bluuebunny/crossref_metadata_2025 huggingface dataset:
The Investigation of Music Recommendation Systems
Authors: Yu Shengqi
Published: January 2024

A recommendation system represents a machine learning technique that examines and presents user preferences derived from their online activities. In today's digital landscape, recommendation systems find widespread use in short video platforms. These systems scrutinize user actions such as search history and viewing patterns to proactively suggest videos aligned with individual tastes. Leveraging an effective recommendation system to propose high-quality videos tailored to user preferences proves advantageous in sustaining user engagement and boosting platform traffic. Nonetheless, users with specialized interests or newcomers to the platform may receive less accurate recommendations due to limited data availability. The development of an artificial intelligence-based recommendation system can significantly expedite product searches, enhance search precision, foster user loyalty, augment average order values, and bolster overall conversion rates. In the realm of artificial intelligence applications, recommendation systems have become indispensable components. This paper delves into the algorithms for automatically analyzing and recommending music based on users' historical playback records. The study employs a random forest model to train the recommendation algorithm.
From Tesla's Price Strategy to Reflects the Overall Industry Trends of Electric Vehicles in China
Authors: Yan Jiecheng
Published: January 2024

This essay explains and focuses on the decreasing price strategy Tesla has adopted in 2022 and 2023. The cost of lithium batteries has decrease in 2023. The demand for electric vehicles is still high, due to the global trend of lowering carbon footprint and the tax reduction policy in China. To increase sales, Tesla decided to decrease the selling price of Model 3 and Model Y, both designed for middle-level income customers. By analyzing the financial ratios, it is proved that the pricing strategy was successful, and Tesla could tolerate the failure if this strategy couldn’t work out in the long run. The electric vehicle market in China is becoming saturated. There will be a price war in the future, and many brands might disappear because of this. Tesla should retain its brand independence and spend more on research and development to further increase its market share. From Tesla's Price Strategy to Reflects the Overall Industry Trends of Electric Vehicles in China.
Hydrogen Fuel's Challenge to Lithium Batteries in Advancing Electric Aircraft
Authors: Liu Zhexing
Published: January 2024

In today's modern society, more and more technologies are gradually emerging from the surface. Capitalists led by Musk have gradually embraced global technology. From electric vehicles to artificial AI, modern technology has gradually anthropomorphized. The most prominent is electric vehicles. With the rise of electric vehicles, it has brought not only the progress of science and technology, but also brought fresh blood to the automobile market. Electric vehicles have brought not only higher speed and efficiency, but more importantly, it has brought significant progress to environmental pollution and residents. Even if electric vehicles have become more popular cars on the market, the problems it faces are also challenging, because hydrogen fuel cells are gradually replacing lithium batteries. Although they cannot be surpassed in a short period of time, it is unknown whether more time and higher efficiency can surpass lithium batteries. This article will be compared through car brands, cost, market prices and environment. The main analysis is to compare the different materials and technologies used by different electric vehicles, and make a relatively important analysis and think about them from money and environment to determine whether hydrogen fuel cells can surpass lithium batteries or help each other in the future based on the results obtained.
A Study on Short-Term Passenger Flow Forecasting for Urban Rail Transit
Authors: Fan Zihan , Si Jiaqi , Wang Yiqian
Published: January 2024

Short-term forecasts of light rail traffic are an indispensable basis for adjusting timetables in real time, improving operational efficiency and providing passengers with informed travel recommendations. At the same time, the subway is the most convenient and widely used mode of transport for people today. The purpose of this paper is to forecast passenger traffic in the subway. To solve the problem of predicting short-term passenger flow at the entrances and exits of metro stations with nonlinear and stochastic characteristics, this paper uses a genetic algorithm (GA) based on ordered long-term and short-term memory (SLSTM) and builds a GA-SLSTM forecasting model to predict future short-term passenger flow by studying the patterns and characteristics of passenger flow in historical data. The model consists of five stages: data preprocessing, model training, model evaluation, and forecast application. Through these steps, the GA-SLSTM model is able to predict the future situation of short-term passenger traffic based on the characteristics and patterns in historical data, providing a reference base for planning and optimizing urban transport.
Design and Analysis of a Bionic Skate Based on MPF Movement Patterns
Authors: Yan Tielin , Li Xiaochun , Li Zengrui , Feng Yiran
Published: January 2024

This paper uses pectoral fins fluctuation pattern class triangular skate as the object of study. The skate generates waveforms through its broad pectoral fins, which are transmitted backwards to push the water backwards, and the reaction force of the water obtained is the forward thrust i.e. the MPF pattern. The fins are designed to meet the fluctuation pattern of the sinusoidal function. A prototype pectoral fin of the ray is analysed to establish the kinematic model of the fluttering wing, the envelope coefficients are designed to decouple and simplify the kinematic equations, and a three-dimensional mesh is drawn using MATLAB; fluid simulation is carried out by Fluent to obtain the vortex cloud; the bionic ray is tested and tested to meet the actual requirements.
Motivations And Effects of NEEQ's Transfer To SSE STAR Market In The Context Of Registration Reform: A Case Study Of TZTEK
Authors: Liu Xinrui
Published: January 2024

