bluuebunny/crossref_metadata_2025 huggingface dataset:
Simulation of Urban Dynamic Traffic Network Based on Greedy Algorithm
Authors: Yang Tianrun
Published: January 2024

This study explores the intricate dynamics of urban traffic flow under varying degrees of intersection and road section carrying capacity. We simulate a city-wide traffic network and examine the impact of extreme situations such as a decline in urban road carrying capacity on the entire traffic system. Our experimental procedure involved simulating traffic flow through intersections and road sections, artificially reducing their maximum carrying capacity, and observing the resultant changes in traffic patterns. Our data reveals a robust correlation between the decrease in carrying capacity and the actual flow percentage across intersections and adjacent sections, with a marked decrease in flow observed when the capacity reduction exceeds 40%. The actual flow percentage of nearby intersections increased significantly under the same conditions, suggesting a degree of redistribution of traffic flow. This study contributes to the broader understanding of urban traffic dynamics, offering valuable insights for urban planning and traffic management strategies.
Analysis of 21-Day Word Grid Learning Method
Authors: Cai Keyuan
Published: January 2024

As a matter of fact, mastering the learning methods in a field can greatly increase the speed and efficiency of learning and improvement in the field. Non-native English speakers develop a foundation for the language by acquiring English words. With this in mind, this paper will explain how a non-native English speaker learns to memorize English words on a large scale, i.e., 21-Day Word Grid Learning Method, as well as explain how to use the "21-day word grid learning method" and how this learning method can help learn English words. This study will present a way to learn to use the "21-day word grid learning method" to help one plan the review time reasonably, so that one can memorize words more reasonably and planned, and greatly improve the efficiency of memorizing English words. Overall, these results shed light on guiding further exploration of learning approaches as well as memory enhancement.
Research On Global Equity Based on Contribution-Welfare Model
Authors: Zhu Ruiqi , Zhang Yuhan , Huang Yijia
Published: January 2024

Based on the outcome equity idea from the proverb "more effort, more gain", this paper established a global equity index based on the assessment of national contribution level and welfare level, then measured and compared the global equity situation in 2020 and 2000. The results indicated that the international society is still under strong inequality, and the fairness situation of the international community has deteriorated in the past 20 years.The model in this paper can evaluate the contribution level and national welfare status of countries in the global scope, and measure the unfairness of the international community.
CAR-T Cell Therapy: Revolutionizing Cancer Treatment with Engineered Immune Cells
Authors: Fan Jiakai
Published: January 2024

CAR-T cell therapy, a revolutionary immunotherapy approach utilizes gene-engineered T cells to recognize and eliminate cancer cells. The CAR is engineered to recognize specific tumor-associated antigens, enabling T cells to effectively recognize and destroy cancer cells. Mostly, the cell for CAR-T cell therapy is collected from the patient which lead to a high individual. Then, the artificially engineered cells which express CAR, expand and culture in the laboratory. Finally, the CAR-T cells are sent back into the patient. This personalized therapy has shown remarkable success in treating hematological malignancies. Till now, there are shortages remaining in extending solid tumor application of it, since the potential side effects, including CRS and neurotoxicity. These challenges limit clinical usage and more waiting to be solved. In this paper, we aim to introduce CAR-T therapy and optimize CAR design, improve manufacturing processes, and explore combination therapies to enhance the efficacy and safety of it.
Unraveling the Choice Not to Work
Authors: Huang Zhiting
Published: January 2024

With the arrival of Covid 19, more and more people began to alter their ways of working. While traditional working practices are gradually disappearing, many firms turned to working from home during the quarantine, which also led to the development of new patterns of electronic device use. Due to the significant reduction in the labor force for many positions that need on-site work caused by people being unable to leave their living space, the business is ultimately forced to lay off employees. People consequently made the decision to stop working. People lose interest in looking for work over time, and this pessimistic outlook is sure to have an effect on both the body and the mind.  And this is not just the sole responsibility of one person, since others, like the family and the government, have to bear the costs of this decision. Therefore, it is in no way a value that should be shared. The functioning of society and the economy is necessary for an improvement in the happiness index of the populace.
Does The Governance Model of Husband-and-Wife Shareholding Lead to Underinvestment?
Authors: Pan Zhuoyu , Zhong Runyu
Published: January 2024

This paper explores the extent to which joint shareholding by husband and wife affects underinvestment in family firms by establishing a multiple regression model based on the family firm-specific socio-emotional wealth theory perspective. It is found that joint spousal shareholding can alleviate the underinvestment of family firms to a certain extent, and it is also found that the underinvestment can be further alleviated when the important positions in family firms have technical backgrounds as well as when the family firms actively undertake social responsibilities. The results of this paper suggest that family firms should utilize the advantages of joint ownership in the future, which is conducive to the long-term development of the enterprise
Research on Supply Chain Management Countermeasures for Fresh Agricultural Products
Authors: Li Yuemeng
Published: January 2024

