bluuebunny/crossref_metadata_2025 huggingface dataset:
Kegiatan Berbagi Kasih: Pembagian Bubur Kacang Ijo Untuk Anak-Anak Yatim Piatu Sebagai Bentuk Kepedulian Sosial di Panti Asuhan Puteri Melati `Aisyiyah
Authors: Nurul Hidayat  , Januari Darung  , Kartini Kartini  , Nirwana Nirwana  , Syarima Z  , Qoningatun Nashikhah
Published: December 2024

Sharing love is a form of caring for others, especially for orphans in orphanages. On Friday 20 September 2024, we held a love sharing event by distributing green bean porridge to orphans at the Puteri Melati `Aisyiyah Orphanage in Sebengkok, Tarakan. This event aims to provide simple happiness and strengthen ties between the community and children in orphanages. Social activities such as sharing food are often considered trivial. In fact, for those living in orphanages, healthy and nutritious food is an important need that is sometimes difficult to meet regularly. By distributing green bean porridge, we not only provide nutritional intake that is beneficial for the body, but also provide happiness and new enthusiasm for the children there. This activity is a form of love that they can feel directly, both through the taste of the food they enjoy and through our presence who provides attention and care. Apart from that, green bean porridge has its own meaning in the tradition of sharing in Indonesian society. As a food that is often associated with moments of togetherness and mutual cooperation, green bean porridge is a symbol of simplicity and sincere love. When this porridge is distributed in orphanages, it is not just food, but becomes a symbol of concern from those who care about the welfare of the children there.  Social concern is an attitude of connection with humanity in general, an empathy for every member of the human community, for example female students. Community service is one of the media to hone student awareness in carrying out community service.
Pendampingan Kegiatan Rapi Administrasi di UKM Pakis Malang
Authors: Muhammad Syafriel  , Novy Karmelita Indrawati
Published: December 2024

It very important for business administration to e carried out in a structured and consistent manners in its execution. If it is not done well, it will become negative feedback in the course of the business and will reduce competitiveness. The activity of administraive tidiness is used for continuous improvement of the administrative system by adjusting the availale resouces, including human resources and technology. This community service aims to provide insights, knowledge, and skills in the implementation of administrative therapy activities through socialization, training and guidance on administrative writing, particularly in production and warehousing. The implementation leads to improved efficiency and effectiveness in working time, tidiness and ease of work. In addition, it makes coordination between employees and departements easier, while accountability is achieved.
Comparative Analysis of Higher Education Funding Policies in China and the UK from the Perspective of Education Finance
Authors: He Ying
Published: December 2024

China and the United Kingdom have numerous similarities when it comes to higher education funding policies, and both have gone through a process from “single” to “diverse”. The purpose of this paper is to make a comparative study of the higher education funding policies in China and the UK from the perspective of education finance, and to expose the similarities and differences through an in-depth analysis of the higher education funding objects, funding methods, funding subjects, and repayment methods in the two countries, and to find that there are problems in China’s higher education funding, such as the limited scope of funding, the lack of coordinated student financial aid institutions, the imprecision of funding, and the imperfect repayment system. Learn from the successful experience of the United Kingdom and propose to integrate into the construction of a subsidized education environment for China’s higher education funding; Improve targeted funding and people-oriented; Establish a complete repayment system and extend the repayment period to ensure that more students graduate smoothly and promote educational equity.
Gender Differences in Cultural Context: A Systematic Review
Authors: Guo Suhan
Published: December 2024

Gender studies’ core competencies include comprehending gender dynamics and how they might promote gender equity. The foundational gender norms that shape individual behaviors and societal expectations are critically examined and evaluated in the field of gender studies. These norms significantly influence on various aspects of our lives, such as the formulation of policies, the structure of educational systems, and the direction of activist movements. The field aims to uncover how these underlying principles perpetuate certain stereotypes and inequalities and subsequently inform and drive decision-making processes in both personal and societal contexts by scrutinizing them. This approach strengthens partnerships and provides long-term satisfaction. Effective communication requires respect for cultural differences and learning from each other’s strengths. Combining empathy with problem-solving skills fosters mutual respect, collaboration, and innovation, benefiting both individual interactions and group success. Gender and culture influence social behavior and relationship formation, with female culture emphasizing emotional support and male culture focusing on competition. Cultural contexts and gender roles vary across societies, affecting expectations. Future research could explore how globalization and changing cultures impact social interactions.
Application of Home-Based XR Art Experiences for Emotional Healing in Elderly Individuals with Mobility Issues: Eye-Tracking and Virtual Natural Landscape Design
Authors: Huang Zhenqi
Published: December 2024

