bluuebunny/crossref_metadata_2025 huggingface dataset:
Consumer Behavior on Online Shopping Platforms in China
Authors: Dai Ziyi
Published: January 2024

Amidst the wave of digitization, online shopping has emerged as a pivotal avenue for individuals to purchase goods and services. Diverging from the conventional brick-and-mortar stores, online shopping platforms offer a more convenient and diversified shopping experience. However, despite their widespread popularity among consumers, investigating the variations in consumer behavior and the determinants across these platforms remains a worthy endeavor. This study zooms in on online shopping platforms such as Taobao, TikTok, and Pinduoduo, aiming to scrutinize the behavioral patterns, influencing factors, and improvement requisites of consumers on these platforms. Through conducting surveys, this research offers empirical evidence to deeply comprehend the behavioral models and determinants on various online shopping platforms. Valuable conclusions pertaining to platform selection, shopping preferences, and enhancement needs are drawn. These insights will serve as guiding principles for enterprises to formulate more targeted marketing strategies, while also offering substantial recommendations for platform operators to enhance user experiences and bolster platform competitiveness.
Action Mechanism and Side Effects of Tetrodotoxin
Authors: Ruan Shuoyang
Published: January 2024

Tetrodotoxin (TTX) is one of the most toxic neuro-toxins found in the world at present. This drug has been widely used in the medical field, such as treating cancer related pain and severe arrhythmias. It is widely distributed and has been found in various high and low organisms such as aquatic and terrestrial organisms. But the source of the TTX and detoxification methods still need to be studied, so the study of the TTX is very significant. At the same time, TTX can block sodium ion channels, has obvious analgesic effect, and also has antiarrhythmia, abandon drug addiction and other effects. As a result, TTX has high medical and commercial value. This research will mainly summarize the pharmacological action, side effects of TTX and its underlying principle. In addition, it is expected that this study can provide new ideas for the study of new functions of TTX and the treatment of new diseases.
Analysis of the Relationship between Regional Carbon Financial Market Development and Industrial Structure Upgrading: A Grey Relational Model Approach
Authors: Yin Wenxuan
Published: January 2024

Carbon finance, recognized globally as one of the effective solutions to combat global warming, is poised to inject fresh vitality into economic and societal production as it develops. Based on data from 13 cities in the Beijing-Tianjin-Hebei region, this study explores how the development of the carbon finance market affects industrial structure upgrading from the perspectives of carbon finance market development level and industrial structure upgrading. Firstly, by constructing an evaluation indicator system, a comprehensive comparative analysis of the carbon finance market development and industrial structure upgrading of these cities is conducted. Secondly, the study uses the grey relational model to delve into the degree of correlation between the development level of the carbon finance market and the upgrading of the industrial structure. The result shows significant regional disparities among these cities in terms of the development of the carbon finance market and the upgrading of industrial structure. Beijing and Tianjin lead in terms of carbon finance market development. Through the analysis using the grey relational model, it is found that there is a moderate to strong correlation between the level of development of the carbon finance market and industrial structure optimization, indicating the importance of all factors in influencing industrial structure upgrading. Empirical results demonstrate that, on a holistic scale, the development of carbon finance has a significantly positive impact on industrial structure advancement and rationalization. However, disparities exist among different cities, primarily attributed to varying levels of economic development, policy orientation, and developmental stages.
Research on the Impact of Artificial Intelligence on the Labor Market
Authors: Bian Zhiqing
Published: January 2024

Language models have a significant impact on the labor market, and this paper aims to analyze the effects on different parties in detail and give policy suggestions on the adverse effects brought by AI. The author first applies a case using news about the employment market, then does an analysis and gives suggestions based on the case. The research finds that AI causes fluctuations in the labor market through the displacement effect, productivity effect, and the reinstatement effect. The pattern of employment also adjusts to favor the job seekers with AI skill sets. The paper further underlines the undesirable effects of AI including deepfakes and biases, and legal and technological measures could be adopted to alleviate the problems. This paper could help scholars better understand the impacts of AI on the labor market, and the suggestions listed could give authorities ideas on policy implementations to regulate AI.
The Values in the Hollywood Cinema Market
Authors: Zhong Ouyuan
Published: January 2024

