bluuebunny/crossref_metadata_2025 huggingface dataset:
HCCI Engine: Advancements in Combustion Control and Potential Innovation in Power Configuration for Vehicles
Authors: He Zhenxi , Yang Xiaohui , Zhang Pengsen
Published: June 2024

Due to the increasingly severe problem of environmental pollution, homogeneous charge compression ignition (HCCI) engines are highly encouraged to be used in lots of countries. HCCI engines aim to reduce load operation and increase efficiency. The potential environmental impact is also discussed and highlights the effect of the HCCI engine on sustainability. Nowadays, hybrid vehicles are becoming increasingly widespread as a possible alternative other than electric vehicles (EV). There are many individuals and companies on the market seeking a much cleaner and more efficient technology for vehicles. This essay will discuss and summarize the positive effect of HCCI engines on combustion control strategies, hybrid powertrain configuration, and the challenge and offer some possible solutions. By examining the cooperativity between HCCI engines and electric motors, there is an overall improvement in fuel efficiency and performance. In addition, some exploration of the real-life examples of car industries that use the HCCI engine or its variant will be demonstrated. The study concludes by stating that the HCCI engine will be a revolutionary step in the future landscape of hybrid vehicles.
Weierstrass Representation of Minimal Surfaces and Related Basic Quantities
Authors: Zhang Weiyi
Published: June 2024

Minimal surface, as an important surface in differential geometry, has long been one of the research topics of many scholars. It provides far-reaching research materials for geometric analysis and nonlinear partial differential equations, and plays an important role in mathematical general relativity. The minimal surface mentioned in this paper refers to the surface with the smallest area when the boundary conditions remain unchanged, i.e., the Plateau problem. The physical counterpart is the soap film experiment. It is different from a surface of constant mean curvature in another sense. Weierstrass discovered that the general solution of minimal surface equations can be given by complex analysis, that is, Weierstrass representation of minimal surface, thus revealing the essential relationship between minimal surface and holomorphic function and meromorphic function. In this paper, the Weierstrass representation of minimal surface is organized, and the first and second basic forms of minimal surface are derived by using its complex vector form. The study of minimal curved surface has played an important role in many fields such as construction engineering, material science and so on.
Present and future of coal use in China
Authors: Bai Zhuohan
Published: June 2024

In recent years, global warming has gradually intensified, and after the signing of the Paris Agreement, countries have gradually established emission targets of "carbon peak" and "carbon neutrality". This paper mainly discusses the main application areas and problems of coal under China's plans to achieve the dual carbon goals in 2035 and 2050 respectively, as well as the challenges China will face in clean coal use in the future. This paper argues that clean energy is an international trend, and countries around the world need to plan energy according to their respective resource endowments. China is in the midst of a transition period from high carbon to low carbon and no carbon. As a matter of current trends, China's total energy demand will still increase, but it is not yet ready to achieve a full replacement of coal from renewable energy. Therefore, in the coming decades, the development of clean coal is an important part of China's sustainable development path. Among China's proven fossil energy reserves, coal accounts for about 94%, which is the energy source with the strongest ability to stabilize the economy and guarantee itself. Deeply understanding China's energy resource endowment and the basic guarantee role of coal, and doing a good job in the clean, efficient and sustainable development and utilization of coal is a choice that conforms to the current basic national conditions and basic energy conditions.
Application of Multi-threading Mechanisms to the Connect6 Gaming System
Authors: Cao Yang , Zhang Meina , Wang Xianjun , Shang Yaqin , Jia Simiao
Published: June 2024

The field of computer games is currently a popular research direction in the field of artificial intelligence, and has a pivotal position in the development and research of artificial intelligence. In the field of computer games, Connect6 is an emerging chess game, whose position complexity and research value are comparable to those of Go and Xiangqi. In the Connect6 game system, there are a large number of branching positions, and the traditional single-threaded search mechanism is time-consuming and laborious, which reduces the search efficiency of the game to a certain extent, so how to find the best positional moves quickly becomes an important factor affecting the strength of the Connect6 game. In this paper, by introducing the multi-threading mechanism in Connect6 intelligent confrontation system, assigning a thread to each branch position, utilizing the computer's multi-threaded parallel computing mechanism combined with a reasonable evaluation method will be able to quickly get the best move for the next move. Through experimental comparison, it can be obtained that in the field of Connect6 game, the multithreaded search mechanism is more efficient for the position search, and also has better game prediction, which can improve the search efficiency and reduce the search time of Connect6 game to a certain extent.
Comprehensive Analysis of Benzene: Synthesis, Applications, and Environmental Impacts
Authors: Wu Yuezhengfei
Published: June 2024