NEEQ, officially known as the National Equities Exchange and Quotations, is the third national equity trading venue after Shanghai Stock Exchange and Shenzhen Stock Exchange. The National Equities Exchange and Quotations Corporation Limited (NEEQ Co. Ltd.) was registered with the State Administration for Industry & Commerce (SAIC) on September 20, 2012 with registered capital of RMB 3 billion, and was inaugurated on January 16, 2013 and gradually opening up to all regions nationwide. For small and medium-sized enterprises (SMEs), NEEQ offers a vital financing channel and enhances their liquidity. As a result, the number of enterprises listing on the NEEQ market has surged. However, this growth has brought about certain issues that cannot be ignored and have become increasingly serious. These issues include a high concentration of equity ownership and a decline in market liquidity. Consequently, the trading volume and turnover rate of NEEQ-listed companies have been decreasing year by year. This decline has significantly constrained the growth potential of some promising enterprises, such as TZTEK. These companies, which typically have good growth prospects, are often compelled to consider transferring to a different board in pursuit of sustainable development. This paper will first introduce the research significance and background of this chosen topic. Secondly, it will provide an overview of TZTEK's background of board transfer and transfer process. Then, it will analyze the motivation behind TZTEK's board transfer from the perspectives of financing, shareholder structure, and company valuation. The study will also involve an analysis of market effects, growth capability, and debt repayment capacity for TZTEK, both before and after the board transfer, using a series of relevant data. Finally, the paper will conclude with a summary of the research findings.
An FPGA-Based Adaptive Solution for Synchronous Configuration in UART Communication
Authors: Shao Ziyi
Published: January 2024

To address the challenges associated with data reception failures, which arise due to abrupt alterations in the baud rate and the data format of the transmission signal in traditional Universal Asynchronous Receiver-Transmitter (UART) scenarios, this study presents an adaptive UART parameter solution underpinned by Field-Programmable Gate Array (FPGA) technology. Initially, this manuscript elucidates the underlying principles of UART communication and delineates the pivotal constituents of the UART protocol. Subsequently, it offers an in-depth analysis, from the transmission perspective, of how specific parameters influence the effectiveness of the UART protocol. Based on the software and hardware embodiments associated with the dual primary functions – baud rate adaptation and data format adaptation – this paper extensively details the flow chart for baud rate adaptation, the circuitry for edge detection, methodologies for baud rate computation, and the parameter eigenvalue approach. Following this, Verilog, a hardware description language, is employed for coding and subsequent simulation within the Quartus II environment. Empirical evidence corroborates the efficacy of the proposed design in achieving synchronous configuration between the baud rate and the data format. The findings of this research bear substantial implications for augmenting both the adaptability and dependability of UART communication systems.
The Relationship between SOFR and Market Yield of U.S. Treasury Securities
Authors: Liang Zaibo
Published: January 2024

This paper introduces the characteristic of the new benchmark rate Secured Overnight Financing Rate (SOFR), explain its connection to the futures price, and show its potential to provide new insight into the argument on interest rate term structure. Based on the future price discovery theory, this study set up a hypothesis that short-term interest rates should contribute to forecasting long-term ones. The causality between interest rates in different terms of, which are separately represented by bilateral repurchase rate and the market yield of long-term U.S. government bonds, is explored in this research using the VAR model, as well as the Granger causality test. The conclusion of this research proves the hypothesis and indicates a single-direction causality between interest rate of different terms. However, the research also has drawbacks such as ignoring non-linear relations and evading the change of government policy. These problems need to be solved in the following study.
The Influence of Institutional Investors' Clustering Behavior on A-Share Stock
Authors: Wang Kai
Published: January 2024

Institutional investors' "clustering" behavior can have significant implications for the stock market, especially concerning its stability and the efficiency of the price discovery mechanisms. Recognizing this, this research utilized regression models to rigorously analyze the effects of such clustering practices on the abnormal returns and volatility of stocks that are targeted by Equity-oriented funds. This research also implemented a T-test to differentiate the impacts of various variables in both bull and bear market scenarios. The findings underscore that within China's A-share market, equity-oriented fund tend to favor certain sectors, with a significant inclination towards the manufacturing and finance sectors. Furthermore, the clustering behavior exhibited by these investors has diverse effects on stock abnormal returns and volatility, contingent upon the time scales and prevailing market conditions. This discovery provides insights into institutional investment strategies and the overarching stability of the market. For individual investors, it's crucial to note that stocks with heavy institutional ownership might exhibit increased volatility, particularly in bear market conditions. Therefore, incorporating this understanding could be important in investment decision-making processes.
Health Implications from the HIIT-Caused Alteration of Gut Microbiota
Authors: Zhu Haotong
Published: January 2024

