bluuebunny/crossref_metadata_2025 huggingface dataset:
Preface: 2nd International Conference on Automobile Engineering and Traffic Science (AETS 2023)
Authors: Ferguson Michaelia , Hong Yun
Published: January 2024

The 2023 2nd International Conference on Automobile Engineering and Traffic Science (AETS 2023) was successfully held during October 28-29, 2023 in Milan, Italy. As a major international conference on automobile engineering, vehicle engineering, mechanical engineering, road safety, intelligent transportation system, and traffic science, AETS 2023 aims at bringing together researchers from the world and providing them with a high-qualified platform for them to share their latest studies and inspiring findings. This conference provides opportunities for the delegates to exchange new ideas and application experiences face to face, to establish business or research relations and to find global partners for future collaboration.

AETS 2023 is a platform for participants from diverse field to exchange ideas and findings to promote cooperation, networking as well as knowledge sharing in engineering practice. The conference includes the fields of i) Automobile Engineering, ii) Vehicle Engineering, iii) Mechanical Engineering, as well as iv) Traffic Science and Transport System. After a rigorous peer-review process, less than 40 papers were accepted. The accepted papers that focused on theory, applications, design, and experimental studies relevant to these fields were invited to present in this conference.

We want to express our gratitude to all reviewers for their time and effort in reviewing the papers. Their feedbacks to the authors have been excellent and useful to ensure the high quality of papers for the conference. Our sincere thanks also go to the organizing committee members for their hard work, cooperation and insights in ensuring the success of this conference.

AETS 2023 Conference Committees

Milan, Italy
Analysis of the Principle and Applications for High Voltage Device Based on SiC
Authors: Li Weiyao
Published: January 2024

The field of high-voltage electronics is rapidly evolving, with a particular focus on materials and devices that can withstand high voltages and temperatures while maintaining reliable performance. Silicon Carbide (SiC) is one such material that has been gaining significant attention due to its unique physical and chemical properties. This study will delve into the principle and applications of high-voltage devices based on SiC, exploring its potential for use in a range of power electronic systems. This paper will first explore the principle of SiC high-voltage devices, including a detailed analysis of the physical and chemical processes involved in their operation. Subsequently, this study will discuss the current state-of-the-art in SiC device fabrication and characterize the resulting devices based on their performance metrics. This will be followed by a discussion on the potential applications of SiC high-voltage devices in power electronics and beyond. Finally, this study will address the current limitations in SiC device research and development and explore possible future research directions that may lead to improved performance and reliability of SiC devices. By delving into the principle and applications of high-voltage devices based on SiC, this paper aims to provide a comprehensive understanding of the material’s unique properties and its potential for use in a range of power electronic systems. The analysis of current limitations and prospects will aid in identifying areas for future research and development efforts, leading to the advancement of SiC high-voltage devices for even more demanding applications.
Russia-Ukraine War's Effects on the World Economy
Authors: Liu Naijing , Su Yuannong
Published: January 2024

The persisting Russia-Ukraine tension has emerged as a pivotal disruptor within the global economic landscape. This protracted conflict has triggered far-reaching repercussions, casting its shadow across the entire international stage. Numerous countries have enacted a flurry of sanctions in reaction to the ongoing war between Russia and Ukraine, most notably the United States and the European Union. In the end, the conflict between Russia and Ukraine has changed energy prices, disrupted traditional trade routes, and generated widespread uncertainty in international markets. The underlying significance of this research lies in its exploration of the critical importance of stability and collaboration in an increasingly interconnected world economy. This article primarily discusses the start of the conflict and how the damage the conflict has produced on a local and global scale may be used to explain why trade routes have been disrupted and energy prices have increased. According to the report, the war has affected the energy system, commercial routes, and international markets, leading to general insecurity and negative economic effects.
The Versatile Applications of Distributed Bragg Reflector (DBR) Lasers: Sensing, Communication, And Beyond
Authors: Shan Siyue
Published: January 2024