With the rapid development of Virtual Reality (VR) and Augmented Reality (AR) technologies, Extended Reality (XR) is increasingly demonstrating its potential in the field of emotional healing. This paper focuses on the application of home-based XR art experiences for emotional healing in elderly individuals with limited mobility. Through immersive interactions and the design of virtual natural landscapes, XR helps alleviate psychological stress and anxiety, enhancing the well-being of elderly users. In addition to analyzing how XR technology, through eye-tracking and multimodal affective computing, combined with personalized and contextual design, provides emotional healing and psychological support for elderly users, this paper proposes several recommendations for future XR system designs. Specifically, it suggests improvements in adaptive interface design, integration of physiological feedback, and the enhancement of virtual social functions to better meet the emotional needs of elderly individuals, ultimately improving their quality of life.
Research on the Integration of Toys and Electronic Devices and Its Development Trends
Authors: Zhou Zijing
Published: December 2024

With the maturation of VR/AR technologies, advancements in 3D printing, and the practical application of AI, an increasing number of everyday objects are becoming intelligent. Meanwhile, the traditional toy market is nearing saturation, and parents’ educational perspectives are evolving. This raises the important question of whether digital technologies can provide solutions to integrate new technologies into toys, thereby enhancing their educational value, interactivity, and playability. Toy design has always been a sensitive topic; many new technologies, despite their maturity, often remain at a distance from the toy industry. This article aims to analyze the applicability of new technologies in the direction of toy design. Using literature review and case study methods, this paper examines the historical development of toys and analyzes both positive and negative cases of integrating new technologies with toys. The findings reveal that the toy sector is often one of the last areas to be impacted by the proliferation of new technologies. For new technologies to be applied to toys, they must undergo thorough evaluation and consideration from multiple perspectives. Subsequently, the paper analyzes the applicability of VR/AR and 3D printing technologies in toy design, summarizing their advantages and existing challenges within this field. Finally, the article offers insights into the future development of toys.
Impacts of Global Warming on different Climate Feedback and related Management
Authors: Ma Luoxuan
Published: December 2024

Global warming is a significant environmental issue caused mostly by increasing emissions of greenhouse gases, specifically carbon dioxide (CO2). The substantial release of CO2, primarily caused by human activities such as the burning of fossil fuels, industrial operations, and agricultural practices, plays a significant role in the Earth’s temperature increase by trapping heat in the atmosphere. This paper analyses the mechanisms by which CO2 intensifies global warming and investigates its environmental consequences, specifically focusing on climate feedback networks. Notable feedback mechanisms that contribute to global warming include water vapour, cloud, and ice-albedo feedback. These feedbacks interact with atmospheric conditions in various ways, leading to an intensification of global warming. Efficient methods to reduce the impact of a problem involve the implementation of both governmental actions and developments in technology. These can include steps like setting a price on carbon emissions, adopting renewable energy sources and implementing sustainable transportation solutions. To limit the adverse impacts of global warming, it is crucial to tackle CO2 emissions and adopt pioneering energy and environmental policies.
Investigation on Spatial Spillover Effect of Transportation Infrastructure on Regional Economy in Yangtze River Economic Belt of China
Authors: Luo Wangshu
Published: December 2024

Exploring the mechanism of the spatial distributed impacts of transportation systems on the local economy helps realize the coordinated development of the local economy and environmental protection. Therefore, correlation tests are conducted using linear regression models, decision tree regression models, machine learning random forest regression models, and spatial econometric models in this study. An extensive analysis was carried out to determine the relationship between the transport infrastructure of the Yangtze River Economic Belt and the impact on regional economic mechanisms and transmission paths from the spatial spillover effect. The three models are compared and analyzed to select the best model. Then the Moran index is calculated to study whether the data have spatial correlation and spatial difference. After confirming the spatial impact of the data, the Lagrange Multiplier test, the Likelihood-Ratio test and other relevant tests were used to select the spatial econometric model that best fits the data set. Finally, the study results show that the random forest model has a higher R2 of 95.14%. To analyze spatial economics, it is recommended to use the fixed effect and double fixed effect of the Spatial Durbin Model (SDM). Road and Density of the transportation network explain GDP more significantly.
The Evolution of Modern Film Business Models: Case Study of Netflix
Authors: Ding Ziheng
Published: December 2024