Due to the rapid growth of China's economy and the popularization of the Internet, Online platforms are becoming increasingly popular for consumers to purchase products, online shopping platforms can provide consumers with a richer range of products and cheaper prices, and therefore favored by consumers. Fresh products, which are considered a special type of consumer goods, are subject to more restrictions on transportation and sales due to their characteristics, which solves the development dilemma of fresh products. In the face of this situation, this article mainly analyzes the problems of the cold chain logistics service system of fresh agricultural products in the context of e-commerce and puts forward the corresponding countermeasures on the basis of which, provides suggestions and guidelines for the development of the relevant logistics and fresh food industry, and then better promote the healthy and sustainable development of fresh agricultural products cold chain logistics under the background of e-commerce.
Research on the Diamond Price Prediction based on Linear Regression, Decision Tree and Random Forest
Authors: OuYang Zhe
Published: January 2024

Diamonds are the symbol of the pure and indestructible love and the luxury that people have always sought after. However, because people know less about diamonds, they often only rely on the introduction of salespeople and jewelers in diamond trading. Therefore, it is difficult for consumers to buy diamonds of equal value and price. To solve this problem, this paper uses Multiple Linear Regression model, Decision Tree Regression model and Random Forest Regression model to predict diamond prices based on various diamond evaluation metrics in data set, so that consumers can intuitively learn about the normal price of the evaluation metrics of selected diamonds. Through this paper, it is found that the Random Forest Regression model has the best fitting and predictive ability in diamond prediction task, which is also the most recommended model.
Recent Advances and Classification of Radar Technology
Authors: Sun Chongkai
Published: January 2024

This paper provides a comprehensive exploration of radar technologies, categorizing them by their unique technological attributes. It delves into phased array radar, known for its rapid directional control, interference resistance, multitasking capabilities, and adaptability. Then compares traditional phased array radar to digital phased array radar and discuss the future potential of phased array radar. Synthetic aperture radar is examined for its all-weather, all-day observation abilities in civilian and military applications, considering performance indicators like frequency, resolution, and repetition observation cycle. Lastly, quantum radar, utilizing quantum entanglement and superposition principles, is discussed for its potential in target detection, ranging, and enhanced system security. Although quantum radar technology is currently not mature and there are still many technical and application challenges, its unique advantages make it a technology with promising prospects. This evolving technology remains indispensable across numerous domains, from defense to agriculture.
Analysis the Principle of AI Chips and the State-of-art Applications
Authors: Zheng Qi
Published: January 2024

In recent years, the artificial intelligence (AI) chips have emerged as indispensable components specialized for executing AI computations, which is considered as a new era for integrate circuit industry. On this basis, this study comprehensively examines the underlying principles, performance characteristics, diverse applications, limitations, and prospective directions in AI chip research. The parallel architecture, sparsity, quantization, and adaptability of AI chips empower the expeditious and efficient processing of AI tasks. These chips find versatile applications in computer vision, healthcare, and intelligent robotics, amplifying their transformative impact. Nevertheless, challenges persist in terms of scalability, versatility, and the rapid pace of technological evolution. As a matter of fact, ongoing research endeavors should prioritize the symbiotic optimization of hardware and software, the creation of energy-efficient designs tailored to specific domains, and the seamless integration of emerging technologies. These results offer a lucid depiction of the prevailing state and the anticipated trajectory of AI chip development.
Multifactor Analysis Revealing Key Factors of Chronic NCDS Based on Random Forest Models
Authors: Cai Jinzhu , Zhao Ziying , Zheng Xinzhe , Feng Qiulin , Deng Jie , Zhang Yu
Published: January 2024

This article investigates chronic non-communicable diseases with a focus on lifestyle and dietary habits. By establishing separate models, eliminating the influence of highly correlated variables, and addressing data imbalance using the SMOTE algorithm, seven independent variables were identified, including basic information, lifestyle, and dietary habits. Random forest algorithm analysis revealed that smoking and alcohol consumption significantly impact the occurrence of chronic diseases, with different dietary factors associated with specific diseases. Occupational type, work intensity, and stress also have a notable influence on the risk of chronic diseases. Furthermore, increasing daily physical activity is associated with a lower disease risk. These findings contribute to a better understanding of the occurrence and management of chronic diseases, providing valuable information for prevention and treatment.
Technology And Application Outlook of Integrated Circuits Under the Internet of Things
Authors: Heng Shengjiang
Published: January 2024