The term "gut microbiota" usually refers to various microorganisms that coexist in the colon and other regions of the gastrointestinal tract. These microorganisms are necessary for the digestion and breakdown of food, the production of certain vitamins, and the preservation of a strong immune system. Simultaneously, high-intensity interview training (HIIT) has been found to have several ways of changing gut microbiotas. Exploring the relationship between HIIT-caused alterations of gut microbiotas would be beneficial to the guidance of further application of exercise science. This review aims to synthesize current evidence on the impact caused by HIIT on gut microbiota and its potential health implications. HIIT-induced alterations in the gut microbiota may help prevent and treat illnesses including obesity, psychological issues, and metabolism. As a potential regulator of the makeup of the gut microbiota, HIIT appears to have important health implications. For the purpose of creating novel techniques to advance general health and resist a variety of potential risks to health, understanding the complex interaction between HIIT and the gut microbiota holds promise.
How Can Energy-Importing Countries Guard Against Geopolitical Risks - Take Japan as an Example
Authors: Wang Ruofan
Published: January 2024

With the gradual decline of global economic growth, the world economic cycle is facing an important turning point at present, and various geopolitical crises have occurred one after another. Under this background, energy security risks of energy-importing countries have become increasingly serious. Therefore, it is particularly important to study the function principle and risk avoidance means of geopolitical events affecting energy security. This paper selects Japan, which has a very low energy self-sufficiency rate but achieved good economic development and energy security after World War II, as the research object, and selects the second oil crisis, the Great East Japan earthquake and nuclear leakage, and the novel coronavirus epidemic as the representatives of three geopolitical events to analyze the changes in Japan's energy structure and the policies and measures of the Japanese government. It is found that geopolitical events can affect a country's energy structure and energy strategy from three aspects: energy supply, energy demand and international relations. Finally, based on the experience of Japan, this paper provides reasonable suggestions for energy-importing countries to prevent and resolve the energy security risks caused by the geopolitical crisis.
Research Progress in Respiratory Syncytial Virus Vaccines
Authors: Yu Hemeng
Published: January 2024

In addition to being a substantial source of morbidity and mortality in older persons, respiratory syncytial virus (RSV) is a major contributor to lower respiratory tract infections in newborns and young children. Worldwide, there has been a lot of research done to provide safe and effective vaccinations against this common infection because there isn't an approved RSV vaccine. A succinct summary of current developments in RSV vaccine research is given in this abstract. Many vaccinations have reached the clinical testing stage and shown promising benefits. Live attenuated vaccines, nanoparticle vaccines, and viral vector vaccines are the three primary categories of current vaccination techniques. Additionally, the production of specific RSV antibodies such as MEDI8897 and polyclonal immunoglobulin RI-002 is being evaluated as an important research antibodies for avoiding RSV infection. The continuous dedication to RSV vaccine development gives optimism for the future prevention of RSV-related disorders across all age groups, despite the fact that challenges still exist, particularly ERD (Enhanced respiratory disease).
Research for the Business Role and Value of AI in the Medical Industry
Authors: Li Runze , Yuan Ping
Published: January 2024

This paper discusses the development of AI in healthcare, from the past to the present, and the future. We carefully analyzed the process of AI penetration into the medical field and also envisioned the future development of AI in the medical field. Because of AI's excellent computing power and analytical capabilities, it has a great impact on the medical industry. This paper describes the use and value of AI and sorts out the relationship between advantages and disadvantages from the aspects of image diagnosis, pharmacy, ChatGPT and human-computer interaction equipment. Based on recent research, the position of AI in the medical field is demonstrated from multiple perspectives, and their future market is speculated, for various reasons, some development cycles are relatively long, and many aspects need to be considered. Finally, this article presents some of the existing problems of AI in healthcare, from different aspects of patients, hospitals and doctors, and then gives different solutions.
Investigating the Roles, Influencing Mechanisms, and Outcomes of Private Equity and Venture Capital on Companies in High-Tech Renewable Energy Sectors
Authors: Wang Julie
Published: January 2024