With the rapid development of digital technology and changes in the market environment, the business model of the global film industry is undergoing a profound transformation. The rise of streaming media platforms has broken the monopoly of traditional cinemas and redefined the way films are distributed and consumed. International distribution and cross-border marketing have accelerated the globalization of the film industry and made the cultural dissemination of films more widespread. At the same time, cross-industry cooperation and brand licensing have become an important means of profitability for the film industry, promoting diversified sources of income. Through typical case studies of streaming platforms, international distribution strategies and cross-industry marketing, research has shown that flexible use of data and cross-border collaboration is key to the future success of the film industry. This study reveals the innovative paths of the film industry in the face of technological advancement and market globalization. It explores how film companies can respond to the current challenges and opportunities through flexible business models.
Case Studies of Management and Maintenance of Sustainable Urban Drainage Systems in Extreme Weather
Authors: Zhang Ruijie
Published: December 2024

Since 1997, Sustainable Urban Drainage Systems (SUDS) have been promoted globally to manage urban stormwater and wastewater. Approaching the third decade of the development of SUDS, this paper explores the management and maintenance of SUDS under extreme weather conditions, focusing on case studies in Singapore and Australia, respectively. Active, Beautiful, Clean (ABC) Waters Program of Singapore integrates blue-green infrastructure to manage stormwater, enhance water quality, and provide social and ecological benefits. In Australia, Water Sensitive Urban Design (WSUD) incorporates natural systems to handle stormwater and reduce urban heat. The study investigates how each region has developed effective SUDS strategies tailored to their distinct climates. While Singapore focuses on managing rapid vegetation growth and maintaining water quality, Australia adapts to challenges like drought, variable rainfall, and fire risks. This research underscores the importance of innovative, site-specific solutions in enhancing urban resilience and offers valuable insights for sustainable urban water management worldwide.
A Criticism of Russell’s Theory of Definite Descriptions
Authors: Zhan Luman
Published: December 2024

Bertrand Russell’s Theory of Definite Descriptions, introduced in his 1905 paper On Denoting, offers a logical framework for analyzing sentences involving definite descriptions, breaking them down into existential and universal quantifiers. While influential, this theory has faced substantial criticism, particularly from P.F. Strawson and Keith Donnellan. This paper critiques Russell’s approach by arguing that it overlooks the role of presupposition and context in ordinary language. Strawson emphasizes how presupposition failures in non-referring descriptions result in truth-value gaps, while Donnellan distinguishes between referential and attributive uses of definite descriptions, demonstrating that Russell’s theory inadequately accounts for these linguistic nuances. By examining these criticisms, the paper argues that while Russell’s theory provides a valuable framework for formal logic, it falls short in accurately reflecting the complexity of everyday language use. This analysis explores the ongoing philosophical debate surrounding the relevance of Russell’s ideas and the challenges posed by alternative approaches to definite descriptions.
Research on Stock Price Prediction by LSTM
Authors: Jin Yihong
Published: December 2024

The stock market’s influence on the contemporary economy is profound, with its fluctuations directing the investment strategies of traders and investors. The intricacies and volatility of the market have consistently drawn the interest of data scientists. Forecasting stock prices is a complex task, influenced by various factors, ranging from individual company financials to global economic indicators. The effectiveness of Long Short-Term Memory (LSTM) models in predicting stock prices has been demonstrated in multiple studies and practical applications. They can capture non-linear trends and seasonal patterns in stock price movements, providing valuable insights for investors and traders. For those interested in implementing LSTM models for stock price prediction, numerous resources are available, including tutorials, research papers, and platforms that offer pre-trained models or APIs for financial forecasting. This study aims to develop a deep learning framework using LSTM networks to identify underlying trends within the data. The objective is to predict future stock market price movements by leveraging LSTM’s ability to model time series data effectively. By tapping into the predictive power of LSTM, this model can seek to provide investors with a sophisticated tool for making well-informed investment decisions, enhancing the precision of stock price predictions.
Research Progress and Application Prospects of Multimodal Brain-Computer Interface Technology
Authors: Hong Xin
Published: December 2024

In the past decades, the rapid development of brain-computer interface (BCI) technology has provided new perspectives on human-computer interaction. Traditional single-modal BCI systems, although showing promising results in many applications, still face challenges in terms of decoding accuracy, real-time performance, and user adaptability due to limitations in signal acquisition. To address these issues, multimodal brain-computer interfaces (MMBCIs) have emerged, aiming to improve the overall system performance by integrating information from different physiological signal sources. This paper reviews the basic concepts, signal sources, signal fusion techniques, application examples, and current challenges and future perspectives of multimodal BCI. By analyzing the existing research literature, we hope to provide theoretical guidance and framework support for further research in this area.
Development Trend of Tropical Cyclones under Climate Change
Authors: Li Peiqi
Published: December 2024