Some have misled Hollywood cinema with impressions due to some conception that it is limited to big budgets, stars, special effects, and extensive publicity campaigns. However, it encompasses more than investment diversification, production, and commercial propaganda feature. In other words, beyond the illustrative classic Hollywood pre-sold mechanism, monopoly, and overseas market, it supports values and serves as multicultural, sexual and race equality. This paper lists the phenomenon that contemporary Hollywood cinema is revenue-driven, resulting in many low-quality and quantity reproduction cinemas such as hybrid genre is typical of formulaic filmmaking, and they arranged all the cinematic elements narrative to meet the audience's expectations. Significantly, formulaic movies have become popular and widespread in the international market and may have an unpredictable impact on the future film industry. The author believes that films are the medium for representing historical periods and are for the generation's legacy, which should craft narratives that intricately blend values and ideology. In a nutshell, it is crucial to discover a solution for cinema's unpredictable future.
Static Analysis of Gear Periodic Symmetrical Structure Based On ANSYS
Authors: Ma Jing , Zhang Wenhui , Ding Shuaibo , Yi Dajian , Wu Maojun , Yi Dajian , Chen Rui , Huang Xiaochen
Published: January 2024

Gears are important components of transmission mechanisms, and it is crucial to analyze the stress and strain of gears using ANSYS to obtain their mechanical characteristics for product research and development in production. After establishing a mechanical model of gears based on material characteristics, define constraints and boundary critical conditions. Through analysis and solution, the deformation diagram and stress distribution diagram of the gear are obtained. Using the characteristic of periodic symmetry can simplify the analysis of the mechanical characteristics of gears, reduce the cycle time and cost of prototype development. Of course, this method can be applied to all similar institutional developments with this characteristic, which provides convenience for product design and improvement and saves cost.
Forecasting default risk of Chinese real estate credit bonds based on Bagging algorithm
Authors: Liu Xuan
Published: January 2024

In recent years, with Chinese rapid economic upgrading, it has also made the property industry more and more prosperous. However, due to the imbalance between supply and demand in China's real estate industry in recent years has led to an overly rapid rise in property prices, the risk of a real estate market bubble has increased, and many real estate companies have gradually defaulted on their bonds. Against this background, the aim of this paper is to construct a bond default prediction model using the Bagging algorithm in machine learning to predict the default risk of real estate bonds. And the results were also compared with Logistic model and SVM model, eventually it was found that Bagging algorithm can improve the prediction results more effectively. It is possible to identify real estate companies that may default on their bonds in advance, reducing investor losses, strengthening the risk prevention awareness of debt issuers, contributing to the healthy and stable development of real estate.
Vertical Farms: A Sustainable Solution to Urban Agriculture Challenges
Authors: Zhu Wenhao
Published: January 2024

Vertical farms are considered to be a powerful response to the shortage of future agricultural cultivation space, which can achieve higher agricultural output in cities and alleviate food shortage. This paper focuses on the characteristics of vertical farms, takes the Plant vertical farm in Chicago as an example, describes its design and performance, analyzes its advantages and design principles, and raises some problems that need to be solved. Vertical farms can expand the yield of crops and simulate the environment required for crop growth and development. The success of The Plant is mainly due to the following aspects of the design: saving raw materials and waste disposal costs through the use of waste, staggered electricity consumption and the use of insulated structures to maximize the savings in energy costs, and ultimately enabling the vertical farm to achieve the ability to compete with traditional agriculture. The vertical farm finally achieved the ability to compete with traditional agriculture. It is worth noting that although the small-scale pilot projects of vertical farms have achieved some success, there are still many constraints to be overcome in expanding the scale of vertical farms because of their high construction and operation costs and high technical level.
Study on Miura Folding Technology and Its Application in Sound Insultation
Authors: Liu Hao
Published: January 2024

Based on the wings of dragonflies, Japanese astrophysicist Koryo Miura invented a new folding technology called Miura folding. The core principles of Miura folding include symmetry, periodicity, and compactness. The structure of Miura folding is arranged alternately by multiple parallel creases, which can remain stable when unfolding and folding. The Miura folding has the advantages of compactness, speed, structural stability, mathematical controllability, and multi-field application. Compared with traditional methods, the Miura folding provides more efficient, flexible, and more controllable solutions for a variety of application scenarios, from space technology to practical tools in daily life. This article reviews the origin and advantages of Miura folding and discusses its applications, focusing on the design and innovation of Miura folding sound insulation walls. The progress in design, the challenges related to the control of sound insulation, and the sound insulation of Miura folding are discussed. In addition, this article also discusses the application of Miura folding in other fields, the application of Miura folding technology in the era of globalization, and the prospect of future Miura folding technology in the emerging technology field. This article may offer a reference for the development of folding technology.
Sliding mode variable structure control of RP manipulator based on computational torque
Authors: Zhang Shuqian , Zhang Wenhui , Ye Yangfang , Jiang Zhongyang , Jing Ma , Gao Zihao
Published: January 2024