Distributed Bragg Reflector (DBR) lasers have emerged as versatile and indispensable tools across various domains. Their advantages, including high signal-to-noise ratios, narrow linewidths, and support for distributed sensing, enable them to excel in diverse applications. DBR lasers have revolutionized optical fiber communication, medical diagnostics, and chaos-based key distribution. They provide precise control over wavelengths, making them valuable in fields such as dermatology, ophthalmology, and photodynamic therapy. Additionally, they play a critical role in flow cytometry, spectroscopy, and dental procedures. In the realm of sensing, DBR lasers have proven their efficacy in detecting parameters like temperature, pressure, current, magnetic fields, and ultrasound. Innovative techniques, such as FPGA-based demodulation and slotted DBR optical fiber lasers, have further enhanced their capabilities. As technology advances, the potential of DBR lasers in sensing and detection applications continues to grow. Their ability to deliver real-time, accurate data across various parameters positions them as essential tools for addressing complex scientific, medical, and industrial challenges. The future promises exciting developments in DBR laser technology, further expanding their role in solving multifaceted problems.
Credit ability evaluation system of power selling enterprises based on big data
Authors: Wang Xudong , Liu Chang , Liu Yongchao , Lu Yuan , Zhang Jialu
Published: January 2024

With the gradual relaxation of the electricity market access threshold, the development pattern of market-oriented electricity sales has brought great challenges to the power grid business development. It is of great significance to select the right electricity selling enterprises in the market-oriented electric power marketing mode to ensure the practical demand of electricity customers and the operating efficiency of power grid enterprises. First, the basic characteristics of power big data are analyzed. Secondly, it classifies and analyzes the important factors that affect the performance credit of electricity selling enterprises under the new electricity transformation environment. By normalizing different types of key index data and assigning index weights, a credit ability evaluation model of electricity selling enterprises based on matter-element extension-TOPSIS is established. Finally, taking eight electricity selling enterprises in a province as an example, the credit ability evaluation model is applied to analyze and calculate the performance ability of different electricity selling enterprises. The results prove the practicability of the evaluation system proposed in this paper.
Bidirectional Multi-Device Daisy Chain Communication Architecture and Verification Based on UART Serial Communication Protocol
Authors: Sun Xun
Published: January 2024

This paper proposes an innovative bidirectional multi-device daisy chain communication framework grounded in the Universal Asynchronous Receiver-Transmitter (UART) serial communication protocol. This intricate architecture employs four distinct physical Input/Output (IO) interfaces to facilitate dynamic serial communication amongst multiple devices. These devices can be conjoined in a sequential daisy chain or in a closed-loop ring configuration. To further enhance the functionality, our system incorporates a unique mechanism that leverages randomized device codes for rapid address allocation. This not only facilitates directional communication but also supports broad-spectrum broadcast transmissions. An exhaustive simulation of the said protocol was carried out utilizing Proteus software in tandem with a Microcontroller Unit (MCU) model. Critical parameters such as communication response delay, the cumulative failure rate of transmissions, and the isolated failure rate of individual data packets between nodes were meticulously evaluated. Preliminary findings underscore the protocol's potential in fostering cost-effective and dependable communication amongst a plethora of devices. The practicality and versatility of this system manifest prominently in arenas like cluster robot command, robotic automation, and holistic environmental monitoring.
Application of Artificial Intelligence Technologies in Concrete and Nanomaterials
Authors: Li Xiaoshuang
Published: January 2024

With the continuous adjustment of contemporary technology, artificial intelligence has gradually become irreplaceable. The main goal of the paper is to discuss the core of artificial intelligence - machine learning and its application in basic concrete materials and nanomaterials. Concrete is a kind of mixed material with high hardness, high compressive strength, low cost and easy production; Nanomaterials, whose properties are mainly determined by quantum mechanics, consist of a powdery or agglomerated natural or artificial material composed of basic particles. With the continuous advancement of modern technology, machine learning algorithms are gradually replacing previous technical algorithms such as manual algorithms, and becoming a very important tool in the engineering field. However, with the increasing complexity of various new materials, some materials such as nanomaterials have still not fully mastered the application methods of machine learning data analysis, therefore they have some limitations on their use. In this work, the impact and role of machine learning on material applications are discussed. Data patterns learned by humans are entered into machine learning, and high-dimensional data are easier to analyze. Machine learning has brought the development of concrete and nanotechnology in the field of materials to a new level, and a new milestone has come for technology to replace labor.
Comprehensive Analysis of Internal Flow Dynamics in Pipeline Systems
Authors: Yang Tianqi
Published: January 2024