Climate change presents a significant global challenge, with one of its effects being the alteration in the frequency and intensity of tropical cyclones. These shifts in cyclone patterns threaten both human societies and economic progress directly. This paper aims to study the effects of climate change on the development trend of tropical cyclones. As the planet continues to warm, there is a growing emphasis on how such intense natural phenomena will change in terms of frequency, intensity, and trajectory. This study examines the impact of climate change on warmer sea surface temperatures, atmospheric conditions, and tropical cyclone distribution. It employs historical data, future projections, and recent case studies to investigate these phenomena. The findings suggest that while the overall frequency of tropical cyclones is anticipated to remain relatively consistent in a warmer climate, with a slight decline, the intensity of these storms is likely to increase significantly, resulting in considerably larger impacts on coastal populations. The study also highlights the pressing need for disaster preparedness and mitigation strategies, particularly in highly vulnerable areas, to reduce the socio-economic losses from more frequent, intense tropical cyclones in the future.
Guzheng Teaching Based on the Orff Approach
Authors: Han Yuntong , Wang Qianhui
Published: December 2024

This paper primarily studies the application of the Orff Approach in music class and integrates its basic concepts and methods into Guzheng teaching. The characteristics of the Orff music method emphasize students’ active participation and creative expression. Music can cultivate students’ musical abilities as well as their intellectual, emotional, social, and other developmental aspects. Influenced by traditional teaching models, many Guzheng instructors tend to focus too heavily on skills, neglecting the essential nature of rhythm and the actual needs of students, which ultimately affects teaching outcomes. Therefore, integrating the Orff Approach into Guzheng class may help improve the current situation.
Research on the Strategy and Practical Path of Promoting Low Carbon Development through Green Finance
Authors: Xu Xiyu
Published: December 2024

Green finance has become a highly anticipated hot topic, and its extensive promotion has sparked a widespread research trend, attracting the attention and discussion of numerous scholars and the industry. This article explores the practical path of promoting low-carbon development through the green finance in clean energy conservation and emission reduction. This study describes the challenges and countermeasures that green finance may face in promoting low-carbon development, effectively addressing the challenges faced by green finance in promoting low-carbon development, further promoting the maturity and improvement of the green finance system and providing solid financial support for achieving low-carbon development goals. This article proposes the following suggestions for the future development of green finance: firstly, efforts should be made to increase the training of green finance professionals to ensure that the industry has sufficient reserves of high-quality talents; Secondly, strengthen cooperation carry out research and practice together with universities and research institutes in actual situations of green finance projects, and promote the deep integration of theory and practice; In addition, people should actively build an ecosystem for green finance, promote collaborative cooperation among government, enterprises, financial institutions, and various sectors of society, and form a strong force about promoting the development of the green finance. Through these measures, the aim is to make China’s green finance development smoother and more effective in addressing the urgent need for sustainable development in the low-carbon economy era.
Research on Movie Trailers’ Effectiveness in Attracting Audiences and Enhancing Marketing Strategies
Authors: Yan Yilong
Published: December 2024

The dynamic film industry has witnessed significant growth in theaters, movie screens, and new releases, making movie trailers a crucial element in shaping viewer perceptions and driving box office success. However, current trailer marketing strategies face challenges, including excessive use of spoilers, lack of originality, and a stagnant approach to trailer formats, which risk diminishing audience interest and engagement. To address these issues, businesses can implement spoiler warnings, emphasize unique selling points (USPs), and leverage audience data to create more targeted and effective trailers. Additionally, fostering creativity by exploring diverse formats and techniques can help distinguish films in a crowded market. This paper introduces the concepts of cross-cultural marketing and audience targeting, analyzes the phenomenon of over-marketing on social media platforms like TikTok, and offers practical suggestions to enhance trailer marketing strategies. By adopting these innovative approaches, the film industry can improve the movie-going experience while optimizing marketing efforts and sustaining its growth in an increasingly competitive landscape.
A Turn-Taking Perspective on the Gender Difference and Power Relations
Authors: Hao Yuting
Published: December 2024

The difference of power relations caused by gender difference is a very common phenomenon in society, which has a profound impact on the way of communication between the two sexes in daily life and the harmony and unity of society.Since 1997, several Chinese academics have studied this subject in great detail; however, their study has not yet produced a cohesive theory explaining the particular gender concerns that arise in everyday conversations. Thus, this study gathers the entire corpus of three groups of research objects and examines their various power relations under particular gender issues using the conversational research analysis approach.. Finally, it is found that the research subjects will develop variables during the study, that is, they are driven by interest and influenced by the demands that women want to express, which can analyze the differences in power relations, and then achieve the purpose of amicable communication between the sexes.
The adverse effects of dissolved organic matter on water bodies and in-depth exploration of management methods
Authors: Chen Yicheng
Published: December 2024