Along with many environmental issues arising, such as climate change and extreme weather disasters, there has been a gradual increase in recognizing the importance of promoting green practices. Venture capital investors evaluate significantly more the environmental impacts of the business, and what the company has done to have a positive impact not only socially, but also on sustainability. Therefore, today, when analyzing a firm, the Environmental, Social, and Governmental (ESG) framework is considered in-depth. In this paper, the mechanisms behind PE/VC investment in renewable clean energy sector startups will be investigated. In addition, the influencing mechanisms, factors considered by PE/VC investors, and the characteristics of successful clean energy startups will be covered. Investors will then be able to make more informed decisions about prospects, potential growth, and development of this industry, while also examining why certain startups are successful as opposed to the countless others that collapse, aligning with the high-risk return balance of such an industry that has relatively greater levels of risk than others.
Fluctuations in Chevron's Share Price in the Context of the Russia-Ukraine War
Authors: Hu Danyang
Published: January 2024

The Russia-Ukraine war led to disruptions in the global energy supply chain and increased inflation. Western countries imposed sanctions to restrict Russian energy exports, triggering market shocks. This essay analyzes how the confrontation between Russia and Ukraine on February 24, 2022 may affect stock markets and energy markets throughout the world. The article selects the closing price of Chevron's stock from January 3, 2011 to July 28, 2023 as the raw data, and uses an ARIMA model to analyze the changes in Chevron's stock price and demonstrate the war between Russia and Ukraine's effects on it from multiple perspectives. It has been discovered that geopolitical developments may possess a significant short-term influence on stock values, but over time, the market gradually shifts its focus from a single event to a wider range of market factors, thus weakening the impact of geopolitical events on stock prices. This paper aims to fill the research gap on the stock price reactions of oil and gas companies in the face of conflict by analyzing the stock price changes of the energy company Chevron to show how global developments affect the American energy market, and to aid investors in evaluating the risks and possibilities, as well as to shed light on the market volatility and long- and short-term impacts of the energy sector. Finally, the paper provides investment recommendations that summarize the main points of the full paper.
Current Status, Development, And Application of Optimization Methods for Analog Circuits
Authors: Liu Manqi
Published: January 2024

The optimization of analog circuits has always relied on the experience and intuition of engineers to find suitable parameters to meet the requirements of the circuit, which is time-consuming and costly. This paper outlines and analyzes the optimization methods for analog circuits in recent years, and draws some summaries that can be used as references for subsequent optimization circuits. The optimization of analog circuits is mainly divided into the optimization of the performance of the hardware in the circuit and the optimization of the circuit structure. Hardware optimization, this paper mainly focuses on the optimization of diodes, transistors, field effect tubes and operational amplifiers, the four main hardware optimizations, from the material, structure, production process and other aspects of the analysis. For the optimization of circuit structure, this paper mainly analyzes from the aspects of algorithms, mathematical models, and the use of integrated methods. The significance of these optimization methods and the outstanding advantages and main application directions of different methods are further explained. The search for optimization methods can reduce the high time cost of analog circuit optimization that is purely dependent on experience and intuition, and is significant in increasing efficiency.
A New Design of A 6-Bit Absolute Value Detector by Using Both VDD Scaling and Sizing to Optimize
Authors: Liu Xuancheng , Wu Jianying
Published: January 2024

The presented paper focuses on the development and optimization of a 6-bit absolute value detector, a crucial digital block in encoder and decoder applications. The primary objective is to minimize energy consumption while maintaining a delay no greater than 1.5 times the minimum delay. The optimization process combines logical effort theory with gate sizing and voltage scaling techniques. Firstly, gate sizes are adjusted while keeping VDD constant, achieving a 73% reduction in energy consumption, reaching a delay constraint of 1.5 times the minimum delay. Secondly, VDD scaling is explored without altering gate sizes, resulting in a 40% reduction in energy consumption, reaching the minimum energy consumption point. Finally, gate sizing and VDD scaling are combined, yielding a remarkable 79% reduction in total energy consumption, with a supply voltage of 0.835 volts. These optimization strategies bridge a research gap in 6-bit absolute value detectors, significantly enhancing energy efficiency and offering valuable insights for intricate digital signal processing scenarios. The findings showcase the effectiveness of combining logical effort theory with gate sizing and voltage scaling to achieve substantial energy savings while meeting stringent delay constraints.
Prediction of Performance for Sony in Financial Market
Authors: Pi Guanpeng
Published: January 2024

Sony Corporation has an enormous impact on society these days. It’s a company majoring in technological innovation, with products like game consoles, cameras, headsets, and televisions. Most of them are the best in the business. With an income of 8,994 trillion yen in a single year, the massive company remains competitive around the globe. It would be essential to predict the future trend of a company that is still making contributions to the world. Expectations on the project is to predict Sony Stock Market. To achieve this goal, Long Short-Term Memory, known as LSTM and Linear Regression are implemented in the project. By first importing the data, dividing it into the training and testing set, and then creating LSTM and Linear Regression model, the result will be provided by the program. Using two models to predict the stock market made comparisons possible. According to the MSE (Mean Square Error), it’s safe to make the conclusion that LSTM is a more reliable way when predicting the stock market for Sony Corporation.
Analysis of the Designs and Applications of AI Chip
Authors: Li Xinnuo
Published: January 2024