The rapid development of the Internet of Things (IoT) has injected new vitality into the development of integrated circuits (ICs), however, IoT devices have a variety of characteristics that are different from those of traditional electrical equipment, such as complex application environments, small installation space, energy supply difficulties, etc., which also puts forward new requirements for the development of ICs, based on which, this paper presents a certain analysis of the recent innovations in the field of integrated circuits (ICs) in the field of Internet of Things (IoT), which are important for solving the problems of IoT communication, energy supply, circuit design, security and confidentiality, etc. At the same time, the author also puts forward some of his own views on solving related problems. All in all, the article analyzes the problems and possible solutions of ICs in the field of Internet of Things and looks forward to the future development prospects. This is of some significance for the further development of integrated circuits in the field of Internet of Things.
Analysis of Barriers and Facilitators to Pregnant Vaccination Rates
Authors: He Ziwei
Published: January 2024

Many vaccines are suggested for pregnant women to protect fetuses, newborns, and women. However, the uptake of already-recommended vaccines varies and falls far below the expected level. Some barriers and facilitators made it less likely or more likely for a pregnant woman to accept a vaccination offered by a healthcare practitioner during her pregnancy. The most common reason for resistance the general population and medical professionals indicated was worry about the safety of vaccinations administered during pregnancy. Other obstacles were skepticism about the vaccine's efficacy, ignorance of the disease burden, and a belief that one is not in danger of contracting the infection. Strong national recommendations, especially the detailed safety information of vaccines for pregnant women and healthcare professionals who suggested their patients' immunization, were both critical facilitators for pregnant immunization. Immunized plans and recommendations are needed to increase the ratio of pregnant immunization. This article analyses the barriers and facilitators to pregnant vaccination rates and provides some beneficial suggestions for increasing willingness to immunization, thus protecting women, fetuses, and newborns from infectious diseases.
Dataset Analysis and House Price Prediction
Authors: Liu Junjie
Published: January 2024

The prediction of house prices through the analysis of data using machine learning and charts is a crucial and significant topic. Many scholars have conducted research in this area, providing valuable insights for both academic learning and real-world applications. The goal of this study is to predict house prices and thoroughly analyze the dataset. The methodology includes data cleaning techniques to ensure data quality. Additionally, three types of charts are employed to analyze the dataset effectively. Finally, two popular models are utilized to predict house prices, and their accuracy is evaluated. The results indicate that the Random Forest Regressor model is more suitable for the specific dataset, and the impact of each factor on house price prediction varies Looking ahead, future research will involve the utilization of more advanced models to further enhance prediction accuracy. This will enable realistic simulations and contribute to the ongoing development of the society. This study has made preliminary progress in data cleaning, dataset analysis, and predictive modeling. The use of charts provides a more intuitive representation of dataset characteristics. The findings have implications for the fields of data cleaning and machine learning.
Optimization of Map Matching Algorithm in Various Road Conditions
Authors: Liao Jingyang
Published: January 2024

Map matching refers to find the real driving trajectory of the vehicle by its GPS data. To solve this problem, most research focuses on improving the accuracy of GPS positioning. Even so, map matching still has a large deviation in complex road sections, such as interchanges, underground tunnels and other areas with high spatial complexity. At the same time, traditional map matching algorithms, such as hidden Markov model (HMM) and nearest neighbor algorithms, have the disadvantage of long running time. Different from the research on improving the accuracy of positioning, this research focuses on optimizing and creating a new algorithm for map matching. In order to solve the accuracy of map matching under complex road conditions, this paper adds a new attribute of altitude to GPS data for the first time, and greatly improves the accuracy of map matching in complex road conditions by constructing a three-dimensional hidden Markov model (3D HMM). In order to reduce the running time of the algorithm, this paper uses graph convolutional neural network as a bridge, integrates a variety of map matching algorithms and constructs a hybrid algorithm. Through experiments, it is found that the running time and accuracy of this hybrid algorithm are better than other algorithms.
Convenience Store Business Model and Success
Authors: Wang Jindi
Published: January 2024

This thesis starts with the Japanese convenience store 7-11 and analyzes the success of convenience stores and their irreplaceability compared to supermarkets. And then discusses with the actual situation of the Chinese market: First, the cross-regional expansion of international convenience stores from Taiwan, China to Beijing, Shanghai and Guangzhou and the emergence of local convenience stores with the river as the dividing line. The development of convenience stores in China today is analyzed and what needs to be improved, from the management of business strategy, store size and number to supply chain and logistics. Through the research and collation of store data, we arrive at a serious status quo of localization of convenience stores in China, as well as a unified integration into a comprehensive, nationally popular convenience store.
Analysis of the Close Relationship between Chinese Films and the Economy
Authors: Cai Yanzhuo
Published: January 2024