Dissolved organic matter (DOM) accounts for a great proportion of organic carbon in all aquatic ecosystems and is often a vital carbon resource for heterotrophic microorganisms. According to the Wet-chemical analysis and 1 H- and 13C-NMR spectra, it is clearly showed that both DOM fractions from the urban waste compost were low in neutral, acidic and amino sugars as well as in lignin derived compounds. In this article, directly or indirectly impacts of the human activities on water bodies are mentioned and the eutrophication, a common and harmful phenomenon of pollution, is introduced as one of the well-known results of concentrated DOM. As a result, human found several methods to remove the DOM. The most likely treatment to be implemented at present is Granular Activated Carbon Filtration (GAC), but it has been narrowly defeated due to its inability to meet the demand for large-scale deployment. Other solution like membrane materials and water-soluble materials are also competitive for organic water pollution removement.
Analyzing Relationship Between Distance Covered in a Soccer Game and Defensive Performance by Regression Models
Authors: Chen Zixuan
Published: December 2024

Regression models are widely used in sports research, and there are mainly for two purposes: prediction and effect estimation. The article focuses on providing better strategies for soccer teams’ managers based on analyzing data, which is related to the team’s defense particularly. The methodology designed to find distance covered by a team as an indicator of its defensive performance. By using multiple regression models, the best fits for specific teams are created. Then based on the curve derived, the relationship between the distance covered and the players’ defensive performance can be found. It is concluded that for some teams the two variables do not relate to each other. By contrast, for the teams do, though the specific relationship for each team differs slightly (they fit in different models), the defensive performance increases in intensity as distance covered increases. This detailed result may assist managers in changing tactics, injury prevention, player selection and training management.
Linear Regression Analysis of Stock Price Dynamics in China’s Alcohol Industry
Authors: Chen Yinuo
Published: December 2024

This paper investigates the stock price dynamics of China’s alcohol industry, with a particular focus on Maotai’s stock performance during the COVID-19 pandemic. The multiple linear regression models to analyze 441 groups of data from 2018 to 2024 show the impact of six economic factors-National Housing Prosperity Index, Retail Sales of Consumer Goods, Insurance Asset Management Registration Size, Public Finance Revenue, Consumer Price Index (CPI), and Keqiang’s Index-on Maotai’s earnings per share (EPS). The results indicate a strong positive correlation between the National Housing Prosperity Index and EPS. A key finding was the pandemic-induced shift in consumer behavior, favoring stable investments in high-end liquor like Maotai over real estate. Maotai’s role as a status symbol in Chinese society also increased demand, further driving its stock price growth. Overall, these predictions provide valuable guidance for investors seeking to understand market shifts in the alcohol industry and underscore the relevance of macroeconomic indicators in stock performance analysis.
The Impact of IFRS S1 on Corporate ESG Disclosure: A Comparative Analysis of SMIC and MTR Corporation
Authors: Li Zhehan
Published: December 2024

Environmental, social, and governance (ESG) issues are becoming increasingly important in corporate investment and financing as the global economy and society evolve. This study focuses on the impact of the IFRS S1 standard issued by the International Sustainability Standards Board (ISSB) in 2023 on corporate disclosure and the standard’s role in improving corporate information’s comparability. By comparing the 2022 and 2023 ESG reports of Semiconductor Manufacturing International and MTR Corporation, this study finds that implementing IFRS S1 promotes a more comprehensive integration of sustainability information in corporate financial reporting. The study notes that the harmonization of international standards, such as the concept of dual materiality proposed by ISSB and the United Nations’ Sustainable Development Goals (SDGs), is influencing ESG disclosure practices globally. The difference in focus between the two companies in ESG reporting reflects their different strategies to address the ESG risks and opportunities. The introduction of the IFRS S1 standard will promote standardization of corporate disclosure, optimize the investor decision-making process, and contribute to the achievement of the broader SDGs.
Study of Random Walk: Basic Theory and Multiple Application
Authors: Yu Boyang
Published: December 2024

Random walk is a randomly walk process that describes the path including a succession of random steps in the mathematical region. A procedure for estimating the likely position of a point exposed to random motions in probability theory, given the probabilities (which remain constant at each step) of traveling a certain distance in a certain direction. A Markov process that exhibits future behavior independent of prior history is the random walk. This paper will discover the classic recurrence Theorem concerning random walks on the d-dimensional integer lattice, and demonstrate the leads to complete generality with simple methods supported by String’s Approximation. Furthermore, this essay will explore the situation that walker randomly walks in different dimensions and discover that random walk on dimensions one and two will return to the initial point, dimension three and higher dimensions will not. The meaning of this essay is to help more people have some basic understanding with random walk and to know there are some applications of random walk.
Challenges and Opportunities of Sichuan Opera Face Changing in Haidilao in Cultural Communication
Authors: Cai Diya , Hong Fanting , Yang Jingfei
Published: December 2024