Study the control problem of a coupled robotic arm with moving and rotating joints, a PID control method based on calculated torque is proposed. Considering that the robot model is difficult to obtain accurately, only its estimation model can be obtained. The output feedback signal is used to define the sliding mode surface function with error signal. Sliding mode variable structure controller(SMVSC) is designed based on the computational torque control method. Taking the mathematical model of RP robot as an example, Experimental calculations have found that the control accuracy can be guaranteed, but there is a significant chattering situation. In engineering practice, it is necessary to process the symbol function.
Enterprise Ordering and Transportation Scheme Based on Entropy Weight TOPSIS Method
Authors: Wang Yipan , Li Diansheng , Wang Lihao , Wang Zhengjie , Fan Xingkui
Published: January 2024

In this paper, we use the entropy weight TOPSIS method to quantitatively analyze the importance of suppliers to enterprises and establish a single objective function supplier selection model. Specifically, by checking the reliability of the data, the validity of the data in the attachment is guaranteed. The supplier's important metric system is constructed by using six indicators, and a single objective function is established to solve it by Lingo programming. In addition, the objective function aiming at the minimum number of suppliers and the objective function aiming at the minimum production cost of the enterprise is established, and the quantitative analysis method is used to consider the value of the transfer plan and the order plan. Furthermore, a dual-objective planning model aiming at enterprise storage costs and transportation costs is established, and the Lingo program is used to obtain the most economical ordering plan for the new enterprise in the next 24 weeks. Finally, the sensitivity of the considered models was analyzed by SPSS.
Pricing And Replenishment Strategies for Vegetable Products Based on Planning Models
Authors: Liu Guannan , Yang Jingbo , Cai Wanbo
Published: January 2024

Reasonable pricing and replenishment strategies for vegetable products are crucial for maximizing profits for fresh food supermarkets. This article mainly studies the relationship between the sales volume and sales unit price of vegetable products and time, establishes a pricing and replenishment decision model based on BP neural network and mathematical programming, and provides strategies to meet the requirements of maximizing the interests of supermarkets.
CRISPR-Cas9 potential in treating HIV/AIDS
Authors: Ji Yuchen
Published: January 2024

In this review paper, the mechanism of HIV infection and some of the most efficacious and updated gene therapy methods developed by scientists will be discussed in detail. Different editing strategy using the CRISPR-Cas9 system inhibits different times of the HIV life cycle are involved with all the same target, which is to block the HIV infection pathway as well as its own replication&proliferation pathway. As the most popular and promising way of treating different kinds of diseases which seemed to be incurable in the past, and CRISPR-Cas9 shows high potency under the data of experiments and clinical studies. These give scientists many confidence to run out more research on this new treatment for diseases and at the same time to improve and optimize the function and efficiency of this gene editing toolkit making sure it can used widely in the future as an actual clinical treatment for the HIV/AIDS.
Research On Time Series Forecasting-Based Pricing Strategy for Supermarket
Authors: Wang Haoke , Zhang Cheng , Song Yufei
Published: January 2024

In fresh food supermarkets, vegetables have a short shelf life. It is of great practical significance to price different products based on market research in order to maximize the benefits of supermarkets. The aim of this paper is to investigate and address the pricing decision question of vegetable products in fresh food supermarkets. This article investigates the correlation between cost-based pricing and sales revenue by establishing linear regression models and time series models.In addition, we have also made price predictions for various categories of products in the supermarket. Finally, this article provides pricing decisions for various categories in the first week of July 2023 for the supermarket.
The Role of Education in Economic Advancement: A Case Study of Silicon Valley
Authors: Wei Yuyang
Published: January 2024

Education is an important ingredient in the development of the human capital of any given country since it directly influences the quality of output of the workforce. With an educated workforce, efficiency is enhanced, as well as the level of productivity, due to the capacity of individual workers to be innovative. This paper seeks to analyze the impact of education in a country by analyzing the impact that education has on the level of economic growth, as well as its influence on a workforce’s capacity to absorb new technologies. Additionally, the paper also discusses how education is a crucial asset in reducing poverty and inequality in society by increasing sustainable household incomes as well as bringing about positive externalities. The paper shows from the case of Silicon Valley in the United States, education plays a great role in economic advancement of a nation or region. The paper shows that the Silicon Valley largely benefits from the presence of top higher education institutions such as Stanford University, which train a large number of technological innovation talents.
Multi-beam line observation optimization strategy based on random variable unitary iterative model
Authors: Hou Qiwen , Zhang Hang , Xu Guirong
Published: January 2024