This research delves into the intricate flow dynamics within a gas pipeline, leveraging the small perturbation equations to elucidate the flow scenario. Utilizing the Python programming language, the study derives the numerical solutions for the governing equations of the pipeline's flow field. This is achieved through the successive over-relaxation (SOR) iterative method in tandem with the Neumann boundary conditions. The flow dynamics are subsequently visualized and analyzed using streamlined diagrams and Mach number cloud representations, facilitating the identification of stress concentration points on the pipeline's inner wall. Such insights significantly affect the pipeline's optimal design and strategic reinforcement. Beyond its immediate application, the methodology presented herein offers a robust framework for addressing diverse fluid mechanics simulation challenges. Its versatility extends to realms such as automotive contour design, pipeline leakage simulations, and engine compressor configurations. When confronted with the need to dissect fluid flow and stress dynamics, professionals can harness the Python-based SOR iteration code to derive governing fluid equations, enabling a graphical interpretation through streamlined and Mach number cloud diagrams. This study, thus, underscores a pivotal toolset for fluid mechanics challenges across various engineering domains.
The Impact of the Use of Fintech on Enterprise Value
Authors: Ma Xianting , Wang Mingjun
Published: January 2024

With the evolution and progression of fintech, an increasing number of enterprises have introduced fintech. However, it is still unclear whether fintech can improve enterprise value in practical application. This study collected relevant data of Shanghai and Shenzhen A-share listed companies in China from 2011 to 2019, and analyze the objective impact of fintech on enterprise value by linear regression. Linear regression model was established, descriptive statistics were performed, collinearity problem was excluded, and significance level was observed. By conducting rigorous empirical research to explore the use of fintech on the value of enterprises. Through this research, it is found that the use of fintech has a significant improvement on the value of enterprises, indicating that fintech is conducive to improving the efficiency of business operations and improving their performance in the market. Further research finds that the significance level of small enterprises is significantly positive at the 5% level. It is speculated that this is because for small enterprises, the technology level is relatively backward compared with that of large enterprises. At this time, the introduction of fintech will greatly promote the development and value of enterprises. Finally, it is concluded that relevant enterprises can improve their self-value by introducing fintech.
Research On Replenishment Decision of Vegetable Commodities Based on Seasonal Decomposition Exponential Smoothing Method and Objective Programming Model
Authors: Hu Xiaofeng , Li Jiaqi , Huang Mingfei
Published: January 2024

Vegetables are indispensable in people’s daily lives and represent a high proportion of the goods sold in supermarkets and bring in a large amount of profit. Therefore, the replenishment and pricing decisions on the day of sales are particularly important. In order to make the best replenishment decision, this paper firstly solves the relationship equation between the sales volume of each vegetable category and the cost-plus ratio coefficient based on the least square fitting; secondly, considering the cyclical change of the vegetable sales volume, the seasonal decomposition of the exponential smoothing method is used to predict the demand for each vegetable category in the first week of July; lastly, the profitability optimization function of the superstore is set up: the objective function is the total profit of the superstore, and the decision variables are the daily supply of each vegetable category. The objective function is the total profit of the hypermarket, the decision variables are the daily supply of each vegetable category and the cost-plus ratio coefficient, and the constraints consider the maximum inventory of the hypermarket, the supply is greater than the demand and is less than the maximum value of the historical sales volume. The maximum daily profit and the optimal cost-plus ratio of the hypermarket are finally solved. This study has reference value for vegetable commodity replenishment decision.
The Application and Characteristics of VR Technology in Disaster Event News
Authors: Shan Hongru
Published: January 2024

With the development of technology, an increasing number of new report formats are being applied in the field of journalism. The immersive nature of VR technology makes it particularly valuable in news reporting, especially in disaster news. Currently, a considerable number of VR news reports have been published across various domains. This paper has analyzed the application of VR news reporting in disaster events, drawing from specific case analyses of three distinctive events: pandemics, fires, and earthquakes. It summarizes the characteristics of VR disaster news in terms of scene construction, information dissemination, storytelling, and more. By comparing VR technology with traditional news reporting on the same topic, it has examined the strengths and weaknesses of VR technology in the realm of disaster news. The paper also provides insights into the hotspots and prospects of this research topic.
Analysis of Real Estate Predictions Based on Different Models
Authors: Li Yixu
Published: January 2024

As a matter of facts, real estate price prediction is meaningful for investors. This study conducts a comprehensive analysis of multiple real estate price prediction models, including genetic algorithms based on optimization algorithms, random forests based on machine learning, and recurrent neural networks (RNN) based on deep learning. The aim is to evaluate the strengths and weaknesses of these models in terms of predictive accuracy, explanatory power, and computational efficiency. Based on the analysis, genetic algorithms perform well in improving prediction accuracy and model convergence speed, but are sensitive to parameter selection and suffer from overfitting problems. Random forests improve prediction accuracy by integrating multiple decision trees, but are not interpretable enough and are susceptible to data noise. RNN has advantages in processing time series data, but requires a large amount of data and computing resources due to high computational complexity. Although each model has its limitations, it also has great potential. Through methods such as algorithm optimization, model integration, and feature engineering, the accuracy and reliability of real estate price prediction can be further improved. This study not only provides multi-angle model evaluation for real estate price prediction, but also provides development directions for future research.
Inverse Kinematics Implementation Techniques in Robotics
Authors: Zhang Benjamin
Published: January 2024

