome of models in future development.
Research on Multi Beam Sideline Model Based on Geometric Relationships
Authors: Peng Yonghe , Liu Rui , Peng Zhonghao , Huang Suwan
Published: August 2024

Marine surveying and mapping is a fundamental construction work to optimise the development of marine resources and safeguard marine rights and interests, while multibeam bathymetric system is an important tool for marine surveying and mapping engineering. This paper studies a multibeam bathymetry model based on geometric relationship. In this paper, firstly analyse the geometric relationship of measurement parameters, and get the mathematical models of coverage width and seawater depth, and the overlap rate of adjacent strips. Considering the changing relationship between the heading of the ship and the normal projection of the slope, this paper further deduces the coverage width equation in three-dimensional space on the basis of the two-dimensional multibeam slope model. It not only provides a simplified strategy for ocean mapping, but also provides a basis for solving the data coverage problem when the heading of the sounding process is not parallel to the isobath.
Comparative analysis of environmental adaptation and individual strategy choice in animal foraging behavior
Authors: Ji Yijia
Published: August 2024

This paper aims to compare and analyze the environmental adaptation and individual strategy choice of different animals in foraging behavior. By selecting lions, antelopes and vultures on the African prairie as the research objects, collecting data by observation and experiment, and using statistical analysis and behavior analysis methods, the foraging behavior of the three animals was deeply studied. The results show that different animals show their unique environmental adaptability and individual strategy choice in foraging behavior. As a top predator, the lion's foraging time and success rate are greatly influenced by food abundance, showing high fluctuation; As a herbivore, antelope has a relatively fixed foraging time and a high success rate. Vultures, as scavengers, have the best foraging efficiency and stability. In addition, food abundance has a significant impact on the foraging behavior of the three animals, while weather conditions have no significant correlation. Behavior sequence analysis reveals the dynamic changes of animal foraging strategies, while principal component analysis further identifies the differences of behavior patterns among different animals. The research in this paper not only helps to deeply understand the mechanism of animal foraging behavior, but also provides a new research perspective and method for ecological protection, animal behavior and other fields.
Forecasting Daily Replenishment Volume and Pricing Strategies for Vegetables Based on Time Series Models
Authors: Yin Ziliang , Sang Yuxin , Li Hongsu
Published: August 2024

Against the backdrop of today's rapid socio-economic development, retail supermarkets are faced with increasingly complex sales management challenges, especially in the area of vegetable sales. As a seasonal and perishable commodity, the accurate forecasting of vegetable sales volume and the effective formulation of pricing strategies are crucial to the operational efficiency of retail supermarkets. The relationship between total daily sales and cost-plus pricing is analyzed by quantifying the total daily sales, average daily sales price per unit, the degree of daily sales discounts, and the daily sales shipping loss metrics for each category. The total sales and total pricing data of each vegetable category from July 1 to 7 in each of the past years were screened to forecast the total sales and pricing from July 1 to 7 in the year 2023 by using the ARIMA model in the time series analysis method. Based on the forecast results, the replenishment volume and pricing strategy for the day are adjusted to achieve the goal of maximizing revenue.
The Impact of the Belt and Road Initiative on the Economic Development of the Countries Participating in the Initiative
Authors: Han Yingjie , Jin Yajing , Wu Jianhui
Published: August 2024

In the context of globalization, common development has become an important goal pursued by all countries. This article aims to evaluate the impact of the “Belt and Road Initiative” (B&R) on the economic development of countries along the route, as economic cooperation between countries continues to strengthen and common prosperity becomes an increasingly important issue. This paper selects panel data from several relevant countries from 2004 to 2022 and uses the difference-in-differences method (DID) to compare the economic development between countries participating in the “B&R” Initiative and those that are not. The empirical results indicate the “B&R” Initiative has a promoting effect on the income per capita level and Industrial structure optimization of participating countries. Moreover, countries with a higher level of economic development are affected by the “B&R” Initiative, and their Income per capita growth effects are more obvious, while the increase in the proportion of secondary industry in less economically developed countries is more obvious. This paper finally puts forward relevant policy recommendations based on empirical results.
Research on the Investment Value of Oracle based on SWOT, Financial Analysis and Valuation Methods
Authors: Wang Yongjian
Published: August 2024

Value investing has long been a major social issue, and a growing number of investors are now shifting their focus to the developing artificial intelligence market. This paper employs the idea of value investment and fundamental analysis to choose a representative Oracle firm in the artificial intelligence market for investigation. The study reveals a research gap regarding value investment in artificial intelligence. This study gathered information about Oracle and its sector and used SWOT, financial, and value analyses to investigate Oracle and the artificial intelligence market. The study discovered that Oracle has great industry competitiveness, exceptional performance across a range of metrics, and a good investment value, and that the notion of value investment can be applied to the artificial intelligence sector. In addition, it is discovered that Oracle must contend with numerous dangers and difficulties from strong rivals. This analysis combines Oracle's advantages, disadvantages.
The Role of Artificial Intelligence in China’s Manufacturing Industry: Reality and Prospects
Authors: Na Kexin
Published: August 2024