The rapid evolution of deep learning model architectures and the increasing scale of model parameters have imposed heightened demands on deep learning training, inference, and deployment, leading to the swift advancement and unprecedented prosperity of AI chips. Therefore, this study sets out to analyze the designs and applications of AI chips by considering their unique requirements compared to conventional chips, and by combining software and hardware aspects. The paper delineates the classification of common AI chips along with their distinct design strategies and optimization algorithms. It commences with the fundamental hardware design of AI chips, elucidating the basic design process and addressing the specialized demands of AI computation, particularly data parallelism and storage optimization. Subsequently, transitioning to the manufacturing process, it examines how current AI chips circumvent fabrication bottlenecks and achieve significant breakthroughs in architecture and performance through chip stacking techniques. The paper then bridges hardware and software through the AI compiler, expounding on model optimization approaches, e.g., quantization and pruning, completing the comprehensive journey from AI chip design to deployment. It identifies current developmental challenges in the AI chip realm and provides a glimpse into future prospects. Through a holistic perspective spanning design, manufacturing, algorithms, and applications of AI chips, this paper offers insights that steer upcoming innovations and practical implementations in artificial intelligence, paving the way for a dynamic future in AI chip development.
Application of Immune Checkpoint Inhibitors in Advanced Melanoma
Authors: Zhang Naran , Zheng Yule
Published: January 2024

The advent of ICIs has significantly improved outcomes for many types of cancer treatment, including advanced melanoma that cannot be respected. Among melanoma patients, there is clear evidence that Ipilimumab, the first monoclonal antibody approved for CTLA-4 targeting, as well as nivolumab and pembrolizumab, which concentrate on PD-1, have led to increased overall survival. Combination therapy with other therapies shows better efficacy with ICI compared to monotherapy (e.g., a combination of CTLA-4 and PD-1 inhibitors). This article will explore recent research on the therapies of advanced melanoma, investigate the pathways of CTLA-4 and PD-1/PD-L1 and their application as single therapy or combination with other therapies such as PD-1 drugs, in addition to other therapeutic methods, and the current application of TCM treatment. In addition, this review will discuss drug resistance to ICI treatment and explore potential biomarkers associated with ICI response in advanced melanoma patients and future prospects for ICI treatment.
Warner Bros. and the DCEU: The Interplay of Financial Interaction and Strategic Decision Making
Authors: Hu Senyang
Published: January 2024

Superhero movies are now an essential component of the worldwide film business, drawing hundreds of millions of spectators to theatres each year to watch them. The DC Extended Universe (DCEU) from Warner Bros. is one such film series that has significantly contributed to the industry. But the film industry's intricacy extends beyond box office success. A company's entire decision-making, marketing approach, and long-term goal planning, may be significantly impacted by the success or failure of its films. This connection has grown even more complicated, especially after Warner Bros. and Discovery, Inc. merged. This essay will examine the financial effects of the DCEU's performances on Warner Bros. and how those decisions have further shaped the DCEU's future course. This essay will also examine how Warner Bros. exploited its success in the movie business to develop its strategic objectives for the future and what this means for the movie business. The analysis shows that the collaboration between Warner Bros. and the DCEU moulded their own trajectories and established a standard for other studios to follow in the ever-evolving film business.
Examining the Progression of Blockchain Technology and Its Implementation During Digital Economy
Authors: Li Mingxuan
Published: January 2024

Blockchain technology is a peer-to-peer, distributed, and innovative database and disruptive information technology. It has features such as decentralized organization, tamper resistance, and anonymity. It has become the most critical element in developing a new generation of information infrastructure in China and a core component in driving the digital economy. Blockchain relies on the Internet ecosystem, providing not only the foundation for trusted protocols but also unlimited potential applications in inclusive financial services, digital assets, e-government, and other fields. It integrates the most advanced information technologies in modern society, making it of great significance in reshaping and developing the digital economy. This article explores the characteristics and development history of blockchain technology, as well as its current research status and potential theoretical value and practical significance when applied to digital economic scenarios. At the same time, it will discuss the current limitations of blockchain research, possible future directions, and development methods.
Smart Home Powered by New Energy: Energy Management Systems (EMS) Technologies and Future Prospects
Authors: Chen Xinxi
Published: January 2024