Inverse kinematics is crucial for offering precision in controlling robotic mechanisms, making them versatile for intricate roles in fields like manufacturing, medical services, and digital animation. It also facilitates innovations in automation, efficiency, and safety, thereby boosting overall performance in diverse industries. This review aims to present an overview of how deep learning techniques are employed in inverse kinematics, targeting researchers seeking to explore different approaches in this field. When calculating the inverse kinematics using the traditional approach, the complexity and non-linearity of a high degree of freedom robotic systems can pose limitations and lead to suboptimal results. Comparing different models of deep learning, this review focuses on the potential of deep learning as a suitable alternative approach for solving inverse kinematic problems. Also, it provides guidelines for researchers in utilizing deep learning for inverse kinematics applications while emphasizing the ethical and societal implications that arise from these advancements. Further emphasis is on the significance of case studies, insights into real-world applications, the challenges encountered, and future directions for research. Overall, this review covers various aspects of deep learning models' implementation in inverse kinematics. It also informs them about the potential of these models in advancing the field of inverse kinematics, paving the way for more precise and adaptive robotic movements, improved human-robot interactions, and greater autonomy in a wide range of industries.
Critical Analysis of Baidu's Business Strategy
Authors: Pan Yining
Published: January 2024

People's life is inseparable from the Internet. However, network information is a huge collection of various information resources. Its quantity is growing rapidly, disorderly, quality varies, and there is no certain organization and control. This brings great inconvenience to people's search and acquisition of information. It is very necessary and important for all network users to accurately and efficiently obtain relevant and applicable information to their needs from massive amounts of information. Search engines can help users find information about themselves in trivial information. Baidu.com has become the leader of China's Internet competition in the world with its relatively conservative specialization strategy. Baidu's brilliance is innovative profit models, tailor-made development strategies, and clear marketing models. At the same time, there are also disadvantages that restrict its development. Thus, this article analyzes the impact of Baidu’s profit model, competitive advantage, shortcomings, shortcomings, and advertising models on business strategies by combing the previous literature.
Analysis on the Time Series Forecasting on COVID-19 New Infections Declining in Shanghai, China
Authors: Ji Peicheng
Published: January 2024

This research focus on the forecast of the effect of policy influence on COVID-19 in Shanghai, China, during March to May in 2022. By using new infection numbers in 50 days as the train model, four different models were used for forecasting the new infection numbers in future 14 days. Data was published on China Centers for Disease Control and Prevention. Simple exponential smoothing, Holt’s linear method, ARIMA model and ETS model were utilized and compared the accuracy with each other to find the best fit forecast model. As the result, the ARIMA (2,2,2,) model best fits the decline of the new infection. This result needs a condition of similar infectiousness to COVID-19 and the policies and efforts similar to those used to control the outbreak in Shanghai from March to May 2022. This research helps the forecast for policy effects in future epidemiologic disease control.
Design And Analysis of Flapping Wing Aircraft Based on Crank Mechanism
Authors: Huang Changlong , Guo Weipeng , Wang Hanyu
Published: January 2024

This paper is proposed a flapping wing aircraft based on the crank slider mechanism to solve the problems of the two flapping wing structures, such as synchronization and excessive local stress common to existing ornithopters. MATLAB is used to solve the equations to determine the dimensions of the individual components, and the 3D model is designed by SolidWorks software. The static analysis on flapping wings, the static stress, and the static strain distribution map of flapping wings are carried out. Moreover, the mechanism of flapping wing aircraft is modeled in Adams software, which simulates the actual structure by designing the kinematic constraint relationships between the components. It was concluded that the flapping wing could achieve a flapping angle of 30 degrees in one cycle, which was consistent with the simulation results by MATLAB. Furthermore, it was found that the first principal stress of the danger point was less than the yield strength of the material to determine the rationality of material selection. Finally, the fluid trace distribution on the upper and lower sides of the flapping wings was analyzed, which was consistent with the actual situation.
Research On Human Physical Characteristics of Drivers Based on Ergonomics
Authors: Xie Huawei , Su Jinzhou
Published: January 2024