Due to the continuous economic development in recent years, there is a phenomenon that people begin to pursue spiritual satisfaction while meeting the basic material needs. Film is an important way of mankind's Daily pastime. As the consumer power in film increases, the economy of film production also develops. This article chose the Huayi brothers, the Light media, Wanda film, Chinese film co., LTD., 4 listed Chinese film and TV making company to analysis the relationship between the economy. Based on their financial statements, revenue expenditure analysis of their income in recent years as well as the spending of filmmaking, this study summarizes the close ties between Chinese movies and economic and carries on the development of some prediction. According to the analysis, China's film and economic relationship is mutual promotion, and after the outbreak of the new champions league era, the development of China's film will continue to accelerate. These results can help people understand more about the development between Chinese film and economy and the development background of Chinese film economy.
Stock Valuation and Risk Analysis Report: Real Estate Industry
Authors: Liu Tinghao , Qi Zhenglin , Tang Siyang
Published: January 2024

The real estate industry plays a fundamental role in laying the foundation for China's national economic development. Its contribution to driving economic growth, promoting social employment, and optimizing residents' living environments cannot be underestimated. Therefore, objective evaluation of real estate company value is of utmost importance. Investors typically utilize stock valuation models to assess the value of a company's stock. However, the theoretical valuations derived from these models often differ from the market value. This research focuses on an empirical analysis of stock valuation and actual pricing in the real estate sector, using the stock (code: 02007) issued by Country Garden Holdings as the case study. The average price-to-book ratio method is applied to theoretically value the stock, and the resulting valuation is then compared with the actual pricing. The analysis aims to uncover the reasons behind the differences between the two and identify the risk factors involved. The risk factors contributing to a lower stock valuation than the actual pricing is primarily associated with the overall impact of the real estate industry and Country Garden Group's operational risks. This study provides valuable insights for real estate companies seeking to improve their business operations and enhance their value creation capabilities. It also serves as a significant reference for investors when conducting stock valuations.
Application Of Sparrow Search Algorithm in Cold Chain Low Carbonization Logistics
Authors: Chang Xiaotong , Wang Jiaxi , Shen Xiaochi
Published: January 2024

Driven by consumer upgrades and national policies, the cold chain logistics industry has experienced rapid development, accompanied by increased expenditure of energy and carbon emissions. To achieve energy savings, emission reductions, and overall cost reduction in the cold chain logistics industry, this article establishes an optimization model for optimizing transportation routes, taking into account carbon emission costs, refrigeration costs, and time penalty costs. The objective is to comprehensively consider reducing refrigeration costs and time penalty costs throughout the entire phase of cold chain logistics, aiming to minimize the total cost for logistics companies during actual delivery processes. The improved Sparrow Search Algorithm (SSA) is employed to solve the optimization problem. The results of the case study analysis validate the applicability and superiority of the improved SSA for route optimization problems, as it demonstrates fast convergence speed and strong search capabilities.
Functional Data Clustering Method Based on Shape Information and Functional Mahalanobis Distance
Authors: Wang Zibing
Published: January 2024

Function-type data can provide insights into the internal structure of the data and facilitate the extraction of data features from the perspective of interactive derivative functions. The paper proposes a nonparametric clustering method for function-based data that incorporates first-order and second-order derivative function information into the Marginal distance for clustering function-based data. The method is based on the traditional K-means algorithm and is designed to cluster function-based data that contains rich shape information. The paper evaluated the performance of the algorithm of the text by comparing its purity and adjusted Rand coefficients against six other clustering algorithms on three different datasets. The results show that the algorithm of the text outperforms the other algorithms, demonstrating its outstanding performance, wide applicability, and practical significance in solving real-world problems.
Empirical analysis of stock prices based on ARIMA-GARCH
Authors: Feng Pu
Published: January 2024

Although ARIMA time series model can grasp the dynamic law of financial time series well, it can not reflect the volatility characteristics of stock price. GARCH can reflect the volatility of financial time series well and is suitable for forecasting in financial field. Taking the closing price of Shanghai Dazhong Public Utilities (dzgy) from January 2, 2019 to December 31, 2021 and using R , ARIMA-GARCH is proposed and the predictive analysis is carried out. The results show that ARIMA-GARCH has a good effect in short-term stock prediction, and has certain reference value and practical significance.
Research on field optimization model of heliostat based on ray tracing
Authors: Guo Jingfeng , Li Chenyang , Lu Hongyi
Published: January 2024