Multibeam system has many advantages such as large measurement range, fast speed, high accuracy, etc., which can be applied in many fields such as marine topographic survey. In this paper, the relationship between coverage width and other variables is obtained by analyzing the geometric relationship between each parameter, and a multibeam sounding model based on geometric relationship is established. And based on the intelligent optimization algorithm, an iterative optimization model with random variable singularization is designed independently. And the actual terrain data were visualized and simplified into various parameters in line with the model. With the help of the definition of the coverage rate, the relationship between the coverage width and other variables, and the one-to-one correspondence between the translation distance of the slope and the coverage rate, the complex measurement problem can be transformed into a simple linear programming problem, and the relationship model between the coverage rate and other variables is established. In the end, the model can be used to derive the optimal wiring scheme to realize high-precision and full-coverage sweeping of the seabed terrain in the given sea area without omission, provided that the ship speed, beam opening angle and other factors are reasonable.
Exploring the Carbon Footprint of Energy Consumption in Shanxi Province Based on the Tapio Decoupling and Grey BP Neural Network Model
Authors: Guo Kejun , Wang Xuemei , Song Jingrui
Published: January 2024

This paper focuses on analyzing the carbon footprint of energy consumption in Shanxi Province, China. It utilizes data from sources such as the 'China Energy Statistical Yearbook' (2001-2022), the China Carbon Accounting Database, and the 'Shanxi Statistical Yearbook' for an exploratory analysis of energy consumption and the province's economy. The study calculates the carbon footprint of energy consumption in Shanxi Province and employs the LMDI model to identify influencing factors. Additionally, it uses the Tapio decoupling model to assess the relationship between these factors and economic development. To forecast the carbon footprint from 2022 to 2026, a grey BP neural network prediction model is applied, demonstrating improved accuracy compared to BP and grey models, with MAE and RMSE values of 2.44 and 10.91.
TikTok’s Revenue Dynamics: Exploring Income Streams Beyond the Surface
Authors: Xie Zhuolun , Yang Yuze , Zhao Yiran
Published: January 2024

Social media has emerged as the predominant mode of global digital communication, captivating a vast and varied spectrum of users with its inventive and swift content. It fundamentally shapes how information is conveyed and social engagements are performed. This article thoroughly analyzes TikTok’s business model with a focus on advertising, virtual gifts, and e-commerce. TikTok’s core advertising revenues, which amount to £10 billion annually, are obtained through various channels, such as recommended videos, app opening screens, and search ads. However, virtual gifts represent a significant income source for TikTok, with users making substantial contributions through rewards. Regarding e-commerce, TikTok has excelled in cross-border trading, experiencing a growth of over 80 percent due to ongoing user experience enhancement, resulting in increased Gross Merchandise Value. The article concludes by assessing TikTok’s current issues and offering recommendations to improve its business model and enhance its long-term profitability. With its pioneering business approach and extensive global user base, TikTok has emerged as a trailblazer in the social media domain.
Research on pricing and replenishment strategy of superstore goods based on linear regression and gray prediction models
Authors: Jia Wangyi
Published: January 2024

The pricing and replenishment strategy of various commodities in superstores have a significant impact on the revenue. This paper aims to address the automatic decision-making problem for pricing and replenishment of vegetable commodities in superstores. It applies the linear regression model to predict commodity prices, aiming to maximize the revenue of superstores. Additionally, it utilizes the gray prediction model to forecast replenishment volume. Based on marketing data from 2020 to 2023 for vegetable goods at a specific superstore, this study provides the replenishment quantity and pricing strategy for each vegetable category from July 1-7, 2023, as well as for each individual vegetable item on July 1, 2023.
Diabetes Analysis Based on Naive Bayes Model
Authors: Zhang Linyue
Published: January 2024

As a matter of fact, diabetes has been one of the most disturbing diseases in human beings’ daily life in recent years. With this in mind, the method to predict diabetes has been conducted through artificial intelligence technology including machine learning as well as big data analysis. On this basis, this study is going to discuss the possibility of predicting diabetes via one of the widely used machine learning scenarios, i.e., Naive Bayes models. According to the analysis, the result shows that although the accuracy is improved after parameter changing, the value is 75.61%, still below 80%. In other words, it indicates that the features offered nowadays are still abundant enough to realize high accuracy predictions. Despite the low accuracy, the result still can be used and applied in many fields, such as the pre-processing of another model’s building. Overall, these results shed light on guiding further exploration of diabetes analysis.
Therapeutic Vaccines in Breast Cancer
Authors: Zhou Yikham
Published: January 2024