The convergence of artificial intelligence with China's manufacturing sector marks the dawn of a new digital era with profound implications for productivity, innovation, and global trade. The emergence of artificial intelligence is redefining how factories operate in China, bringing unparalleled efficiency and agility. Powered by AI, the promise of smart manufacturing is more than just an incremental advance; It represents a fundamental shift in manufacturing towards intelligent, connected and autonomous systems. In the current situation, AI has begun to be deployed in many manufacturing areas in China, focusing on process optimization, supply chain management, product development and after-sales service. Factories are becoming smarter, using big data analytics and machine learning algorithms to improve decision-making and operational efficiency across all aspects. At the same time, such rapid development will raise questions about the collapse of the low-skilled labor market and information safety. This essay also puts forward some solutions in turn.
Legal Attributes of AI-Generated Images in Copyright Law
Authors: Li Xiaoyao
Published: August 2024

The use of artificial intelligence (AI) to generate images has become a trending method of content creation, yet many controversies still surround the legal attributes of AI-generated images. An analysis of the definition of works in copyright law reveals that assessing “originality” is key to determining whether AI-generated images can be recognized as works. The academic community holds both affirmative and negative views on the legal attributes of AI-generated images. Based on this, an analysis of the current two theories from the perspective of originality suggests that the legal attributes of AI-generated images should be comprehensively considered from both subjectivity and objectivity perspectives. This includes taking into account the individual’s subjective contribution to creation and whether the generated images themselves constitute works in the sense of copyright law. Therefore, the core of judging whether the artificial intelligence generated map can constitute a work lies in the degree of correlation between the originality contribution of human beings and the originality of the generated map in the process of artificial intelligence creation. The generated map with a high degree of correlation is the “work”, and its copyright should also belong to the user.
Analysis of the Business Model of Taikang Elderly Care Community
Authors: Wang Ruiyan
Published: August 2024

The human society is entering the era of longevity, accompanied by the exacerbation of the aging problem in society. To achieve the happiness of the elderly in their old age, providing better care and health support for the elderly, and release the pressure of offspring taking care of the elderly's daily life and inconvenient medical treatment in certain regions, the requirement for elderly care communities is increasing every day. Taikang Life Insurance Co., Ltd. responded to the market demand, and established a big health industry system. Taikang creates three closed loops of "live longer, healthier, and richer", established a "Taikang Community · Yan Yuan" elderly care community. This community relies on a medical and elderly care integration model called "one community+ one hospital". The purpose of this model is to create a new lifestyle of "Elderly Disneyland" and "Five in One" while achieving simplicity, comfort, energy conservation, environmental protection, and humanistic care, laying the foundation for Chinese new elderly care model.
Preface: 3rd International Conference on Art Design, E-Education and Innovation Management (ADEIM 2024)
Authors: Tony Zachary , Sun Qilin
Published: August 2024

The 2024 3rd International Conference on Art Design, E-Education and Innovation Management (ADEIM 2024) was resoundingly held at Canberra, Australia from June 22-23, 2024. It highlights recent and significant advances in research and development in art design, e-education, educational reform, humanities, innovation management, and social sciences.
With participation of a large number of young researchers, ADEIM 2024 can be a platform for new collaborative ventures and strategic alliances to gain better insights into research and innovation, to harness the strength and synergies, and to bring further prosperity to the nations. As the future becomes more competitive and challenging, it is important to remain relevant and maintain the performance for continuous improvement in research & education. It will also serve to facilitate the exchange of information between researchers and professionals to discuss the latest issues and advancement in these areas.
ADEIM 2024 brought together experts from different organizations to initiate discussions on topics that are of interest to the conference attendees. This conference encourages young researcher from multi-discipline background to share their new and innovative ideas and findings is the aim of the conference.
ADEIM Organizing Committee
Canberra, Australia
Research on Quantitative Investment Strategies Based on Artificial Intelligence
Authors: Sun Wenjie
Published: August 2024