In this paper, the average optical efficiency and output power of the tower solar thermal power station are studied. The ray tracing method is used especially to the calculation process and details of the shadow blocking efficiency and collector truncation efficiency are carefully derived. Combined with intelligent optimization algorithm, the key parameters [1][2] of the mirror field layout are optimized. Then, the main method used in this paper is ray tracing. For the calculation of cosine efficiency and shadow blocking efficiency, the coordinate transformation matrix is established in this paper, which simplifies the coordinate calculation. For the calculation of collector truncation efficiency, based on Monte Carlo simulation, and an accurate collector truncation efficiency model is established by random sampling of large samples. Finally, MATLAB software is used to calculate the efficiency of the heliostat in different coordinate positions. The average optical efficiency (62.71%), cosine efficiency (75.65%), shadow blocking efficiency (94.54%), collector truncation efficiency (98.85%), thermal output power (34.77MW), and average annual thermal output power per unit area mirror (0.5535kW/m2) are obtained. This model not only helps to understand the propagation mode of light in the heliostat field, but also can quantitatively evaluate the loss of light.
Research on the Impact of the US China Trade War on the Economy of Other Regions of the World
Authors: Liu Zhongwei
Published: January 2024

In recent years, China's economy has developed rapidly, and the technology industry has made significant progress. The US launched a tariff-fueled trade war with China in 2018. The ongoing economic dispute, characterized by a series of tariffs, trade restrictions, and negotiations, not only affect themselves but also deeply on the rest of the world. This article is going to discuss how the trade dispute affects the global economy and the influences on each separate country. While some countries experienced benefits from the trade war, these advantages were often offset by broader economic uncertainties and disruptions caused by the trade tensions. The overall global economic impact of the trade war is negative and the benefits to certain countries are limited and temporary. Overall, the whole world's economy has benefited very little but has mostly been negatively affected by the trade tensions and trade war dynamics between the US and China.
Research on AI Commercial Application development
Authors: Xia Luyu
Published: January 2024

As the emerging industry continues to grow, there has been a rise in both the quality and quantity of AI products during the era of commercialization. This article aims to discuss the pros and cons of AI products and looks ahead to their commercialized development. The primary focus of this paper is to examine the current state and progress of AI commercialization by analyzing four aspects: AI-generated artwork technology, machine translation capabilities, and intelligent customer service to AI itself such as its lack of intelligence, limitations in creativity, copyright concerns, and social impact. increasing involvement in human society, it becomes crucial to establish a new human-machine ecosystem in this era under specific circumstances. In terms of politics, the " China 2025" policy proposed a means to integrate information technology with manufacturing processes – aligning with the trajectory of AI commercialization.
Analysis of the Principle and State-of-art Performances of Perovskite Solar Battery
Authors: Lin Shijia
Published: January 2024

As a matter of fact, the perovskite has been widely implemented in solar material due to the high convergence efficiency. With this in mind, this paper will analyze the principle as well as the state-of-art performances for the solar battery based on perovskite. To be specific, the brief history of the development of calcite solar cells was given. The basic perovskite crystal structure is shown simultaneously. Two structural types of the Perovskite solar battery: mesoscopic structure and planer heterojunction are introduced. Focus on the performance of the quasi-2D Perovskite Solar Battery. First, this study will show its structure and then show Characterization Methods and Features. The photovoltaic characteristics of Perovskite Solar Cells with various device architectures and various organic amine cations is given. According to the analysis, the applications of Perovskite Solar Battery with Greenhouses Technology as main object is shown. Overall, these results shed light on guiding further exploration of solar material.
Short-term Passenger Flow Prediction of Urban Rail Transit based on ARIMA Model
Authors: Chen Junqing
Published: January 2024

Urban rail transit is very important in modern urban transportation, which meets the needs of People's Daily travel. This paper aims to introduce the ARIMA model into the short-term passenger flow forecast of urban rail transit, analyze its principle and application method, and build ARIMA model combined with AFC data to forecast short-term passenger flow of urban rail transit. Through the research and improvement of ARIMA model, it is anticipated that it would give urban rail transport operators more precise and trustworthy short-term passenger flow forecasting capabilities, so as to realize more intelligent and efficient operation of urban rail transit system. In this study, the ARIMA model was established, and rigorous scientific methods such as residual test, autocorrelation function (ACF) and partial autocorrelation function (PACF) test, and comparison of predicted value and real value were adopted to conduct tests step by step according to the experimental process. Finally, it was confirmed that the excellent prediction accuracy of the ARIMA prediction model used in this paper, can provide accurate prediction results, and can be used in practical scenarios.
Future Trends in CAR-T Cellular Immunotherapy and the Pros and Cons in Cancer Treatment
Authors: Zhou Haoyuan
Published: January 2024