As a cornerstone in producing fuels, plastics, pharmaceuticals, and other commodities, benzene catalyzes innovation and modern convenience. However, its simultaneous classification as a Group 1 carcinogen necessitates a nuanced understanding of its potential detriments alongside its benefits. This concise but comprehensive paper explores the complex characteristics and pervasive influence of benzene, a compound integral to numerous industries and facets of daily life. This study meticulously delineates the adverse health implications of benzene exposure, with a particular focus on its role in the onset of various leukemias. Moreover, the research scrutinizes the environmental repercussions of benzene dissemination through industrial emissions, vehicular exhaust, and other prevalent sources, elucidating its detrimental impact on air, water, soil, and broader ecosystems. In light of these pressing concerns, the paper highlights ongoing initiatives striving to curtail benzene-induced pollution and enhance air quality. These efforts encompass the implementation of stringent regulatory frameworks, the development of cleaner fuel alternatives, and the advancement of emission control technologies. As people navigate towards a future that is both sustainable and health-conscious, the imperative lies in fostering a symbiotic relationship between leveraging benzene's utilities and minimizing its potential hazards to both human health and the environment.
Assessing the Impact of COVID-19 on Automobile Sales in the United States
Authors: Chen Lumin
Published: June 2024

This comprehensive study delves into the COVID-19 pandemic's substantial impact on the American automotive industry, emphasizing its specific effects on sales volume, production, and market demand. It thoroughly examines the sector, including an in-depth analysis of the supply chain and market dynamics. Utilizing a time series model, the research meticulously analyzes data from the onset of the pandemic in early 2020, offering a quantitative assessment of its impact. The findings reveal a significant influence of COVID-19, particularly in the decline of sales volume, which has been alarming for industry stakeholders. Production processes have also faced severe disruptions, leading to challenges in meeting market demand efficiently. Moreover, there has been a notable shift in market demand, reflecting changing consumer preferences and the economic uncertainties triggered by the pandemic. These changes have posed considerable challenges, necessitating strategic adaptations in marketing, production, and overall business strategies within the automotive sector. The study underscores the need for resilience and innovative approaches to effectively address these issues. The study concludes that COVID-19 has had a profound and multifaceted impact on the American automotive industry. It not only highlights the current challenges but also proposes strategic measures for overcoming these hurdles. The study offers valuable insights for future development and innovation in the sector.
Evaluating the role of momentum in tennis based on neural network models
Authors: Zhang Ruochen , Dong Tianrui , Tang Yujie
Published: June 2024

The research on the evaluation mechanism and prediction model of tennis player performance is of great significance and value for improving the quality of matches and cultivating excellent athletes. Firstly, by establishing a scientific and reasonable evaluation mechanism, the technical, physical, and psychological performance of athletes in competitions can be objectively analyzed, providing a basis for developing personalized training plans. Firstly, this article selects five parameters representing the stage performance status of athletes and extracts parameter data. Use clustering algorithm (K-means) to classify data. Based on the calculation of weights for different parameters, a score evaluation formula was established. It also provides indicators for the range of athlete evaluation scores, so that status data can be updated to obtain evaluation values at different times. It also provides a momentum evaluation score calculation function. Based on the calculation function, the total integrated momentum of 100 matches was simulated, combined with the logistic regression algorithm, and the results were compared. It has been found that the use of momentum accumulation evaluation mechanism can predict the success probability of players. Meanwhile, Monte Carlo simulation methods were used to simulate the number of player games under random probabilities. It was found that in 100 games, the performance of players fluctuated and contradicted the actual situation. Therefore, the momentum evaluation mechanism is of great significance for predicting the progress of athletes in competitions.
Principle and Applications of Big Data Consumer Behavior Analysis
Authors: Xu Zilin
Published: June 2024

As a matter of fact, with the rapid development of computation ability as well as machine learning approaches, the usage of big data has long been a theme that has attracted researchers from different fields. To be specific, it includes practical applications in the fields of economy, education, as well as market development. With this in mind, in this article, the author explores the actual use of big data in terms of consumer behavior analysis through different research methods of big data to understand big data. The principle, utilized models as well as procedure for big data analysis will be demonstrated in detail. At the same time, the current limitations of different models will be discussed. Finally, the study puts forward the problems faced by big data and the views on future big data development. Overall, these results shed light on guiding further exploration of consumer analysis based on the state-of-art bigdata analysis scenarios.
Research On Multi-Beam Line Measurement Design Based on Genetic Algorithm
Authors: Ma Yuetong , Li Yanlin , Yang Bohui
Published: June 2024