Breast cancer (BC) is a major worldwide health issue, characterised by an increasing occurrence in both males and females. The classification of breast cancer subgroups is determined by variations in hormone receptor expression. Although traditional breast cancer therapies, including chemotherapy, surgery, and radiotherapy, have demonstrated effectiveness in the treatment of patients, they are frequently associated with significant adverse effects and recurrence. The emergence of therapeutic vaccines has become a promising option for the field of immunotherapy. These vaccines enhance the body’s immune system to identify and eliminate cancerous tumour cells. The current approach to vaccine therapy for breast cancer focuses on the targeting of two main categories of antigens: tumour associated antigens and tumour specific antigens. Excitingly, multiple vaccine strategies for breast cancer treatment have been employed, all of which have demonstrated promise and effectiveness in clinical studies. Currently, proposed vaccine types include peptide-based vaccines, whole tumour cell vaccines, DNA/RNA-based vaccines, dendritic cell vaccines, and viral-vector vaccines, etc. This review examined the present state of different types of vaccines in breast cancer therapy, including the therapeutic mechanism and the treatment outcomes.
Integrating Electronics and Biomedical Applications in 3D Printing Current Progress and Future Possibilities
Authors: Zhong Youxi
Published: January 2024

Biomedical three-dimensional(3D) printing has redefined the landscape of medical practice, facilitating the customization of implants, prosthetics, and medical instruments. The use of 3D printing, also known as additive manufacturing, empowers healthcare professionals to create patient-specific medical solutions that align seamlessly with anatomical complexities. Through the deposition of material layer by layer, 3D printing allows for the fabrication of intricately designed structures with precision and reproducibility. The medical field has witnessed a paradigm shift as personalized implants and prosthetics are tailored to the unique needs of patients, thereby improving functionality and patient outcomes. This review aims to provide a comprehensive analysis of the integration of electronics and biomedical 3D printing. The focus extends beyond individual domains, encapsulating the crossroads where the two converge to form synergistic solutions. Each subsequent section of this review will delve into specific facets, discussing current advances, challenges, and potential future trajectories. From 3D printed medical devices with embedded electronics to wearable health monitoring systems, this review seeks to unearth the emerging landscape of interdisciplinary innovation.
The Relationship between Spousal Co-ownership of Shares and Corporate Governance Level
Authors: Zhong Runyu , Pan Zhuoyu
Published: January 2024

Amid continual societal advancement, a growing number of women have assumed roles in the business realm, co-owning shares with their spouses and managing family businesses, which in turn exhibit varying qualities of operational administration. This study selects family businesses listed on A-shares between 2010 and 2021, with an initial sample studied extensively through multiple regression analysis. The empirical examination discerns the influence of spousal co-ownership of shares on corporate governance levels. The results indicate that businesses with spousal co-ownership tend to have a higher percentage of familial involvement, with suboptimal internal quality control, not conducive to the elevation of governance levels. In conclusion, the author provides policy recommendations for government entities and anticipates the future rationalization of corporate structures.
The Impact of Federal Reserve Interest Hike: Currency, Stock and Bond Market
Authors: Li Zixuan
Published: January 2024

The paper investigates the consequences of interest rate hikes initiated by the Federal Reserve on various financial markets. This comprehensive analysis examines the relationships between interest rate changes and their effects on currency, stock, and bond markets, which also discuss the potential scenario or solutions in respond to the rate hike. By analyzing data from different regions of the world, the paper discusses how these monetary policy decisions influence market dynamics, investor sentiment, and overall economy. Federal Reserve raising interest rate has impacted the world from various aspects, which each’s country government needs to plan strategically to respond to the impact toward currency, stock, and bond market. The findings presented in this paper contribute valuable insights for policymakers, investors, and economists seeking a deeper understanding of the intricate interplay between central bank actions and financial market reactions, which it is important to understand the impacts and apply monetary policy in order to ensure economic stability.
Research On Emotion Management Based on Speech Analysis for Nursing Homes
Authors: Liang Boyuan
Published: January 2024

Speech emotion recognition is an important research area in artificial intelligence aimed at identifying the emotional states of speakers. This paper provides an overview of the current state and key algorithms of speech emotion recognition, focusing particularly on the emotional well-being of elderly residents in nursing homes. Firstly, the paper introduces the background and application areas of speech emotion recognition, emphasizing its significance in human-computer interaction, psychological health monitoring, and emotional intelligent systems. The paper extensively discusses methods of extracting emotional features, it adopts the K-Nearest Neighbors (KNN) classification algorithm, which serves as a simple yet effective classification method with potential in emotional speech recognition. This study aims to explore the design, implementation, and future directions of an emotion recognition system based on KNN. This algorithm exhibits a high fitting performance for emotional speech data, presenting advantages such as ease of implementation and alignment with the distribution characteristics of emotional speech data. Through multiple comparative experiments, the optimal K value for recognition has been determined, achieving a straightforward and convenient emotional recognition simulation. Finally, the paper summarizes the current state of speech emotion recognition, emphasizing its potential and significance in practical applications.
Research based on open space collaborative intelligent fire system
Authors: Sun Jiaqi , Hu Ke
Published: January 2024