In recent years, the basic research of tumor immunology and the research of biotechnology have made rapid progress, which provides a profound knowledge base and technical reserve for the research and development of tumor immune drugs. The move helped make the topic of tumor cell immunotherapy a household word. As of May 2019, there were a total of 1011 cell therapies in the world, of which 568 CAR⁃T therapies, accounting for 56.2%, especially CAR⁃T cells for the treatment of blood tumors, which has achieved world-renowned efficacy. However, in the treatment of solid tumors, CAR⁃T cells have not yet shown extremely accurate inhibition of solid tumors due to the presence of immunosuppressive microenvironment, most of the features (signals) of abnormal antigens are expressed in normal tissues, and other complex factors. At present, domestic and foreign research on CAR⁃T cell therapy of solid tumor has been carried out in various directions and made some progress.
Analysis of the Impact of Transnational Cybercrime in Southeast Asian Countries on Global Social Development
Authors: Zhang Shuhan , Zhang Shuhan
Published: January 2024

Recently, the frequent occurrence of cybercrime has brought a significant negative impact on the development of society. Based on the geographical location of Southeast Asia, where the Golden Triangle region is located, there have been frequent outbreaks of fraud crimes in recent times. Therefore, this article takes Southeast Asia as the research object and focuses on the discussion of criminal incidents in the region. At the same time, the article provides relevant issues brought about by transnational crime and its negative impact on social development. Finally, the article elaborates on illegal activities, the construction of legal frameworks, global economic and political impacts, and how to combat crime. The research in this article has important practical significance in clarifying the dangers and threats of cybercrime and building a good social environment.
Analysis of the Impact of US Quantitative Easing Policy on China's Macro Economy
Authors: Tian Yulu
Published: January 2024

The 2008 financial crisis caused many large enterprises to go bankrupt. In order to revitalize the crumbling economy and inject liquidity into the financial markets, US has carried out four rounds of QE policy. Since the COVID-19, America has resorted to unlimited quantitative easing in hopes of saving economy. The United States' QE has an impact on China's economic development due to their frequent economic interactions, and this impact will unavoidably spread as a result of QE's spillover effects. This research examines the Fed's QE monetary policy influence on Asian's biggest country economy in two time period, after the 2008 financial crisis and during the new coronavirus pandemic, in depth using current theories. In this study, the content of the QE monetary policy in the American continent is introduced, the implementation backdrop and impact of the policy are examined. The main focus of this paper is to present the impact of US QE monetary policy on China’s economy. First of all, US policy impact will inevitably spread to China's monetary policy and exchange rate policy. Secondly, the QE’s spillover effect of Chinese inflation is analyzed from RMB appreciation and commodity price rise. Third, the capital market's strong liquidity will lead to the inflow of international capital into our country due to the United States' QE monetary policy, so the impact on our capital market is analyzed. Fourthly, it analyzes the impact of dollar depreciation brought about by QE on the China's foreign exchange assets safety.
Microneedle-array patch system applications in diabetes
Authors: He Siwuxie
Published: January 2024

Diabetes is turning into a chronicle disease with further improved drugs and more facilitated delivery systems coming out. An essential part of the drugs is insulin and its analogs that patients with diabetes use to control their blood glucose levels. The conventional treatments, like injection and open-loop (release are not responsive) transdermal delivery, are short of maintaining glucose levels in the expected range incurring risks of hypoglycemia. Nevertheless, closed-loop drug delivery shows high potential as its release response to glucose levels dynamically. In the transdermal delivery field, microneedle (MN)-array patch systems presented great capability in transdermal delivery and manipulation. So, the glucose-responsive MN-array patches that make progress in safety and convenience were drawing worldwide focus. This review provides an overview of the topic and presents some advanced outcomes.
The Investigation on Anime-Themed Recommendation Systems
Authors: Chen Jiyue
Published: January 2024

In today's digital era, the way we enjoy entertainment has experienced a significant revolution, and this transformation also encompasses the world of anime. With a seemingly endless array of anime series accessible through online streaming services, users frequently grapple with a formidable dilemma: the paradox of abundance. This paper introduces a sophisticated anime recommendation system, carefully crafted to tackle this quandary and enhance the overall anime-watching journey. Drawing upon the capabilities of machine learning and data analysis, the system's primary goal is to provide personalized anime recommendations based on user preferences and behavior. This paper not only outlines the development of an intelligent anime recommendation system but also takes a critical look at the existing body of research in the fields of recommendation systems and anime-related studies. Emphasizing the significance of personalized recommendations, it highlights the crucial role they play in enhancing user engagement and satisfaction within the world of anime streaming. The system itself is a culmination of various techniques and methodologies, employing a hybrid approach that combines collaborative filtering, content-based filtering, and advanced machine learning techniques. Linear models, random forests, and boosting algorithms are skillfully harnessed for prediction purposes, showcasing the system's versatility and adaptability. Preliminary results presented in this paper offer a tantalizing glimpse into the system's potential to deliver tailored recommendations, ultimately enriching the user experience and fostering greater engagement with the captivating universe of anime.
Prediction Of Vegetable Pricing and Replenishment Based on ARIMA Model
Authors: Meng Dewang , Jiang Xingyu , Xie Zhongjun
Published: January 2024