As companies integrate intangible cultural heritage into brand promotion, Sichuan opera is face-changing and representative of traditional Sichuan culture, and it is widely used in commercial marketing. However, balancing cultural heritage and commercial promotion has become an important issue. This study explores the communication effect of Haidilao’s integration of Sichuan opera face-changing, a regional traditional culture of Sichuan, into brand promotion and analyses the advantages and shortcomings. Through quantitative and qualitative research, this paper conducts a questionnaire survey of the nationwide audience and structured interviews on consumers’ satisfaction levels and positive and negative attitudes in different regions. It is found that Haidilao has enhanced its brand’s competitive advantage and promoted the dissemination of intangible cultural heritage through Sichuan Opera Face Changing. Still, the depth of dissemination needs to be improved due to the over-simplification and entertainment of the culture in a commercial environment, resulting in the sacrifice of cultural values. In addition, the promotion of Sichuan Opera Face Changing in different regions shows a lack of cultural adaptability, especially in areas with significant differences in cultural backgrounds, where the audience’s acceptance of this cultural form is low. In this regard, this paper proposes a regionalized traditional culture promotion strategy and a model of brand-culture symbiosis. This study provides new ideas for effectively disseminating traditional culture in national commercial promotion.
The application of conductive hydrogels for self-powered wearable devices: medical field
Authors: Zhang Yaocheng
Published: December 2024

Wearable devices are playing an important role in many fields, especially in the medical field, where they are responsible for the detection of vital signals, the quantification of health indicators, and the prevention of diseases. Nowadays, the demand for flexible wearable devices is increasing, and conductive hydrogels (CHs), as an important flexible material, have attracted a lot of attention from researchers because of their excellent properties such as flexibility and bio-adaptability. This paper introduces applications and recent advances of CHs in self-powered devices in the medical field, and divide into two aspects, according to their functions. CHs show excellent potential for applications, especially in human signal detection and biofluid analysis. The versatility of CHs makes them indispensable in the medical field, especially in precision medicine and personalised therapies. Finally, it also discusses the difficulties and challenges still faced by CHs in the integration of wearable devices, as well as the outlook for their future applications and development.
Analysing Problems of Chinese Pension Market and Proposing Solutions through Government Initiatives and Private Sector Strategies
Authors: LI Zhenglin
Published: December 2024

This study aims to analyse the problems of the Chinese pension market and test whether the current solutions are effective. It combines two ideas of pension reform: privatisation and Richard Thaler’s “Save More Tomorrow” (SMT). A questionnaire was distributed to 577 interviewees to test whether these policies could work for them. The results are analysed using the Z-test and ANOVA test to examine the hypotheses. The results show that privatisation will fail at solving the pension crisis because people are insufficiently informed about the conditions in the pension market. Furthermore, they are more willing to invest to other areas other than private pensions. On the other hand, SMT will be effective as the money illusion makes people ignore the increase in pension rate when their wages increase at the same time. It provides a better policy for the Chinese government to solve the pension crisis. Furthermore, it also shows that the non-neoclassical paradigm can be effectively applied to policymaking.
Unraveling the Complex Dynamics of Dark Matter and Dark Energy
Authors: Yan Haofang
Published: December 2024

mwymwAbstract:This study examines the dynamics of recent findings related to dark matter and dark energy, beginning with an overview of the theoretical concepts. It assesses various potential dark matter entities such as sterile neutrinos and primordial black holes, alongside a hypothesized exotic variant of hydrogen atoms. Different cosmic simulations are explored; THESAN simulations demonstrate the critical role of dark matter in galaxy formation conditions and galaxy stellar masses, while EAGLE simulations show that Maxwellian distributions are still effective for analyzing dark matter dynamics. The concept of dark energy in cosmic acceleration is discussed through the equation of state parameter. Observations from instruments like WMAP and studies of supernovae are explored; findings suggest that phi cold dark matter model (ϕCDM) aligns more closely to current observations compare to traditional lambda cold dark matter model (ΛCDM). Furthermore, the exploration of early dark energy as a potential approach to mitigate the Hubble tension is highlighted, proposing it as a vital factor in reconciling observed discrepancies in cosmic expansion rates.
Feasibility of Lecithin: Cholesterol Acyltransferase as the Therapeutic Target of Atherosclerosis
Authors: Wu Jihang
Published: December 2024