This paper aims to measure the seabed depth using a multibeam survey line scheme and analyze its performance in a real sea area. The multibeam depth measurement system can send and receive multiple sound waves in a plane perpendicular to the survey line, achieving high accuracy, resolution and efficiency. This paper builds a mathematical model, using geometric analysis, vector algebra, iteration, traversal and other methods, to determine the multibeam depth measurement coverage width model, and find the variable relationship of survey line length, spacing, overlap rate, slope, etc. Using a rectangular seabed slope as an example1, this paper first covers the sea area with parallel survey lines, and then applies the genetic algorithm to calculate the coverage width of different survey line positions, and derive the shortest, full-coverage, overlap rate 10%~20% survey line combination.
The Feasible Way of Public Hospital Reform from "Sanming Medical Reform"
Authors: Zuo Huiyun
Published: June 2024

As the main provider of current medical services, public hospitals bear the medical and health tasks of various cities and make important contributions to protecting the health of residents. Since the implementation of China's new medical reform in 2009, promoting the pilot reform of public hospitals has been one of the important tasks in the medical system. Sanming medical reform dares to be the first, to the people first, from the reform to the present, the reform achievements have been affirmed many times. Sanming medical reform can be summarized as three stages, namely, to cure confusion and stop waste; To establish articles of association and systems; Cure disease, practice the concept of great health. This paper attempts to review the reform process of Sanming medical reform, summarize the feasible experience of medical reform, and point out the feasible road for public hospital reform.
Study On Replenishment and Pricing Strategy of Fresh Merchants' Super Vegetables Based on Time Series Prediction and Optimization
Authors: Li Jin , Zhou Anlan , Wang Yuhang , Yan Yihan , Si Yueran , Zheng Yu
Published: June 2024

Aiming at the problem of vegetable replenishment and pricing strategy in fresh merchant supermarket, this paper makes a replenishment plan based on categories by analyzing the distribution law and interrelationship of vegetable categories and individual product sales. and the total daily replenishment and pricing strategy in the coming week are obtained by using the time series prediction model, so as to maximize the profit. The research methods include data preprocessing, sales law analysis, interrelation analysis, linear regression model, time series prediction model and optimization model. The results show that mastering the distribution law and interrelationship of the sales volume of various categories and individual products of vegetables, and using the time series prediction model and optimization model to formulate the total replenishment and pricing strategy can maximize the profit.
Research Progress in Magnesium-Based Solid Hydrogen Storage
Authors: Chen Guo
Published: June 2024

The materials produced with magnesium for hydrogen storage have the highest potential for growth and have received huge attention because of their low cost, large supply, and excellent hydrogen storage capacity. However, because to its steady hydrogen absorption and emission thermodynamics and slow kinetics, this material's use in hydrogen storage is constrained. Hydrogen uptake and release of materials are thermodynamically stable and slow kinetic, because hydrogen molecules have a high dissociation energy on the surface of Mg, while hydrogen atoms have a slow diffusion rate in the magnesium lattice, which limits its application. Therefore, a large number of research works have focused on the thermal/kinetic modification of magnesium-based materials recently, and has made significant progress. In this paper, the modification methods of the above materials are analyzed, with emphasis on the mechanism of absorption and release of hydrogen, and the influence of alloying, nano crystallization and catalyst addition on optimizing and improving the material properties. Finally, research results are summarized, and the future development direction is discussed.
The Debates on Infinity: A Mathematical History Approach
Authors: Guo Jiayi
Published: June 2024

Calculus and set theory sparked centuries of debate on infinity, which continues today. After discovering paradoxes and inconsistencies, mathematicians and philosophers questioned the underlying systems and conceptions of the infinite. Today, we easily use the infinity sign in our academic work. We often forget infinity's turbulent debut in our contemporary use of the term. David Hilbert wrote "On the Infinite" in the 1920s to persuade sceptics to embrace and use infinity. Gödel and his second incompleteness theorem defeated him very quickly. Beyond Gödel's claim of system inconsistency, Hilbert's theory neglected two factors when seen from a current viewpoint. First is the genuine nature of actual infinity, and second is Zermelo-Fraenkel's (ZF) axiom-based refined set theory. This article will look into the these great achievements and argue the deficiencies of them.
Unveiling Gravitational Wave, Dark Matter, and Dark Energy in Astrophysics
Authors: Liu Yuxi
Published: June 2024

Astrophysics is an important field of physics that has made a lot of achievements in the past hundred years. The research and discovery of gravitational waves is a very influential part of astrophysics, which has the effect of verifying the theory of relativity. This article discusses the relationship between gravitational waves and Einstein's general theory of relativity, which predicts the gravitational wave. This review delves into the genesis and nature of gravitational waves, elucidating their generation from cataclysmic cosmic events like binary black hole mergers and neutron star collisions. This review also emphasizes the meaning of research of gravitational wave in the physics and cosmology. It has played a key role in understanding the expansion of the universe and the behavior of black hole. Through a synthesis of historical, current methodologies and technology, and future aims, this review aims to provide an understanding of the gravitational waves, inspiring continued exploration in this captivating frontier of astrophysics.
Fusion and Application of Chinese Elements in Film and Television Scene Design
Authors: Du Chenying
Published: June 2024