The open space collaborative intelligent fire protection system studied in this article uses STM32F407 as the main control chip of the drone, and the STM32F103 is used as the main control chip of the fire truck. ZigBee wireless communication and other modules. The main innovation of this article is to use OpenMV's ground black line recognition positioning, the attitude fusion algorithm of the main controller module, and the PID control algorithm for real -time positioning of drones and fire trucks in the testing area of the test. After actual testing and verification, this system can complete the full coverage of the patrol area in different environments, fire identification in the patrol area, and fire extinguishing tasks. Through the ZigBee wireless communication module Essence.
A Review of Three Methods of Artificial Intelligence in Smart Grid Cyber Security: Machine Learning, Reinforcement Learning, Ensemble Methods
Authors: Xu Luyao
Published: January 2024

Renewable energy is gradually replacing traditional fossil fuels. The change of power generation energy structure brings new challenges to the traditional power grid. Through the efficient bidirectional movement of electricity and information, smart grids might include renewable energy. For the complex informational and financial operations required by smart grid, communication systems are crucial, but they also make smart grid vulnerable to numerous cyber attacks. Smart grid cyber security has been widely concerned. The purpose of this paper is to explore the use of artificial intelligence technology in smart grid cyber security. Three methods in the field of artificial intelligence are highlighted: Machine Learning, Reinforcement Learning, and Ensemble Methods. This paper summarizes the benefits and drawbacks of their use of smart grid cyber security, and further makes a qualitative comparison of the three methods from multiple performance indicators.
Sleep Quality Analysis Based on Logistical, SVC and Xgboost
Authors: Gong Hanjun
Published: January 2024

As a matter of fact, a healthy lifestyle requires sleep quality to be one of the main ingredients. It's a common practice to spend roughly a third of the lives sleeping, or at the very least, one should. Regrettably, that goal is not met by many of human beings in recent years. With this in mind, this study will investigate to build three models LogisticRegression Model, XGBClassifier Model, SVC Model using python technique. From the acquired data the model is used to find out some lifestyle effects on sleep. XGBClassifier Model is selected as the best model for the study. The model concluded that Occupation has the greatest effect on insomnia. Sleep apnea is most affected by BMI Category. BMI Category, Stress Level, Blood Pressure, Sleep Duration have more influence on sleep. These results show that the quality of sleep can be improved in terms of BMI Category and Blood Pressure.
Chronic Low Back Pain Treatment
Authors: Zhou Yutong
Published: January 2024

Chronic low back pain is the attachment point of lumbar muscle fascia and sola.t, and chronic inflammation damage. This is one of the common causes of low back pain. The main symptoms are lumbar or lumbar spine swelling pain, soreness, recurred, and pain changes with the degree of climate or accumulation. Lumbar pain can also from muscle pain to shooting, burning or stabbing. In addition, pain will emit legs. Bending, twisting, weightlifting, standing or walking will make the situation worse. Lumber muscles degeneration has a lot of different treatments like Muscle strengthening such as ab strengthening, gluteal strengthening, back strengthening to prevent muscle dystonia. Physical therapy, such as electromagnetic, ultrasonic, infrared, laser, acts on the human body through sound, light, electricity, heat, and plays the role of thinning tendons and activating complexions. Chinese medicine therapy such as electroacupuncture. This article is about the above three therapies, hope to provide reference for chronic low back pain treatment.
Redefining Service Work: The Role of AI in Restructuring Employee Participation
Authors: Li Huaying
Published: January 2024

The use of AI in better service delivery is common. Different types of AI are developed: Mechanical, Thinking, and Feeling AI. Each AI technology has its strengths and drawbacks. There are anticipations that AI may replace human beings in service. However, not many studies have delved into this issue by simultaneously analyzing the value of AI technology and human employees and considering current and future trends. Thus, this essay will address this gap by concluding that Mechanical AI can be applied to complete standardized tasks; Thinking AI assists in identifying new opportunities, customizing services, and making more sound decisions; and Feeling AI can interact with customers, providing general emotional support. However, human employees should complete tasks regarding an advanced level of service as they possess self-consciousness and genuine emotions. Moreover, in the light of the Feeling Economy, jobs will become people oriented. It is necessary to keep and expand people’s specialty.
Research on road congestion analysis strategy based on combined weights of game perspective
Authors: Hong Bin , Qiu Yu , Liu Yafei , Han Shixuan , Liu Shuaicong
Published: January 2024

In recent years, the vehicle carrying demand of urban roads has been growing, and in order to prevent road congestion, this paper conducts a road congestion analysis based on the game perspective of AHP-EWM combined weights, and the analysis shows that drivers have a great relationship with the congestion degree of roads when choosing routes in urban roads, so establishing a more perfect visualization of induced information can play a significant role in alleviating urban traffic congestion and guiding drivers to choose more appropriate roads.
Analysis of China and Chinese Foreign Trade Enterprises' Response to Anti-Dumping
Authors: Yang Yankai
Published: January 2024