The world needs to switch to sustainable energy sources, and smart homes are emerging as a key frontier in this shift. Energy Management Systems (EMS) are essential in this situation for maximizing energy use and guaranteeing effective use of renewable resources in residential settings. Integrating new energy sources with the changing needs of contemporary households is a challenge. This analysis explores cutting-edge EMS systems designed for smart homes, highlighting its potential for utilizing renewable energy sources like solar and wind. Our thorough research shows that combining artificial intelligence with optimization techniques like particle swarm optimization opens up interesting new directions for demand-side management and dynamic energy scheduling. These developments redefine our notion of sustainable household energy management while also improving the efficiency of smart houses. In essence, the combination of EMS with smart home technologies ushers in a new era in domestic energy, paving the way for a more environmentally friendly and economically sensible future.
Comparative Analysis of Operational Advantages and Disadvantages Between Conventional Internal Combustion Engine Vehicles and Electric Vehicles based on Tesla
Authors: Zheng Jingyan
Published: January 2024

The automotive industry is undergoing a transformative phase driven by concerns over environmental sustainability, energy efficiency, and technological advancements. In this context, the shift from conventional internal combustion engine vehicles to electric vehicles (EVs) has emerged as a focal point. This paper conducts a comparative analysis of operational pros and cons between conventional internal combustion engine vehicles and electric vehicles, using Tesla as a case study. This paper undertakes a comprehensive comparative analysis of financial and operational aspects among leading automotive companies: Tesla, Volkswagen, and Toyota. This comparative exploration highlights the transformative potential of the new energy vehicle sector.
Impact of Macroeconomics Variables on Stock Market Indices During the period 2010-2020
Authors: Wang Xueyiting
Published: January 2024

The primary goal of this research is to look at the influence of numerous macroeconomic variables on stock market indexes, with a particular focus on the NASDAQ. The ARIMA model was utilized to observe the NASDAQ stock price time series and forecast future prices. By analysing data from 2010 to 2020, the research revealed the links between NASDAQ stock prices and macroeconomic factors such as the CPI, interest rates, inflation rates, and unemployment rates. Results indicated a pronounced negative linear relationship between unemployment rates and the NASDAQ closing price, whereas the relationships with other macroeconomic variables were more intricate. Additionally, residual analysis of the model confirmed its commendable fit to the data. The data sources for this study are all from Yahoo Finance and Federal Research Economic Data. The findings contribute to a deeper understanding of how macroeconomic conditions influence stock market behaviour and offer valuable insights for investors, policymakers, and economists. By carefully selecting the model, time frame, and transformation methods, the study presents a well-rounded view of the complex interplay between the stock market and the broader economy.
External Event Crises on The Stock Market: Taking Japan’s Sea Discharge Incident as An Example
Authors: Hao Zhiyi
Published: January 2024

On August 22, 2023, the Japanese government announced that it would start discharging nuclear wastewater into the sea from August 24. This decision was widely questioned and opposed by the international community and caused strong concerns in Japan. This article aims to take the Japanese nuclear sewage discharge incident into the sea as an example to explore the impact of social crisis on Japan's domestic stock market. The main research method of this article is based on stock return analysis, using the ARIMA model to predict the Japanese stock price trend after excluding the impact of this event, and then comparing it with real data. The results of this study provide evidence that the predicted stock prices are close to the actual stock prices, indicating that as of mid-September, there was no short-term negative impact on the Japanese stock market due to the event, but from a long-term perspective, the predictions remain It is uncertain whether stock prices in Japan's financial markets will fall because of this incident. The main conclusion drawn from this study is that external events may not have a large impact on stock prices in the short term. Different from previous literature, this study uses ARIMA analysis on daily data and weekly data to obtain the relationship between them. Recommendations include organizing a team of experts; hiring a legal team; establishing a complete procedure to handle social media information, and having a dedicated public relations team may be helpful.
Preface: 2nd International Conference on Electronics, Machinery and Intelligent System (EMIS 2023)
Authors: Wilhelmina Patrick , Ke Lijun
Published: January 2024

With great pleasure, we would like to welcome all delegates to our 2023 2nd International Conference on Electronics, Machinery and Intelligent System (EMIS 2023). This conference was held during December 02-03, 2023 in Jakarta, Indonesia. As a major international conference on electronics engineering, mathematical modeling, computer simulation, machinery and mechatronics, intelligent system, and information technology, EMIS 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.

EMIS 2023 conference covers a wide range of current research areas which covers important elements in the related engineering fields. This conference gathers experts from different countries to discuss and present new research findings and perspectives. Four prominent keynote speakers from oversea universities and from industry were invited to share their ideas on current developments in these emerging and important topics. Our participants came from several countries. There are 4 sessions for oral presentation, and the participant are given 10-15 minutes to deliver their works and 5 minutes for Q&A.

We are sure all participants used this conference as a platform to present their work and address current problems in this challenging and promising field and subsequently create new avenues for the commercialization of new products.