With the continuous development of economy, information and technology, modern technology and art form a huge digital media industry. This unique art form and language of digital media art design has become a globalization era of digital information media of human society the main manifestation. In this trend, the global cultural exchange carries the local cultural elements of various countries to the world exchange through art communication. The use and research of Chinese cultural elements in digital film and television media industry is one of the hot topics. This thesis studies the application of Chinese elements in the field of scene design, taking White Snake as an example, and compares the shortcomings of Chinese elements in scene design. Taking White Snake as an example, this paper analyzes the advantages and disadvantages of integrating this Chinese element into the scene design, and finally considers the development of China's film and television industry. This thesis not only deeply studies the Chinese elements in the excellent films and TV programs, but also deeply realizes the importance of creating the design works with Chinese elements.
Navigating the Financial Landscape: The Power and Limitations of the ARIMA Model
Authors: Liu Jin
Published: June 2024

In today's dynamic world, accurately predicting future trends is crucial. This is the reason why the Auto-Regressive Integrated Moving Average (ARIMA) model has become so important. ARIMA is a statistical tool that helps analyze time series data and make predictions. ARIMA has proven to be incredibly valuable in the finance industry in applications. It greatly improves stock price forecasting with accuracy rates exceeding 70%, which empowers traders and investors alike. By integrating with GARCH models, ARIMA can even reduce portfolio volatility by up to 20%, which is great for risk management purposes. It also plays a role in credit risk assessment, economic forecasting, and option pricing. However, it's worth noting that ARIMA does have some limitations to be aware of. For example, its linear assumptions can lead to errors during events like market crashes. The process of selecting parameters can also introduce subjectivity and uncertainty into the analysis. Additionally, while ARIMA performs well for short-term forecasting it tends to have more significant errors when it comes to long-term predictions. Furthermore, since ARIMA relies on historical data it may not fully account for external factors naturally occurring in the real world. To overcome these limitations and ensure financial analysis and forecasting it's crucial to complement ARIMA with other models.
Huge Potential of HCCI Engine in Rarefied Air Environments
Authors: Ma Zizai
Published: June 2024

Homogeneous Charge Compression Ignition (HCCI) engines represent a significant technological advancement over the traditional Spark Ignition (SI) and Compression Ignition (CI) engines by offering prospects for improving thermal efficiency and emission reduction. This study explores the advantages of HCCI engines in thin air environments specifically, and it delves into latent design considerations such as the square bowl piston, two-stroke engine-inspired type piston, Superchargers and Turbochargers, methanal injections and other considerations. While the HCCI cycle holds substantial potential in the realm of engine technology, inherent challenges are confronted in controlling combustion phasing and maintaining consistent reliability. These pivotal concerns require dedicated attention to be addressed in future studies. In short, with the increasing need for efficient combustion mechanisms, the insights offered herein underscore the importance of improving the HCCI engine's operational range and reliability without compromising its inherent benefits. With continued research and design innovations, HCCI may become the optimal engine of choice for a thin-air environment.
Quantifying the Impact of the COVID-19 Pandemic on Steel Price and Production Trends Using Time Series Analysis
Authors: Darrer Brian Shuai
Published: June 2024

This paper aims to quantify the impact of the COVID-19 pandemic on steel price and production trends. By using time series analysis to identify discernible trends over the past decade, Seasonal ARIMA models and variations of Holt-Winters’ methods were implemented. Historical data, from 2013 to 2020, was used as the training set for steel price and production values to forecast their post-pandemic predictions, from 2020 to 2023. The ratio of the mean absolute percentage errors (MAPEs) of the pre-pandemic model and its post-pandemic forecast against the actual data established a method of quantifying the observed impact on trends. Results showed that the post-pandemic test set values had MAPEs approximately 4-6 times greater than those for the pre-pandemic training set values when compared against the best-fitting forecast models. Providing quantitative evidence that the COVID-19 pandemic impacted steel price and production trends, this analysis enhances the understanding of the steel industry's resilience and responsiveness to external shocks.
Frontier Solar Stirling Engines: Technical Optimization and Wide Application
Authors: Wen Junming
Published: June 2024