In the era of fierce competition in the global economy, the country which suffers the most from anti-dumping in the world is China. This implies the importance of the current Chinese foreign trade enterprises to deal with anti-dumping measures, with the possibility for enterprises to make appropriate strategic adjustments to cope with the damage to their interests in the face of anti-dumping. In view of this, based on a comprehensive analysis of the literature of the past nearly 20 years, the impact from the point of view of productivity and exports is explored, the important impact caused by the EU and the United States is analyzed, as well as some analyses of developed and developing countries for anti-dumping in the past. The conclusion is that China will likely adjust its economic structure in the face of anti-dumping, enhance its trade negotiation capacity, and eliminate anti-dumping trade barriers; and that enterprises will be able to reasonably increase productivity as well as technological progress under the pressure of anti-dumping, and reduce costs by upgrading and iterating within the enterprise. However, in the long run, this does not mean that China benefits from anti-dumping measures.
Design Of Communication Unit for Mine Explosion-Proof Reversible Vacuum Electromagnetic Starter
Authors: Li Tongzhe , Zhang Hongkui
Published: January 2024

Mine explosion-proof reversible vacuum electromagnetic starter is the main electrical equipment in underground coal mine. On the basis of analyzing the situation of coal mine safety production, the characteristics of mine explosion-proof reversible vacuum electromagnetic starter and CAN bus technology, the digital signal processor (DSP) is used as the core to design the communication unit of mine explosion-proof reversible vacuum electromagnetic starter, and the real-time transmission of data between the DSP and the upper computer is realized through CAN communication technology.
The Comparison of RS Codes, LDPC Codes, And Turbo Codes
Authors: Lei Xinyu
Published: January 2024

Error correction codes have been widely used in various fields in recent years, including the communication field, storage field, digital media field, computer network field, and so on. In this paper, the development history of error correction codes is briefly summarized; and the principles and performance of three kinds of error correction control codes are systematically summarized starting from RS codes, LDPC codes, and Turbo codes. Three types of error correction codes are compared and analyzed in the field of wireless optical communication, and the error correction characteristics of different codes in three different weather conditions are compared and summarized for the applicable environments. The error correction codes are also compared in the field of aviation flight telemetry, and which codes are suitable for uplink and downlink telemetry in flight telemetry are summarized. At the same time, the paper provides an outlook on the future development trend of error correction codes.
Investors' Stock Investments in the Chip Industry: Motivations, Strategies, and Impacts
Authors: Jin Yan
Published: January 2024

This paper talks about what motivates investors to invest in chip-related stocks, and how their investment strategies and models do impact the chip market. This paper analyzes investors' stock investments in the chip industry from the perspectives of their motivations, strategies, and the subsequent impact on the market. The research identifies that investors are driven by diversification, passion, innovation support, and long-term growth, employing strategies such as in-depth research, active involvement, and early-stage investments. Their choices influence market sentiment, accelerate research and innovation, and impact M&A activities in the chip sector. This paper is significant for investors seeking insights into investors' investment motivations and strategies in the chip industry. Gives the investors a clearer view for the current Chip Technology Corporation’s stock market. And also, benefits researchers studying the dynamics of the semiconductor market and the pivotal role of investors in shaping it.
Relationship Between Housing Price and Income in China
Authors: Chan Hsiao-Yi
Published: January 2024

The average house price to income ratio of the 100 key cities in China monitored in 2022 is 12.4, which is lower than that in 2021. According to international standards, the housing price to income ratio is a rational range between 3-6 times, and China is 12.4 times, which is far higher than the international reasonable range. At the same time, China's house price to income ratio has continued to decline in recent years, and the level in 2022 will be lower than that in 2021. However, even so, China's house price to income ratio is still very high, especially in first-tier cities and hot second-tier cities. From the current situation, the real estate market can hardly be called "stable", whether it is to boost market confidence, or balance the ratio of house prices to income, it will take time. This paper starts with some background information to the housing market and income to demonstrate the negative conditions in both real-estate market and living conditions for Chinese citizens. Secondly, the relationship and the negative effect of these conditions are reviewed. Finally, how people's relative responses to difficulties create a new set of problems is shown.
Analysis of the Perovskite Solar Battery
Authors: Chen Qihan
Published: January 2024