Correctly identifying the driver's identity is the breakthrough in case investigation and tracing back to the source.Based on ergonomics, this study explored the relationship among man-machine-environment and their interaction rules from the perspective of human physiological and psychological characteristics, so as to achieve the purpose of optimizing the man-machine system's working efficiency.In this study, the key data acquisition elements such as car seat, control device, visual field and display device are determined under the condition of driving comfort.At the same time, the key data of drivers with different personal characteristics on the adjustment of cab layout elements under the driving comfort state were collected, and then combined with relevant theoretical knowledge of statistics, the prediction model of personal characteristics of motor vehicle drivers under the background of ergonomics was constructed.
Tesla Price Prediction Based on LSTM and GRU
Authors: Feng Zhenting
Published: January 2024

As a matter of fact, in today's society more and more people are becoming aware of stocks and are finding that they can gain great benefits from them. In this case, investors want to propose a method that can accurately predict the stock market in order to gain extra return from the markets. With this in mind, by studying the historical data of Tesla's stock, an LSTM model and a GRU model were implemented to analyze this data as well as give different predictions for the short-term future. According to the analysis, the result was that the GRU model's predictions were more accurate than the results predicted by the LSTM model based on several statistic indicators. Based on the evaluations, a better prediction model is derived from this study and the factors affecting the efficiency of the model are discussed in depth. Overall, these results shed light on guiding further exploration of price prediction.
Financial Analysis and Risk Study of Tesla Inc.
Authors: Zheng Zixin
Published: January 2024

In recent years, the development of energy-saving energy has become an important and promising market trend to strengthen the protection of the environment, achieve zero emission of transportation and reduce dependence on oil. The electric vehicle (EV) industry is growing rapidly with strong policy impetus in various countries, especially China. In 2022, China's EV sales accounted for 61.2% of global EV sales. However, with the continuous development of the market, the increasing progress of technology and the constant change of policies, the complexity of the market has increased. Therefore, it is challenging to predict the future direction of the EV industry and identify projects with long-term investment value. However, whether Tesla has the ability of sustainable development as the industry leader is the research topic of this paper. This paper describes the opportunities and challenges of the EV industry and analyzes its profitability, operating capacity, solvency, and development capacity based on TESLA's financial statements from 2020 to 2022. At the same time, the financial statements of companies in the industry, BYD and SAIC, were compared and analyzed with, and the opportunities and challenges encountered by them in China were analyzed. Ratio analysis is the main method used in this article in financial analysis, it is collected from the annual report of the company to calculate. The study found that from these different dimensions of financial analysis, it can be concluded that Tesla is a promising company.
Relationship Between Structure and Pathogenicity
Authors: Yu Xinyu
Published: January 2024

The global COVID-19 crisis caused by the SARS-CoV-2 virus has led to the emergence of multiple variants, capturing substantial international attention. This extensive study offers a comprehensive examination of the structural attributes and disease-causing potential of the original SARS-CoV-2 strain and its primary variants, namely Alpha, Beta, Delta, Gamma, and Omicron.
A Study on Pricing and Replenishment Decision of Vegetables in Fresh Superstores Based on Time Series Analysis
Authors: Wang Jiangning
Published: January 2024

This paper focuses on an in-depth study of the vegetable pricing and replenishment decision problem in fresh produce superstores. Using data preprocessing and multiple mathematical models, the sales and correlation laws between different categories and single products of vegetable products are analyzed. Firstly, the cyclical pattern of sales is revealed through the analysis of historical sales data; secondly, the pricing and replenishment strategies are optimized by using multiple linear regression and time series models; finally, an optimization model is constructed to predict future sales and replenishment, taking into account the spatial limitation of sales.
Analysis of the Impact on the Labour Market after the British Prime Minister and Government Policy Change
Authors: Lin Guangyu
Published: January 2024

Britain's economic situation is facing severe challenges following the failure of Liz Truss's mini-budget policy, and a series of fallouts is affecting the UK. After taking office, the Rishi Sunak government's policy direction should be necessary for workers' lives. This article focuses on the Labour market and analyses the factors contributing to the current state of the UK labour market. Economic development and labour interests should be balanced. The article is mainly based on qualitative analysis and economics theories. Data are sourced from the UK’s Office for National Statistics, mainstream press institutions, the Institute for Fiscal Studies, etc. In conclusion, the policies are suggested to ensure the interest and basic living standard of laborer’s as it is better for long-term development and future construction.
Research on the problem of multi-beam line measurement based on the cattle plowing traversal algorithm
Authors: Wang Zhaoyu
Published: January 2024