Vegetables are indispensable consumer goods in the daily diet of the majority of consumers. Reasonable pricing and replenishment strategies of vegetables are conducive to maintaining the interests of agricultural producers and promoting the stable development of the market. The main contents of this paper are two points: one is to visualize the pre-processed data and establish the distribution map of vegetable sales in recent years; Secondly, the ARIMA time series prediction model was established by linear fitting of the data, and the feasibility test of the prediction results was carried out to obtain the total daily replenishment quantity and price of each vegetable category in a period of time. Under the background of the new era with low-carbon green as the mainstream, this research has broad development space and prospect. The pricing and replenishment strategies formulated in this study can reduce the waste of vegetables in the whole consumption supply chain, maintain the purchasing power and living standard of consumers, and meet the market demand. Marketing techniques that promote healthy foods in supermarkets are important to encourage healthy eating at the population level. The content of this study can provide ideas for the optimization of vegetable supply chain, further use of new technology, reduce waste, improve efficiency, and ensure the quality and supply stability of vegetables. This study is also helpful to analyze consumer behavior and understand consumers' reactions to vegetable price fluctuations and changes in purchasing behavior in order to better predict market trends and adjust production and supply strategies.
Investigation Of the Biodegradable Plastic and The Application by Cornstarch and Kappa-Carrageenan
Authors: Luo Mingchuan , Qin Shizhe
Published: January 2024

By comparing the manufacturing of conventional plastic with biodegradable plastic, a brief investigation of plastic and future developing trend was done. It is essential to investigate a biodegradable polymer which is produced with low cost and recyclable resources. An experiment was carried with cornstarch and kappa-carrageenan, which aim to produce a natural polymer can be biodegradable and has similar properties to conventional plastic. This experiment focuses on the mechanical properties and solubility of different amount ratio of the dry components to find out whether it has any functions that can be use in daily life. The results show the membrane with higher ratio carrageenan represents lower solubility, better mechanical properties and water resistance, but these properties become weaker in dry environment. The results provide a theoretical basis of the application of this polymer in medical region and food packaging.
LR-GA Algorithm Based Study on Vegetable Replenishment and Pricing Decision Making
Authors: Liu Zixuan , Yang Xiaoyu
Published: January 2024

The sales volume and sales price of vegetable products fluctuate greatly due to factors such as origin, variety and freshness period. Therefore, rational replenishment and pricing decisions are particularly important for supermarkets. Therefore, this paper proposes a replenishment and pricing strategy model for vegetable products based on linear regression-genetic algorithm. In this paper, all vegetable commodities are first classified into four categories using K-mean cluster analysis, and the sales performance of the four categories is observed to understand their sales behaviors and provide references for sales strategies. Then, the cost, price and profit margin of each vegetable commodity are calculated using the weighted method, and the linear regression equation between the sales volume of vegetable commodities and the weighted sales price is given. Finally, using the total profit formula considering the loss rate of each item as the objective function and the linear regression equation between the total sales volume of each vegetable item and the weighted sales price as the constraints, the optimization search is carried out by using linear regression and Genetic Algorithm (LR-GA) to find out the sales price and the sales volume under the maximum profit so as to realize the sales strategy.
Causes and Analysis of Sex Discrimination in Price Discrimination
Authors: Liu Zhuoran
Published: January 2024

Price discrimination in marriage and gender discrimination in the labor market are common problems in Chinese society. By exploring the pressure and impact of these issues on men and women, this article analyzes the excessive financial pressure that men bear in marriage and the various unfair treatments that women encounter in the labor market. In response to price discrimination against women in the labor market, this article puts forward a series of policy recommendations, including improving relevant laws and regulations to protect women's legitimate rights and interests, increasing penalties for gender discrimination by employers, and improving social concepts to promote gender equality. By releasing women's productivity and enabling women to earn income independently to support their families, it can reduce men's financial pressure in marriage and achieve the best of both worlds for social development goals. The innovation of this article is that it deeply explores gender issues in marriage and the labor market in Chinese society and puts forward feasible policy suggestions for these issues. Through the research of this article, People can deepen people's understanding of gender discrimination, promote the change of social concepts, create a more equal and just social environment, and achieve sustained social stability and sustainable development.
Research On MQL Flow Rate Based on CNC Milling of Aircraft Structural Parts
Authors: Lin Haifeng
Published: January 2024