As a matter of fact, the subversive photovoltaic technology of the perovskite solar cell has the benefits of high energy efficiency in conversion, low production costs, and ease of preparation in recent years. A larger number of scholars have given perovskite solar cells a lot of attention because of their advantages such as simple process, roll-to-roll production and low cost, as well as have become the most eye-catching new generation photovoltaic devices. At the same time, PSCs have enormous potential, as seen by the rise in efficiency from 3.81% to 25.7% in just a decade. On this basis, the perovskite solar cells' mechanism of operation and device architecture are described and discussed in this study. To be specific, its fabrication is also summarized and discussed accordingly. According to the analysis, the future perovskite solar cell development issues and difficulties are also anticipated and demonstrated at the same time. Overall, these results shed light on guiding further exploration of solar cells.
Analysis of the Principles and Applications of Ultra-intensity and Ultrashort Laser
Authors: Li Zerui
Published: January 2024

With the development of laser technology, how to improve the output performance and peak power of lasers has become one of the hot directions of current research. This study analyzes the principles and applications of ultra-intensity and ultrashort pulse laser. It firstly outlines the development history of laser technology and the basic definition of ultra-intensity and ultrashort pulse laser. It also mentions the realization methods for generating ultra-intensity and ultrashort pulse lasers, such as mode-locked femtosecond oscillators and CPA-based femtosecond amplifiers. The paper describes the principles of CPA technique and emphasizes its importance in realizing high power ultrashort pulses. The paper discusses various applications of ultra-intensity and ultrashort pulsed laser and summarizes and discusses the major bottlenecks facing current and future ultra-intensity and ultrashort pulsed lasers and their possible solutions. The technical review in this paper aims to enhance the understanding of ultra-intensity and ultrashort pulsed laser and provide insights into the next phase of research exploration in ultra-intensity and ultrashort pulsed lasers.
Probing Leakage Current Suppression Techniques for Non-Isolated Photovoltaic Inverters
Authors: Cheng Yangrui , Lou Zhijunxi , Lu Yintong , Wang Zexun
Published: January 2024

The evolution of photovoltaic (PV) inverters has witnessed distinct trade-offs between isolated and non-isolated configurations. While isolated PV inverters grapple with challenges such as increased volume and suboptimal system efficiency due to transformer inclusions, their non-isolated counterparts offer a solution by eliminating these transformers. However, this lack of electrical isolation in non-isolated inverters engenders a distinct predicament: significant leakage currents. Such currents not only impede system operation but also curtail operational efficiency. Recognizing this, the suppression of leakage current has catapulted to the forefront of contemporary research. This manuscript elucidates the operational intricacies of non-isolated PV inverters. It then embarks on a panoramic review of prevailing leakage current suppression techniques, both domestic and international, contextualizing them with state-of-the-art inverter topologies such as the H7, H10, three-level neutral point clamped (NPC) and three-phase four-bridge arm configurations. The paper culminates with a prospective glance at future research trajectories in leakage current suppression, proffering seminal recommendations for academic and industry fraternities.
Research on Space Optimization of Service-Oriented Public Facilities Based on Interaction Design
Authors: Shao Yanrong
Published: January 2024

This paper aims to discuss the relationship between service-oriented public facilities and interaction design, analyze relevant cases, and discuss how to improve the user experience of service-oriented public facilities from the perspective of interaction design. Service public facilities refer to the infrastructure that provides services to the public, such as bus stations, airports, hospitals, etc. In service-oriented public facilities, interaction design has become an important part, which can improve user experience and efficiency, so as to bring better services to the public. In summary, interaction design plays an important role in service-oriented utilities, which can improve user experience, increase efficiency, and enhance accessibility. In actual cases, designers also bring better service experience to the public through continuous innovation and practice. Finally, it needs to start from the perspective of interaction design, pay attention to user needs and ease of use, provide more humanized interaction design for service-oriented public facilities, and bring a better service experience to the public.
Analysis Of Silicon Crystal Materials: Meeting Growing Demands Across Industries
Authors: Li Hanwen
Published: January 2024

The demand for silicon crystal materials is poised for continued growth across diverse sectors in the upcoming years. In the realm of computers and communication, silicon single crystal wafers and chips are in high demand, fueled by the increasing adoption of communication equipment and the essential requirement for memory and control chips in information processing systems. Beyond the electronics domain, silicon crystals find applications in various industries, including environmental protection, new energy, and construction. In the field of environmental protection, silicon crystals play a vital role in denitrification and dust removal devices. In the new energy sector, they contribute to solar photovoltaic power generation systems and geothermal power generation systems. In construction, silicon crystals find their place in the production of building glass and semiconductor building materials. As China's economy continues to evolve and environmental concerns gain prominence, the demand for semiconductor materials, including silicon crystal materials, is anticipated to rise. This underscores a bright market outlook for silicon crystal materials in the foreseeable future.