In order to study the depth and coverage width of sea water measured by the multi-beam detection system and the control of the overlap ratio range of the detection strip, the full coverage path optimization of the survey ship is carried out. In this paper, firstly, a model is established for the depth of the sea and the coverage width of the multi-beam detection system under the premise that the overlap rate is controlled within the range of 10%````~20% by using the property theorem of trigonometric function and geometric relation. Secondly, the Angle between the direction of the survey line and the projection of the normal direction of the submarine slope on the horizontal plane is analyzed, and the model for the depth of the sea area and the coverage width of the multi-beam detection system is further established under the constraint of the rolling attitude of the survey ship. Finally, the measured sea area is divided into molecular areas according to the overlap rate range and coverage width as standards, and then the coverage width and the number of survey lines are measured based on the cattle plowing traversal algorithm. The following results are obtained: When the survey ship starts and ends in the east-west direction and meets the requirement of 10%````~20% overlap rate, the number of survey lines is stable at 23, the total coverage width of the survey lines is 8.7852x108m, and the spacing of each survey line is 340.50m.
Research on Vegetable Product Pricing and Replenishment Decision Based on Linear Regression and ARIMA Model
Authors: Chen Yu , Hua Ziyan , Fu Yiwa
Published: January 2024

With the rise of fresh food supermarkets, how to automatically price and restock vegetable products has become a major challenge for many businesses. To develop a restocking and pricing plan for vegetable products in supermarkets, we first calculate the cost profit margin, standardize the profit margin and total sales volume data, and then incorporate vegetable categories into a linear regression model using dummy variables, We found a significant negative correlation between profit margin and total sales volume, and obtained the product pricing strategy using the linear equation of profit margin. After conducting ADF testing, the number of autoregressive terms and the average number of sliding terms of the Time Series (ARIMA) model were determined based on the test set results, and the model was used to predict the total daily replenishment of each vegetable category in the next week. This study has reference value for vegetable restocking and pricing decisions.
The Impact of Supplementary Pension on Household Risky Financial Asset Allocation
Authors: Yu Mingyue
Published: January 2024

With increasingly serious aging problem in China, supplementary pension, as the second pillar of the endowment insurance system, is expected to play an important role to relieve the pension pressure. Nowadays, people in China are exposed to various investment tools, but they still prefer to invest in risk-free financial assets. The allocation of household financial assets is not diversified enough. While supplementary pension is expected to improve financial structure of households. It may enhance the anti-risk ability of households, rational allocation of household assets, the ability of value-adding, and thus reduce the pressure of society to cope with the aging population. This paper selects the 2019 China Household Finance Survey (CHFS) database, using STATA software to investigate the impact of supplementary pension on risky financial asset allocation of Chinese households by applying probit and tobit models. The results show that supplementary pension can significantly increase the willingness of households to purchase risky financial products but has no significant effect on increasing the proportion of risky assets being held.
Comparison of Average Temperature Prediction Based on XGBoost and Prophet Models
Authors: Zhou Xiang
Published: January 2024

Temperature prediction is extremely important in various fields. With this in mind, this study utilized two prominent models, XGBoost and Prophet, known for their efficacy in time series forecasting, to perform daily average temperature predictions based on historical data. XGBoost model enhances the Gradient Boosted Decision Tree method and the Prophet model leverages an additive model that combines seasonal and holiday features. The dataset comprised historical data (1995-2020) of daily average temperatures from major cities, serving as an ideal time series subject for forecasting. This study trained both models on the initial 80% of the data from four cities and used them to forecast the remaining period. This research employed Root Mean Square Error (RMSE) analysis to evaluate the performance of the models. The results indicated that the Prophet model surpassed the XGBoost model in two out of the four cities and matched its performance in the other two.
A Comparison of the Performance of Rainbow Options and Stocks under COVID-19 and Ukraine Conflict
Authors: Liu Zhenhao
Published: January 2024

This paper hopes to explore which is the better choice for investors under the different environments of the US stock market, rainbow option or buying a single stock. Due to the improvement of the COVID-19 situation in the United States in 2021 and the introduction of government policies to stimulate the economy, the US stock market showed an upward trend throughout 2021. In 2022, due to the conflict between Russia and Ukraine, the global economy will be impacted, and the US stock market is no exception. In these two long-term bear markets and bull markets, it hopes to find a mutation option to control risks and improve returns. In this case, it focuses on rainbow options, which are options that help investors screen out the better-performing stocks or futures included in them. First, this paper paired 14 stocks in five fields, calculated the option’s payoff according to the rainbow option's rules, and then compared it with the return of the stock alone to explore the superiority of the rainbow option. The return on the rainbow option is higher than the return on any single stock. Then the option is simulated and priced for 1000 future trading days so as to obtain the return of the rainbow option under the assumption of stable fluctuation in the US stock market environment, which is used as the reference for pricing. Finally, the sensitivity analysis of options is conducted to study the main factors affecting the volatility of option premiums. The result is that the moves in rainbow options are always correlated with the stock that is more active.
Cultural Identity of Desert Architecture: Exploring Strategies for Integrating Traditional and Modern
Authors: Zhu Yueling
Published: January 2024