As an external gas turbine, the solar Stirling engine uses an external heat source to expand the gas in the inner cylinder to generate power. It can effectively transform solar energy into various kinds of energy and has a broad range of application prospects in the field of sustainable energy since its theoretical foundation is the Stirling cycle, which has the same thermodynamic efficiency as the Carnot cycle. This article elucidates the fundamental principles underlying the Stirling engine, provides an exposition on its three basic types, delves into potential constituent elements, explores avenues for optimization, showcases multiple exemplars of cutting-edge solar Stirling engine applications, and ultimately conducts a comparative assessment of the benefits and drawbacks inherent in solar power generation versus conventional thermal power generation methodologies. It is hoped that after understanding the innovative technology and application prospects of the solar Stirling engine, readers can better understand its importance and potential in the field of sustainable energy and optimize its structure or materials so as to promote the further development of solar Stirling engine.
Assessment of new hydrogen fuel cell technology in Electrical vehicles application and how it would improve the EV’s performance
Authors: Wu Yueyang , Yang Yuwei
Published: June 2024

In light of climate change and air pollution, this paper addresses the urgent issue of sustainable transportation. The potential of Fuel Cell Hybrid Vehicles (FCHVs) utilizing Proton Exchange Membrane (PEM) technology is investigated, focusing on the reduction of greenhouse gas emissions by utilizing hydrogen as an energy carrier. Analyzing the intricate interplay between FCHV control systems and overall efficiency, we explore diverse Energy Management Systems (EMS) strategies' impacts on fuel cell degradation, battery performance, and cost. Through a comprehensive literature review, our research underscores FCHVs' pivotal role in achieving sustainability goals while navigating the intricate landscape of technology, control strategies, efficiency, and environmental imperatives. We also evaluate its social, economic, and ecological benefits compared to traditional vehicles. At last, we address specific gap questions which could be studied in the future.
The Path to Carbon Neutrality in U.S. Focusing on Energy Sector
Authors: Zhou Zilu
Published: June 2024

One of the most important things for human is energy. Literally every physical action by machines requires energy consumption. With the increase of energy consumption, relying solely on fossil fuels is not the right method because fossil fuels have a finite amount, and they are also the main cause of global warming. Therefore, using renewable energies is the best solution. The United States (U.S.) is one of the largest and powerful country worldwide, so the prospects of renewable energies in U.S. can have a great influence in global renewable energies. After full-scaled research and analysis on U.S. renewable energies, two of the most suitable renewable energies for U.S. are nuclear energy and wind energy, which can replace fossil fuels on a large scale. Although both energy sources have their shortages, they are the most applicable solution to achieve carbon neutrality, and they both have a bright future in the U.S.
E-Commerce Demand Forecasting Using SARIMA Model and K-means Clustering Analysis
Authors: Zhao Yiding
Published: June 2024

E-commerce has become a significant driver in the retail industry within the digital era, with escalating online transaction volumes. Accurate demand forecasting and effective inventory management are crucial for retailers to minimize costs related to overstock and stockouts while maximizing customer satisfaction and revenue. This study explores the application of advanced time series models for demand forecasting by e-commerce retailers, with a particular emphasis on the Seasonal Autoregressive Integrated Moving Average (SARIMA) model. The SARIMA model, an extension of the ARIMA model, incorporates autoregression, moving averages, and accounts for seasonal variations, making it suitable for analyzing data with regular periodic patterns, such as seasonal fluctuations in consumer purchasing behavior. The study methodology includes data preprocessing, establishment of the ARIMA model, construction of a Linear Regression (LR) model, development of the SARIMA model, demand forecasting, and clustering analysis. The SARIMA model demonstrated higher fit and predictive accuracy compared to traditional LR and ARIMA models, as substantiated by the 1-mWAPE and RMSE metrics. The application of the K-means clustering algorithm enhanced the homogeneity of demand forecasting and improved the model's adaptability to new sequence data. Cluster analysis categorized products into four classes, with more similar demand characteristics within each class, aiding the model in more accurately capturing potential demand changes. In conclusion, this research confirms the effectiveness and practicality of combining the SARIMA model with the K-means clustering algorithm for e-commerce demand forecasting.
Design of Offshore Wind-Powered Pump-Propelled Environmentally Friendly Ship Based on Spiral Vertical-Axis Wind Turbine
Authors: Chen Wenzhuo , Zhang Yibing , Liu Huiying
Published: June 2024

In this study, a new concept offshore wind-powered pump-propelled environmentally friendly vessel is designed for offshore navigation to protect the marine environment. The ship adopts shaft-vertical wind power generation technology and pump-propulsion technology, which will greatly promote the upgrading and innovation of existing ships in terms of power. In addition, the launch of the vessel will further promote the development of marine power batteries and the application of vectorial magnetic hydrodynamic propulsion technology. By adopting this environmentally friendly ship, environmental pollution in offshore coastal areas can be reduced and marine protection can be promoted. If the ship is successfully launched, it will make an important contribution to China's shipping industry and environmental protection.
Research on the Models for Forecast of Tax Revenue of Wenzhou City
Authors: Xie Hanqi
Published: June 2024