Atherosclerosis is a global concern in this century. It is a progressive disease caused by the accumulation of cholesterol plaque, which thickens and hardens the arterial walls. It was found that low-density lipoprotein is the major leading factor because it delivers cholesterol towards the arterial walls. By contrast, high-density lipoprotein has anti-atherogenic properties due to its ability to remove cholesterol for hepatic excretion. Lecithin: cholesterol acyltransferase is an endogenous enzyme that boosts high-density lipoprotein-mediated reverse cholesterol transport. It has thereby been studied as a therapeutic target of atherosclerosis for decades. Currently, different lecithin: cholesterol acyltransferase-based therapies have different progress under development. This review illustrated the structural, biochemical, and functional properties of this enzyme. The basic rationale for two main types of this enzyme-based therapy, enzyme replacement and gene therapy, was also explained. Enzyme replacement involves artificial recombinant human lecithin: cholesterol acyltransferase. Gene therapy utilises adeno-associated viral vectors to allow enzyme expression in vivo. In addition, the advantages and limitations of each treatment were also evaluated by summarising clinical and pre-clinical data. Although whether reverse cholesterol transport is the route by which lecithin: cholesterol acyltransferase achieves its anti-atherogenic effects is not clear yet, and the variety of safety issues of the techniques, this enzyme is still a promising therapeutic target for further pre-clinical and clinical efforts.
Risk Factors of Non-Alcoholic Fatty Liver Disease
Authors: Shen Yiyang
Published: December 2024

An increasing number of people worldwide are suffering from non-alcoholic fatty liver disease (NAFLD), a condition characterized by fat buildup in the liver. Numerous categories can be used to group the risk factors for non-alcoholic fatty liver disease (NAFLD), including metabolic, genetic, epigenetic, demographic, and environmental factors. First, metabolic variables—obesity and insulin resistance in particular—are among the main risk factors for non-alcoholic fatty liver disease (NAFLD). The accumulation of fat in the liver is largely caused by obesity, and the disruption of normal fat metabolism caused by insulin resistance adds to the burden on the liver. Furthermore, there is a strong correlation between the onset of NAFLD and the existence of metabolic syndrome. Second, how susceptible a person is to NAFLD depends largely on hereditary factors. The start of the disease is also significantly influenced by epigenetic variables. Age, gender, and other demographic traits are linked to an increased risk of developing nonalcoholic fatty liver disease (NAFLD). In addition, smoking, leading a poor lifestyle, and being around pollutants can all increase the risk of developing the condition. In order to lower the incidence of NAFLD, effective prevention and intervention methods will be devised with the help of a thorough analysis of the interactions among these factors.
Integration of Loudspeaker Technology in Wearable Devices: Applications, Challenges, and Future Directions
Authors: Sun Qitai
Published: December 2024

This paper primarily focuses on the audio technology utilized in wearable devices. It conducts a comprehensive and detailed review of the evolutionary trajectory of audio technology, which not only encompasses the application of speakers but also the various challenges encountered in the design process. Additionally, it delves deep into the theoretical underpinnings of micro speaker physics, integration, and low power audio technology. Furthermore, meticulous tests and evaluations are carried out on both wearable device speakers and bone conduction speakers. The outcomes clearly reveal certain limitations present in the current speakers. Consequently, the conclusion drawn is that future wearable device speakers urgently necessitate technological innovation to significantly enhance sound quality, optimize power consumption, improve durability, and elevate the overall user experience. Future research directions encompass the exploration of advanced audio processing algorithms and low-power strategies, as well as the undertaking of extensive and in-depth user research to gain deeper and more valuable insights.
Prediction of Diabetes Based on Machine Learning Algorithm
Authors: Zhou Zijian
Published: December 2024

Diabetes is a well-known chronic disease that includes a range of metabolic disorders characterized by persistently elevated blood sugar levels over an extended period of time. Early and precise prediction of diabetes is essential to reduce risk factors and minimize potential complications associated with the disease. However, there are significant challenges in creating reliable predictive models due to factors such as limited labeling data, the presence of outliers, and the absence of information in diabetes-related datasets. To address these barriers, this paper proposes a comprehensive framework aimed at improving diabetes prediction through data preprocessing and machine learning techniques. The framework combines methods for dealing with missing values, data standardization, and feature visualization to extract meaningful insights. In addition, various machine learning classifiers - including support vector machine (SVM), decision tree, logistic regression, and naive Baye - are implemented to improve prediction accuracy and support early diagnosis of diabetes. Among these models, SVM shows better comprehensive performance.
A Sentiment Analysis of User’s Comments on Higher Education Topics on Social Media
Authors: Zhou Zhuoyi
Published: December 2024