Predictions for desertification on a global scale, under an unusually variable climate, ecological vulnerability, and further expansion of human activities have become important in helping people build sustainable, green buildings in sensitive areas and exploring the possibility of better habitats in desert areas. The main objective of this study is to explore the possibilities of different types of desert architecture to provide sustainable habitats by combining desert traditional architecture, with modern architecture and human activities, to provide an alternative perspective on habitats on a global scale, and to predict their future evolution. Desert traditional architecture has always been a product of sustainable and green building, but the influence of globalization has made the people in the desert areas gradually lose their traditions and move towards industrialized construction and the use of materials, people are looking for modern living facilities to meet the needs that are not met by the traditional dwellings. In order to avoid the loss of traditional tangible and intangible architectural knowledge, this study focuses on how contemporary desert architecture can be adapted to meet the needs of modern lifestyles while still retaining the beneficial aspects of traditional techniques. Using examples of desert architecture from different periods in several countries, the study explores the differences and commonalities and summarizes the possibilities for sustainable development of traditional architecture in desert areas. In addition, the new architecture is categorized into three directions. The three directions of architectural design explore different possibilities for future desert architecture.
Analysis of the Impact of Dual Shareholding Structures on the Governance of Technology-Based Firms
Authors: Zhong Zhichao
Published: January 2024

As a matter of fact, since the technological revolution, the use of dual shareholding structures has become more and more widespread in technology-based companies as the number of technology-based companies has increased. These start-ups with dual shareholding structures have grown rapidly and have been able to grow into large corporations in a relatively short period of time. On this basis, dual equity structure seems to be a perfect match for many technology-based companies. In order to explore the positive effects and risks of dual equity structure on the corporate governance of technology-based companies, this paper investigates, studies as well as analyzes the issues. According to the analysis, it is concluded that dual equity structure is favorable to consolidate the founder's control over the company, expand financing, but harms the interests of small and medium-sized shareholders, and is detrimental to the equality of shareholders. Overall, these results shed light on guiding further exploration of firm governance.
Exploring the Formation of Sino-Japan Third-Party Market Cooperation Through the Lens of Industrial Strengths
Authors: He Bingxuan
Published: January 2024

With the intensification of the wave of anti-globalization and the prevalence of unilateralism, multilateral economic cooperation is urgently needed, due to the delicate bilateral relations between China and Japan, the field and strength of cooperation are limited, in this case, the third-party market cooperation has been explored. This paper focuses on the establishment of Sino-Japan third-party market cooperation, the impact of comparative advantages of different industries on the establishment of cooperation between the two sides, calculates the RCA indices of SITC classified products and some typical industries in recent years, searches for the complementary zone of the two countries' advantages, and evaluates the expected benefits of Japan; At the same time, it compares and discusses the trade and industrial structure of ASEAN countries as third-party market partners, and concludes that third-party cooperation is in line with the economic development needs and cooperation strategy of ASEAN. Finally, the article concludes that the establishment of Sino-Japan third-party market cooperation is in line with Japan's expected benefits and ASEAN regional development strategy, so it is necessary to make full use of the advantages of cooperation, take advantage of the industrial strengths of different regions to carry out a new type of industrial cooperation, and also reduce the negative competition in cooperation, so as to contribute to the recovery of the world economy.
Risk of New Energy Investment: A Case Study of BYD
Authors: Zeng Ruitong
Published: January 2024

Amid diminishing traditional energy sources and escalating environmental challenges, the new energy sector flourishes, presenting numerous investment avenues. However, increased opportunities are often synonymous with heightened risks, necessitating protective measures for investors through robust risk identification and mitigation. This paper leverages the Capital Asset Pricing Model (CAPM), a revered financial analysis instrument, to study investment risks in the emerging new energy realm, spotlighting China's BYD. Employing a decade's SZSC index data and China's risk-free interest rate, the research evaluates BYD's investment landscape across varying phases, notably during the COVID-19 era, and contrasts it with contemporaries like XPENG, NIO, and others. The findings aim to discern the new energy sector's risk portfolio, culminating in actionable insights for prospective investors.
Strategic Insights into the Global Energy Landscape
Authors: Wang Zhangchuying
Published: January 2024