Artificial Intelligence (AI) has been developing rapidly in recent years, and the application of AI in various fields has gradually emerged. This paper focuses on exploring the cross-fertilization of AI with the Chinese stock market, and the study adopts 7 types of factors, totaling 29 factor indicators, covering multiple types of value, valuation, leverage, financial quality, growth, technology, and risk factors, etc. Through data preprocessing, feature engineering, and other steps on the factors, and then combined with 8 machine learning algorithms to construct corresponding quantitative trading strategies on CSI 300 constituent stocks. By comparing the results of various models, it is found that the trading strategies constructed by machine learning algorithms can obtain significant excess returns in the Chinese market. Except for Gaussian Park Bayes, the other seven model strategy returns beat the benchmark returns, among which XGBoost performs the best, achieving a 20.10% return and the smallest retraction. This paper has a positive impact on advancing the research on the intersection of machine learning and quantitative investment.
Research on the Subprime Crisis Based on Regional and Housing Type Perspectives
Authors: Lin Wenpei
Published: August 2024

This study discusses the 2008 subprime mortgage crisis's causes, housing and financial sector changes, and long-term effects. It forms the basis for real estate market regulation and risk mitigation. The research analyzes the causes of the crisis, including subprime loans, complicated financial derivatives, and lax regulatory monitoring. The problem is also linked to an overheated real estate market and loose credit policies. The crisis period is then examined, including housing price declines, sales volume declines, mortgage default increases, and foreclosure increases. It compares impacts across geographies and housing types, including apartments and single-family homes. Financial institution responses and policy changes are then examined. The study finishes with city or community case studies showing market dynamics post-crisis. The findings can help policymakers and financial institutions navigate the housing market and avoid future catastrophes.
The Impact of Sex Ratio Adjustment on Population Dynamics and Ecosystems in Marine Sea Lampreys
Authors: Ma Rongjun , Zhang Liaoyu , Lin Hangfei
Published: August 2024

As climate change leads to more frequent intense environmental changes in aquatic ecosystems, understanding how marine species adapt under changing conditions is increasingly important. This study investigated the survival strategies of sea lampreys under varying temperatures and food availability. A logistic model was developed based on changes in sex structure to examine if sex ratio adjustment could act as an adaptive mechanism under different environments. A food chain Lotka-Volterra model then investigated the impacts of sex ratio changes in sea lampreys on ecosystem dynamics. Resource utilization ratio varied with sex ratios, maximizing at 37.16% and minimizing at 1.43. Excessive sex ratio changes could destabilize the ecosystem. A population dynamics model compared the effects of initial fixation and variable sex ratios on population size. Sea lampreys showed the highest predation rate at a sex ratio of 1.43, best suited for population growth, averaging 35.31%, much higher than 4.68% under initial fixation. Findings provide insights into how species use plasticity to adapt to global change and may inform sea lamprey control strategies.
Study on Illegal Wildlife Trade Based on Gray Prediction and TOPSIS Methods
Authors: Yang Yulin , Zhang Hongjiang , Xia Zhongyang
Published: August 2024

In this paper, the protection of wildlife resources was studied, and an effective and universal assessment method was established by using the illegal wildlife trade index model. Firstly, through literature reading and open data collection, we creatively set up the Illegal Wildlife Trade Index System (IWTI). Then, the entropy weight method and TOPSIS method were used to evaluate countries, and four important constraints were identified: economic power, governance effectiveness, population status and local power. Secondly, we use the grey prediction model to predict the change trend of these constraint indicators in the next five years. Finally, we construct a two-objective fuzzy optimization model to obtain the optimal values of the four constraints by maximizing the benefits of protecting wildlife from illegal trade (Net-PER) and minimizing the costs. This study provides scientific assessment and decision support for wildlife conservation, and helps to formulate effective forecasting and planning strategies.
Critical Discourse Analysis of an Inaugural Speech Based on Halliday’s Systemic Functional Grammar
Authors: Zhou Xiuying
Published: August 2024

This study, from the perspective of critical discourse analysis (CDA), based on Halliday’s Systemic Functional Grammar, analyzes Biden’s inaugural speech from both macro and micro levels. At the micro level, it focuses on the language strategies used in the speech, analyzes the subject words of high frequency, transitivity and modality concerning textual meta-function, ideational meta-function and interpersonal meta-function of SFG. At the macro level, the interrelationship between language, power and ideology behind the text features is investigated and discussed. On the one hand, this study attempts to dig out the choice and usage of words by showing the distribution of subject words of high frequency and modal words. On the other hand, it tries to delineate how the language works to construct a privileged public speaker, thus to indicate the interrelationship between discourse, power and ideology. Transitivity analysis discloses Americans’ hegemony ideology as the leading power in the world stage. Subject words of frequency reflect that “freedom” and “democracy” have been used as tools to manipulate the power. Modality analysis reveals that Biden was trying to maintain and consolidate his power. The study of the interrelationship between language, power and ideology is conducive to exploration into the ideological construction behind discourse, and thus reveal the truth of political discourse.