Tax revenue is a vital economic indicator that reflects the level of economic development, and tax revenue forecasting plays an important role in financial budgeting. Previous studies have demonstrated various influencing factors of tax revenue and proposed many feasible ways to forecast tax revenue. However, it is acknowledged that tax revenue of different region might bear different relation to influencing factors. In this research, tax revenue forecast of Wenzhou City is studied based on multiple linear regression model and MLP neural network model. The data for this research are collected from the website of Bureau of Statistics of Wenzhou, compiled in the 2022 statistical yearbook of Wenzhou. With multiple linear regression model, it is discovered that Value-added of the primary industry, Value-added of the tertiary industry, Investment in fixed assets, Total retail sales of consumer goods are significant for prediction. Comparing the forecasting outcomes of the two methods, the MLP neural network model appears to have better goodness of fit.
Long-term Clinical Efficacy Evaluation and Prognosis Analysis of Deep Infiltrating Endometriosis in Young Patients
Authors: Zu Meng
Published: June 2024

The purpose of this study is to evaluate the long-term clinical efficacy of young patients with Deep Infiltrating Endometriosis (DIE) and analyze the related prognostic factors. Through retrospective analysis of a group of young patients, the survival curves of different treatment methods were compared, and the effects of age, course of disease, treatment methods and complications on prognosis were discussed by logistic regression model. The results show that surgical treatment has obvious advantages in improving the long-term prognosis of patients compared with drug treatment. At the same time, the prognosis of young patients with short course of disease and few complications is relatively good. This study provides a useful reference for clinicians to formulate personalized treatment plans and prognosis strategies, which is helpful to improve the quality of life and prognosis of young patients with DIE. However, there are still some limitations in the study. In the future, it is necessary to further expand the sample size, extend the follow-up time, and explore more potential prognostic factors in order to improve the understanding and treatment strategy of the disease.
Research Progress on Silver Nanoparticles in the Prevention and Treatment of Oral Diseases
Authors: Zhao Xiaolin , Liu Xuan , Zhao Gaoye , Gu Jianqi , Dong Qing
Published: June 2024

Silver compounds and silver nanomaterials have shown excellent antimicrobial effects on microorganisms and have been used commonly in the clinic in recent years for the prevention and treatment of a variety of oral diseases, such as caries, gingivitis, pulpitis, dentin hypersensitivity and oral cancer. Since conventional silver and silver compounds lead to tooth staining, studies have indicated that silver nanoparticles can alleviate this problem and exhibit outstanding antimicrobial effects. Nowadays, nanomedicines have become a research topic as an emerging potential anticancer therapeutic drug. These nanomedicine carriers are characterized by intelligent response to the tumor microenvironment, which can deliver the drugs precisely to the tumor site and improve the therapeutic effect. Nanomedicine can also decrease the distribution of drugs in normal tissues, reduce side effects, and improve patient tolerance to treatment. The application of environmentally responsive nanomedicine in the treatment of oral squamous carcinoma demonstrates great potential and may become a novel strategy for the treatment of cancer. Consequently, the article provides a comprehensive overview of the advances in the application of silver materials in the prevention and treatment of oral diseases, as well as describes the possibility of nano-targeted therapy as an innovative strategy for the treatment of oral squamous carcinoma, which provides a new way of thought in tumor therapy and brings new expectation for enhancing the effectiveness of cancer treatment.
Traditional and Advanced Technologies in Intelligent Transportation Systems
Authors: Zhu Lingwen
Published: June 2024

In the past decade, rapid urbanization and the increase in vehicles have worsened traffic conditions. Intelligent Transportation Systems (ITS) are considered an ideal solution to optimize urban transportation and tackle traffic challenges. This article comprehensively discusses the current development of basic and new technologies used in ITS. It includes specific subdivisions for these technologies, their application in ITS, as well as current and potential future challenges. The review indicates that vehicle-to-everything (V2X) communication technology is increasingly focused on the advancement of Cellular V2X (C-V2X). Sensor technology research and development has reached a high level of maturity. Reinforcement learning as a robust machine learning algorithm, is being extensively applied in traffic management. The article also provides examples of recent research-based applications using these technologies and explores potential directions for their future development. These reviews and analyses can serve as practical references for traffic managers and researchers working on further advancements in ITS.
The Temporal and Spatial Distribution Patterns and Influencing Factors of Typhoons’ Intensity in East Asia
Authors: Huang Haoyang
Published: June 2024