In the 21st century, as the world grapples with the dual challenges of energy security and climate change, the energy sector stands at the forefront of global debates and discussions. This comprehensive analysis delves into the multifaceted realm of this pivotal sector, spotlighting three industry behemoths: Exxon Mobil, NextEra Energy, and Chevron. These corporations, with their vast global footprints, play a dominant role in shaping the energy narratives of our times.By weaving together intricate financial metrics with broader industry determinants and global influences, this essay seeks to offer a kaleidoscopic view of these companies' performances, trajectories, and the challenges they face. Key financial indicators, such as EPS, P/E ratio, ROE, and DCF, are meticulously dissected. They are then juxtaposed against the backdrop of technological innovations, environmental imperatives, and the constantly evolving geopolitical landscape. The transition from fossil fuels to cleaner energy alternatives poses both challenges and opportunities for these energy giants. Through this intricate exploration, the essay aspires to provide not just a snapshot of the current state of these companies but also a visionary perspective on their potential future in a world increasingly tilting towards sustainability.
Deep Brain Stimulation In The Treatment Of Cocaine Addiction
Authors: Lyu Jiaqi
Published: January 2024

The history of cocaine addiction as a considerable public health issue has remained more than a century. In recent decades, as the population of cocaine addicts has risen again, more external interventions, such as neurotechnology, medication, and psychological therapy, are being considered and discovered as tools to address the effectiveness of the issue. Deep Brain Stimulation (DBS) has emerged as a potential intervention as existing treatments are limited to managing and healing cocaine addiction effectively. This paper delves into the multifaceted relationship between cocaine addiction and DBS, drawing insights based on neurobiological functions and existing experiments in rodent models. While DBS has been given expectation in targeting addiction-related neural circuits such as rewarding systems, its effectiveness and safety in decreasing cocaine craving remains a critical topic. This paper also emphasizes the caution of translating the results of preclinical experiments into clinical applications. In an era when innovative therapeutic strategies are urgently needed, this article explores the intricate promise of DBS in the treatment of cocaine addiction, providing a balanced perspective on its potential and challenges in reshaping addiction therapies. The purpose of the paper is to make the process of overcoming cocaine addiction easier using neurotechnology, specifically deep brain stimulation, and furthermore, to reduce the population of cocaine users in the United States.
The Express Delivery Company Goes Public Through a Backdoor Listing based on the Backdoor Listing of Dingtai New Material by SF Express
Authors: Zhou Fanli
Published: January 2024

In China, enterprises face relatively huge costs in going public, resulting in enterprises preferring indirect listing methods such as backdoor listing to Initial Public Offerings (IPO). At the same time, backdoor listing has also saved many traditional industries with declining performance, making both parties win-win. At present, the logistics industry is developing rapidly. In 2016, logistics companies have been backdoor listing, logistics industry competition is becoming increasingly fierce, and more and more logistics enterprises choose to go public in order to enhance competitiveness and improve the status of the industry. Choosing the right timing and backdoor listing with a precise strategy will produce no less wealth than an IPO. This paper takes SF Express' backdoor listing of Dingtai New Material as a case, conducts performance analysis based on a theoretical basis, studies the impact of backdoor listing on the financial performance of enterprises, and provides experience for other logistics enterprises planning to adopt backdoor listing.
Past And Current Vaccine Development Effort of Gonorrhea
Authors: Qiu Jiayue
Published: January 2024

Neisseria gonorrhea causes gonorrhoea, which is one of the sexually transmitted infections (STI) diseases that can affect the health of women, men, and neonates. Reflecting on its history of treatment, the development and distribution of a vaccine hold significant potential for mitigating the impact of this disease, especially in vulnerable populations. However, developing a novel vaccine for Neisseria gonorrhoeae has posed considerable challenges. This is primarily due to the Gonorrhea's antigenic variation, rendering it difficult for the human immune system to identify. Neisseria Gonorrhea is currently exhibiting significant antimicrobial resistance, raising concerns about the potential for it to evolve into a superbug in the future. This escalating antimicrobial resistance has led to a diminishing effectiveness of antibiotics in treating Neisseria gonorrhoeae infections. Consequently, there is an increased risk of reinfection, potentially necessitating higher antibiotic doses during treatment. This, in turn, contributes to elevated treatment costs. Thus, the development of a new vaccine against Neisseria gonorrhoeae becomes imperative. This urgency is particularly pronounced for safeguarding the health of women and newborns. In this review, I explored the progress and efficacy of both historical and contemporary vaccines designed to address Neisseria gonorrhoeae infections.