In a digital era where social media platforms have grown to be significant forums for public discourse, it is crucial to comprehend and capitalize on the tone of remarks made about the various fields including education. This paper utilizes the sentiment analysis technique to delve deeper into the diverse opinions and feelings that people have expressed regarding higher education and its subtopics such as graduate employment, educational policies, institution qualities, and the general landscape, aiming to provide insightful recommendations to help educational institutions enhance their services. Based on the comments under 20 trending higher education-related tweets scraped and analyzed by Python on Sina Weibo, the study indicates a predominance of positive sentiments among the overall opinions toward higher education, alongside negative and neutral sentiments. Potential explanations for the varying sentiments towards the subtopics and the role of social media in shaping public opinions are also identified through detailed observations. This study demonstrates, for the first time, how sentiment analysis can be applied to higher education research, shedding light on the complex interplay between communication and education.
Effectiveness of Probiotics Supplementation in Improving Health Conditions of Athlete Groups
Authors: Peng Ziyun
Published: December 2024

The gut microbiota, comprising bacteria, fungi, archaea, and viruses, plays a critical role in regulating various physiological functions in healthy adults. In athletes, strenuous physical exercise can lead to gut dysbiosis due to oxidative stress, immune suppression, and metabolic imbalance. This paper describes the effects of immunosuppression, oxidative stress and energy metabolism induced by high intensity exercise and training on the health of athlete populations. The gut microbiota is suggested to be associated with these responses. The role of probiotics in improving the gut microbiota is being recognised. Specific details of the improvement of overall health and maintenance of the stabilised gastrointestinal microbiota in athlete population through the influence of probiotic interventions on immune responses, oxidative stress and energy metabolism aspects are discussed in this paper. The positive effects of probiotic interventions in improving the health of athletic populations are suggested, but future research will be needed to determine the specific effects on sports performance.
Prediction of AAPL Closing Price based on ARIMA-LSTM Hybrid Model
Authors: Li Changlin
Published: December 2024

In the context of highly volatile financial markets, accurately predicting stock prices remains an important and difficult task, particularly for major technology firms such as Apple Inc. (AAPL). Forecasting methods that are more traditional, like the Autoregressive Integrated Moving Average (ARIMA) model, perform well in linear analysis but have trouble handling the non-linear patterns that are common in financial information. In order to handle both linear and non-linear dynamics, this study presents a novel hybrid model that combines ARIMA with Long Short-Term Memory (LSTM) networks. This model efficiently leverages the advantages of both approaches. Utilizing historical closing price data for AAPL obtained from Yahoo Finance, the study demonstrates that the ARIMA-LSTM model significantly enhances predictive accuracy and adapts proficiently to the complexities inherent in stock market fluctuations. As seen by the data, the model’s predictive ability has significantly improved, accounting for 91.1% of the fluctuation in stock prices. In addition to providing a more trustworthy prediction framework, this hybrid approach offers analysts and investors helpful information to assist them negotiate the turbulent nature of financial markets.
The Communication Situation of Japanese Anime “Anohana: The Flower We Saw That Day” on Xiaohongshu Platform
Authors: Shi Luofei
Published: December 2024

The promotion of anime works is increasingly widespread globally. However, the communication mode and influence have not been thoroughly investigated. The existing literature mainly focuses on content analysis, audience research and communication effect evaluation, but the in-depth discussion on platform characteristics is insufficient. This research analyzes the communication situation of “Anohana: The Flower We Saw That Day” on Xiaohongshu platform through questionnaire surveys and interviews. The study reveals that the communication of this work on Xiaohongshu has the characteristics of globalization, localization, indigenization and regionalization, and the proportion of female users is relatively high. Users mainly encounter related content through short videos and graphic and text notes and show a strong interest in high-quality emotional resonance content. However, there is also the problem of uneven content quality. It is suggested that the platform enhance the communication effect and user experience by encouraging the creation of high-quality content, strengthening community management and cross-platform promotion.
The systematic analysis of present situation and future development of semiconductor
Authors: Wang Chenyue
Published: December 2024

Semiconductor has a property between conductor and insulator. The property is caused by the different structure of the p-type and n-type material in the semiconductor, which only allows the current to travel in one direction. Because of this special property, semiconductor is used to design many different devices. Solar panel is an important technology to reduce pollution to the environment, with the energy generated by sunlight, the demand to fossil fuels will decrease. Therefore, global warming and air pollution will be solved by this solar panel technology. Wafer is also an important technology. It is widely used in computer and smart phones to processing complex information, many communications technology have a large demand on wafer. LED is a lighting device; its color and brightness is depended on the structure and material of semiconductor. There are many challenges and limitations in recent semiconductor industry, including its low efficiency in different scenario and high cost in production. In future, the need to semiconductor will increase a lot, like the 5G station and electric cars. The limitations of semiconductor are very important to solve by design new structure and new materials. Semiconductor will largely change the development in future technology.