Against the backdrop of global climate change, extreme weather events are becoming increasingly frequent. Typhoon disasters are among the most frequent and severe meteorological disasters globally. This study, in conjunction with sea surface temperatures and other environmental factors, explores the environmental conditions conducive to the formation of super typhoons and how environmental factors may exacerbate the adverse impact of super typhoons on human life. The study reveals that typhoons are characterized by high occurrence probability, great intensity, unpredictable paths, and wide-ranging impacts. As a mid-sized weather system, typhoon generation and distribution are significantly influenced by natural conditions. By analyzing historical data, it becomes evident that there are distinct patterns in the temporal and spatial distribution of typhoon generation sites. For instance, the likelihood of typhoon formation is greater over warm ocean surfaces during the summer season. To investigate the influence of environmental factors on the intensity of typhoon generation and development, as well as their impact on human production and life, this paper conducted relevant analyses. The research indicates that in the low-latitude ocean surface of the western Pacific with temperatures ranging from 30°C to 30.5°C, particularly from July to September, super typhoons are more likely to occur, posing a greater impact on human production and life in East Asia. Based on the findings, future research on the relationship between typhoon intensity and typhoon generation areas can be further advanced.
An Initial Exploration of the Historical Development and Origin of the Guzheng
Authors: Kang Yijie , Sh Ariunaa.
Published: June 2024

The guzheng (ancient zither), also referred to as han zheng, qin zheng, yao zheng, and luan zheng, is hailed as the “King of Music” and the “Eastern Piano.” It holds a significant place as a plucked instrument within the realm of traditional Chinese musical instruments, serving as a unique and important national treasure in China’s musical landscape. Dating back to the Spring and Autumn period (770–476 BCE) and the Warring States period (475–221 BCE), it gained popularity in Shaanxi and Gansu regions. In 237 BCE, Li Si vividly depicted a traditional guzheng performance in his correspondence with Qin Shi Huang, describing the performer’s actions and the captivating music, henceforth leading to the instrument being commonly referred to as “Qin zheng.” He wrote, “The performer strikes the drum and beats the fou (an ancient Chinese percussion instrument), plays the zheng while rhythmically patting their thighs, and sings with deep emotion. The authentic music of Qin delights both the eyes and ears.” This study endeavors to delve into the origin and evolution of the guzheng, providing a dependable resource for the vast community of guzheng enthusiasts and practitioners.
The Current Research Status of Imaging Assessment of Bone Disease in Multiple Myeloma
Authors: Zhou Jing
Published: June 2024

With rapid advancements in the diagnosis and treatment of bone disease in multiple myeloma (MBD), Imaging assessments play a crucial role in the diagnosis and management of MBD. Traditional whole-body X-ray has been commonly used. Whole-body low-dose computed tomography, whole-body MRI, and 18F-FDG PET/CT are more sophisticated techniques that have been recommended for the initial assessment of MM-related lytic bone lesions. MRI remains the gold standard for bone marrow involvement detection, while PET/CT offers valuable prognostic data and is preferred for therapy response assessment. Diffusion-weighted MR has been shown to be superior to both skeletal X-ray and MRI of the spine for detecting focal lesions in MBD. Diffusion-weighted MR is a functional imaging technique that effectively detects bone disease changes according to treatment response and can be used to monitor disease response. Advanced imaging techniques have significantly improved the sensitivity for detecting MBD. This review focuses on the imaging modalities available for MBD patient management, highlighting advantages, disadvantages, and applications of each.
Optimal combination choice of submersible search and rescue equipment based on AHP-multi-objective planning
Authors: Zhang Xinyang
Published: June 2024

There are a variety of accidents that can occur when a submersible is traveling in the ocean. The main solution to improve the survival rate of the passengers in the submersible is to optimize the combination of search equipment on the main ship. In this paper, the preparation cost, maintenance cost and usage efficiency of different types of equipment are firstly identified as decision variables, safety, availability and inter-equipment compatibility as constraints, and minimization of total cost under the premise of maximizing usage efficiency as the objective function. By establishing a multi-objective planning model, the optimal equipment brand is found. Finally, the optimal equipment combination is solved by the combination of a robotic arm, Forum Sub-Atlantic Mohican ROV, and an underwater light, Underwater Kinetics Aqualite Pro, and the minimized overall cost is $90, 619. 05. This result not only reduces the cost of submersible search and rescue, but also improves the search efficiency, which is a strong guidance for the future underwater search and rescue field.
Prediction model of Illegal Wildlife Trade using genetic algorithm and Bayesian optimization
Authors: Li Ziqi , Sun Yiming , Wei Jiayu , Gao Yan , Li Yifei
Published: June 2024