Conference Organizing Chair

Jakarta, Indonesia
Impact Of the Economic Embargo Imposed by The United States on China on The Chinese Economy
Authors: Wang Jiarui
Published: January 2024

Amidst an increasingly tense global landscape, the ongoing power struggle between two major players, China and the United States, persists unabated. Notably, the economic sanctions that the U.S. levied against China have wielded substantial influence over China's economic trajectory. This research sets its focus on the intricate dynamics of these sanctions, dissecting their methods, intentions, and the resultant toll on China's economic well-being. Moreover, it examines the realm of U.S.-China trade, scrutinizing the extent of U.S. influence over China's exports, imports, and trade mechanisms. Drawing from a comprehensive lens, the study scrutinizes China's strategic responses to these sanctions, unveiling the multifaceted strategies it has employed to navigate these challenging circumstances. Through insightful analysis, the paper not only outlines the repercussions faced by China but also lays bare the implications for global trade and diplomacy. Within this context, the paper envisions a forward-looking trajectory for U.S.-China relations. By fostering a nuanced understanding of the intricate interplay between economic sanctions, global trade, and diplomatic strategies, the study proposes a more constructive and cooperative path for the future. As the international arena continues to evolve, the pursuit of mutual benefit and sustainable coexistence emerges as a promising proposition for both nations to navigate the complex web of global dynamics with greater harmony and shared prosperity.
Structural Analysis of High-rise Buildings Under Lateral Loads
Authors: Cui Jiarui
Published: January 2024

With the advanced development of modern society, the structural analysis towards high-rise buildings becomes more and more important to ensure stability for service purposes. Foundations of high-rise buildings provide fundamental support to the structure and transfer lateral loads from the upper portion of the building to soil and deep underground sublayers. While taking multiple factors such as soil-structure interaction, foundation layout configuration, and dampers, into consideration, the foundation must resist seismic energy and prevent excessive soil settlement. Compared to different structure systems, each high-rise building has different design and construction, such as rigid-frame, diagrid frame, and shear wall structure system. Structural analysis about each of the structure systems is conducted in this paper. Structure could dissipate and absorb lateral loads using different mechanics and materials. In addition, the exterior shape would affect the stability of the structure using analysis with fluid mechanics. Finding the most suitable structure system needs collaboration between engineers to achieve the best design with highest safety factor and stability.
Explore the Role and Influence of Bex gliflozin (A Type of SGLT-2 Inhibitors) in Type 2 Diabetes
Authors: Shi Yuanqi
Published: January 2024

There are many chronic metabolic diseases in the world, and diabetes is one of them. Blood sugar control and improvement of insulin resistance are the main means of clinical treatment of type 2 diabetes (T2D). A variety of hypoglycemic drugs are now used in the clinic, but due to the different physical conditions of patients, only 50% of the drugs that may play a certain curative effect. Traditional T2D drug treatment relies on the regulation of insulin and has a variety of side effects. Bex gliflozin, as a sodium-glucose co-transporter 2 inhibitor (SGLT2i), the tubules have a reabsorption effect on glucose in the original urine, and the mechanism of action of Bex gliflozin is to inhibit this function of the kidneys, which makes part of the glucose not reabsorbed by the renal tubules and excreted with urine, thereby achieving the purpose of hypoglycemia. As an approved SGLT2i, it has shown good hypoglycemic effect and safety in the treatment of diabetes, combined with others. In addition, Bex gliflozin has a certain protective effect on the heart and kidneys, and some studies have shown that it has no significant effect on blood pressure and weight. This article summarizes the therapeutic progress and mechanism of SGLT2i and Bex gliflozin in T2D, in order to expanse of the indications for Bex gliflozin.
Research on Textile Dyeing Formulation Based on Young's Double-Slit Interference Experiment Optimization Algorithm
Authors: Tam Junyu , Chen Yi , Wu Junyu
Published: January 2024

With the development of intelligent algorithms, computer color matching has become an important method to improve product quality and save labor cost in printing and dyeing industry. In this paper, based on the K-M optical theory and the color difference theory of CIELAB uniform color space, and combined with the latest heuristic optimization algorithm "Young's Double-Slit Interference Experiment Optimizer (YDSE)" proposed in 2023, a feasible solution to generate textile dyeing formulas quickly is proposed. The model is tested with 12 textile target samples, and the experiments show that the proposed dyeing formulation model can converge quickly, and the color parameters of the generated scheme are closer to those of the real samples, with the maximum parameter error not exceeding 10-2 orders of magnitude, and the predicted color differences of the optimal scheme are all in the range of 10-6 orders of magnitude or less. Simultaneous testing of the sample formulations using three other common optimization algorithms, WOA, HHO, and IHHO, shows that their predicted color differences are greater than those of YDSE, proving the reliability of the model.
Research on option pricing of Tesla based on Black-Scholes-Merton, Binomial Tree, and Cox-Ingersoll-Ross Models
Authors: Ding Hanzhi
Published: January 2024