Micro lubrication technology (MQL) has been widely applied globally, mainly focusing on the design of lubrication mechanisms. There is a lack of research on the flow rate under actual processing conditions. The size of cooling capacity affects manufacturing costs, environmental governance, workpiece quality, and other factors. This article conducts research on the MQL flow rate of oil gas mixed lubrication, and experimentally obtains MQL flow parameters suitable for aircraft structural component processing.
The Impact of Corporate ESG Performance on Corporate Green Innovation
Authors: Hang Lanqi , Wang Longze , Xu Peiqi
Published: January 2024

The incorporation of green innovation by firms is considered essential to attain superior developmental outcomes. This study aims to examine how ESG (Environmental, Social, and Governance) performance influences green innovation and delve into the mechanisms that facilitate its implementation based on data spanning from 2011 to 2021, with a particular emphasis on companies listed on the A-share market in China. Its primary. The research findings substantiate that robust ESG performance by enterprises plays a pivotal role in driving green innovation. This influence can be attributed to several key factors within the implementation mechanism. Firstly, companies exhibiting excellence in ESG performance tend to demonstrate heightened social responsibility. Secondly, commitment to comprehensive and transparent information disclosure practices is more pronounced among such companies. Lastly, easier navigation of financing constraints is often observed, facilitating their green innovation initiatives.Drawing upon this analysis, valuable suggestions are proposed, emanating from ESG information disclosure practices and their influence on fostering green innovation. The study underscores the importance of integrating environmental, social, and governance considerations into corporate strategies as a means to usher in an era of sustainable, high-quality development for firms.
Preface: 2023 International Conference on Computer Simulation Technologies and Mathematical Modeling (CSTMM 2023)
Authors: Perkin Andre , Wang Shuai
Published: January 2024

We are proud to organize the 2023 International Conference on Computer Simulation Technologies and Mathematical Modeling (CSTMM 2023), which was held on September 2-3, 2023, in Wellington, New Zealand. Mathematics is a pre-requisite in advancing many fields, including science and engineering. The conference was aimed to provide a platform for academicians and researchers to meet, exchange ideas and present the latest findings involving mathematical applications in various field of studies.

Participants from many countries attended the conference. This publication contains most of the papers presented during the conference. All papers selected here were subjected to peer reviewing process. As such, we would like to thank all reviewers, type-setting editors, and last but not least all committee members for the successful publication of this proceedings.

CSTMM Conference Organizing

Wellington, New Zealand
The Development of Green Bonds: Current Issues and Solutions
Authors: Zhang Zihan
Published: January 2024

The increasing deterioration of climatic issues in recent years promoted the development and the necessity of green finance, and green bonds have also developed rapidly under the opportunity. The purpose of this paper is to review the development of green bonds to figure out issues encountered in development and corresponding solutions. The main body of this paper can be divided into three sections. The first section of this paper concentrates on the historical development and current status of green bonds. The second and third sections first concentrate on analyzing issues that influence the development, then focusing on solutions from the viewpoints of investors, government, and issuers respectively. The results revealed that both historical and current overall development of green bonds shows positive; the issue of greenwashing can be solved with the policy of Third-Party Certification and enhancing investors’ perceptions; the issue of financial performance can be improved by enhancing liquidity and fixed-income assessment; the barriers of globalization can be solved by setting up green investment banks in developing regions, enhancing regional relationships and setting forward contracts. It also provides suggestions for three parties: local government, global organizations, and issuers to carry out the solutions better. This paper contributes to further investigating the development of green bonds, which is conducive for researchers intending to study in related dimensions.
Analysis on the Development, Sales and Development of New Energy Vehicles by BYD Company
Authors: Chen Sheung Leong , Li Wenting , Liu Yijun
Published: January 2024

With the continuous improvement of the transportation system, the increasing demand for transportation tools by the people, and the increasing awareness of environmental protection among the global public, new energy vehicles have been widely favored, and the sales of new energy vehicles by BYD, which is committed to research on new energy vehicles, have also significantly increased in recent years. Based on the financial statements and other data released on BYD's official website, this paper conductes SWOT analysis, financial statement analysis, and marketing strategy analysis to study the overall operating status of the company and the development and sales of new energy vehicles, and proposed corresponding suggestions for its shortcomings. Research and analysis have found that due to BYD's overall good business performance in recent years, it has invested a large amount of funds and human resources in the research and development of new energy vehicles, sales, and gradually expanded overseas markets. In recent years, especially in the Chinese market, sales have continued to rise, and brand influence has further expanded.