In this paper, genetic algorithm and Long Short Term memory network (GA-LSTM) are used to predict the amount of global illegal wildlife trade, and differential method and Bayesian optimization support vector machine (SVM) are used to predict the future trade volume of high-risk countries. GA-LSTM model combines the memory retention ability of LSTM and the optimization ability of genetic algorithm, and performs well on time series data. The differential approach identifies strict international wildlife trade restrictions that significantly reduce the volume of trade, while large-scale infrastructure investments have a positive impact on raising local incomes. Bayesian optimization support vector machine (SVM) finds the global optimal parameters of the model through the probabilistic proxy model and the return function. The results of this paper provide data support for the government to strengthen governance.
Exploring the dynamic performance of tennis matches: a comparison of momentum models based on neural networks and entropy weighting methods
Authors: Hu Qishu , Pei Chengdong , Qi Yongqiang
Published: June 2024

The aim of this paper is to develop two models to evaluate the performance of players in tennis matches, which these studies refer to as "momentum models". This paper described the process of building a momentum model, which included the building and solving of two models based on Artificial Neural Network (ANN) and Information Entropy Weighting Method (EWM). In the ANN-based model, the authors first constructed a neural network structure that could perfectly handle a given dataset and prove its effectiveness through comparative experiments. Then, the authors interpreted and validated the output results for the model to reflect its ability to describe the momentum of the race. In the EWM-based model, the authors determined the weights of the features through the information entropy weighting method, which were used to calculate the momentum of the players in the match, and demonstrated the changes of the momentum through linear and scatter plots. Subsequently, the authors compared and analyzed the momentum with the score and comprehensively evaluated the player's performance by calculating the cumulative momentum. Finally, the authors evaluated the generalization performance of the model and found that the model showed good generalization ability under different training set sizes and different feature conditions. The results of the study showed that the authors' proposed model could effectively evaluate players' performance in tennis matches and have strong generalization ability.
Unveiling Gender Inequality in American High School Golf: A Time Series Analysis and Future Prediction
Authors: Wu Han
Published: June 2024

Gender inequality remains a significant and persistent issue in golf. While some scholars have studied its historical origins, current status, and measures, there is a dearth of research focused on high school golf. Few studies have explored the specific challenges female high school golfers face, accurate predictions for future trends are lacking. This study uses a time series chart to visualize the male-female ratio of high school golf players in the United States from 2010/2011 to 2021/2022. The data is then fitted into an ARIMA model to forecast future trends. The visualization of the data reveals a significant increase in female participation from 2010/2011 to 2021/2022, although it remains lower than that of males. Despite some progress over the past 12 years, true gender equality in high school golf has not yet been achieved. The predictions indicate a decline in the female participation ratio from 2022/2023 to 2033/2034, highlighting the insufficient efforts to promote gender equality in sports. This lack of effort hinders sustained and stable progress in female participation. The results of this study have brought about a greater awareness of the severity of gender inequality in high school golf. This has prompted stakeholders to take stronger action to prevent the exacerbation of gender inequality issues in high school sports and collectively build a more inclusive sports environment free from gender bias and discrimination.
Research and Application of Submersible Position Prediction Model Based on Kalman Filtering
Authors: Zhang LingPeng , Xiong HaoRan , Xu XuanMing
Published: June 2024

In this study, a positioning prediction model is proposed for the submersible position prediction problem based on the Kalman filter algorithm. First, the problem is analyzed to determine the uncertainty factors involved in the prediction of the position of the submersible, such as the propulsion of the submersible, ocean currents, seawater density and seabed topography. Subsequently, a position prediction model based on Kalman filtering algorithm is established, including the steps of state definition, system dynamic model, observation model, definition of initial state and covariance matrix, Kalman gain calculation, state update, and state prediction at the next moment. For the equipment requirements involved in the model building process, the factors affecting the position prediction of the submersible are analyzed and the corresponding equipment requirements are proposed. Finally, Python software is utilized for model fitting and prediction, and the fitting accuracy of the model is evaluated by mean square error and mean absolute error, and the results show that the model has a good fitting effect.
The Relationship between Land Use and Bicycles: A Case Study in the Manhattan Area of New York City, USA
Authors: Shi Jiawei
Published: June 2024

With rapid, sprawling cities, travel is becoming increasingly car-orientated, which can create several problems. Smart growth strategies are seen as an effective way of dealing with this problem, centered on the interrelationship between transportation and land use. However, this relationship is still being determined. This paper uses various regression methods based on bicycle trip data from the Manhattan area of New York City, and explores the relationship between the number of restaurants, amenity facilities, income, rent, population, and the number of trips. The results show that the account of shopping facilities, rent, and population performs better and has a more significant positive correlation with the number of bicycle trips due to its better R-squared value and smaller possible multicollinearity. Triggered discussion on the impact of land use mix on travel selection. It illustrates land use mixing significantly reduces car trips, increases the use of surrounding transport facilities, and is politically feasible.