This study examines the predictive accuracy of three option pricing models—Black-Scholes-Merton (BSM), Binomial Tree, and Cox-Ingersoll-Ross (CIR)—using Tesla Inc's real data. The research surveys the evolution of option pricing models and their significance in risk management and speculation. By applying these models to Tesla's volatile stock, the paper compares their predictions against actual prices. Results indicate that while outcome yielded from all three models resembles the real price to a reasonable extent, the Binomial Tree model's superior performance offers closer mean values and correlations with real prices. This research advances the practical understanding of option pricing, contributing valuable insights for traders and investors facing dynamic market conditions.
Comparative global temperature prediction based on arima and bp neural networks
Authors: Jiao Lin , Gao Jingchao , Man Min
Published: January 2024

This paper focuses on the issue of global warming. Due to a large amount of alarming temperature reporting data in the past, with some countries hitting new temperature highs again and many countries declaring emergencies, this has raised concerns about future temperatures. Therefore, this paper predicts the future temperature changes based on historical data, and observes the future temperature trends in 2050 and 2100 as an example, focusing on comparing which one is more accurate in global temperature prediction, the ARIMA model or the BP neural network model. The data was first processed and then an ARIMA model was built using MATLAB and a BP neural network model was built using SPSS. These two models were used to describe the past and predict the future global temperature levels, and line graphs were plotted using SPSS. The two models predict that the temperature in 2050 will be 10.16 °C and 11 °C respectively, the temperature in 2100 will be 10.87 °C and 13 °C differently, and the time for the temperature to reach 20 °C will be 2202 and 2350 separately. Finally, the model was tested by regression analysis of the two models, and the goodness of fit of Arima model and BP neural network was calculated to be 0.726 and 0.84668 respectively, BP neural model is better.
The Toxic Mechanism of Heavy Metals and Their Effects on Human Health
Authors: Peng Hongqin
Published: January 2024

Heavy metals show significant risks to both human health and the environment. The analysis of the toxic mechanisms of heavy metals and their toxic effects on humans has received increasing attention. For this reason, this comprehensive research explores the toxicology effects of heavy metals, delving into their common sources, mechanisms of toxicity, specific health effects, routes of human exposure, regulation and prevention strategies, and notable case studies. Each section provides in-depth insights, from the neurological impacts of lead to the potential link between lead exposure and Alzheimer's disease. The research underscores the importance of understanding heavy metal toxicity, its regulatory framework, and preventive measures. Ultimately, addressing heavy metal contamination requires global cooperation, stringent regulations, and ongoing research to protect individuals and ecosystems from the adverse effects of these toxic elements. In addition, this study also provides a new approach for the study of the impact of heavy metals on human health.
A Study on the Impact of Louis Vuitton's Business Strategy
Authors: Wang Shilin
Published: January 2024

This paper delves into a comprehensive analysis aimed at understanding the multifaceted impact of Louis Vuitton's business strategy across its operational domains. The research is concentrated on four pivotal areas: Firstly, it scrutinizes the brand's sales performance and its evolving audience, both within physical stores and the digital realm. This includes an exploration of foot traffic patterns, an assessment of marketing methodologies, and an evaluation of the customer experience, both online and offline. Secondly, the study meticulously examines Louis Vuitton's promotional endeavors, encompassing aspects such as advertising campaigns, celebrity endorsements, and various marketing initiatives, providing insights into their contributions to brand visibility and market appeal. Thirdly, the paper delves into Louis Vuitton's adaptability and innovation in refining its product line and mix, addressing the brand's ability to respond to shifting market demands and consumer preferences. By conducting a thorough analysis of these dimensions, this study aspires to offer an in-depth understanding of the far-reaching implications of Louis Vuitton's business strategy. In doing so, it contributes to the discourse surrounding strategic management, marketing, and the dynamics of the luxury fashion industry.
Replenishment And Automatic Pricing Strategy for Vegetable Products Based on Genetic Algorithm
Authors: Sheng Yicheng , Zhang Zhiwen , Jin Zhenru
Published: January 2024

In order to improve the accuracy of replenishment and pricing of vegetable commodities sold in supermarkets, and to maximise the benefits of vegetable commodities sold in supermarkets, this paper comprehensively establishes a strategic planning model for replenishment and automatic pricing of supermarkets. Firstly, we carry out descriptive statistical analysis and non-linear fitting on the historical sales data of supermarkets to find the distribution pattern of the sales of each single product of vegetables, and then find out the relationship between each single product of vegetables through correlation analysis. and then find out the relationship between each vegetable item through correlation analysis. After that, we built an LSTM time series forecasting model based on the cost data to predict the replenishment volume of the six vegetable categories in the coming week. Finally, in order to maximise the revenue of the superstore, we constructed a pricing planning model for the combination of vegetable categories, and solved the optimal purchase quantity and pricing strategy based on genetic algorithm.