bluuebunny/crossref_metadata_2025 huggingface dataset:
Penanggulangan Kleptomania Melalui Pendekatan Terapi Perilaku Kognitif Dalam Perspektif Al-Qur’an
Authors: Muhamad Barqun Syafei  , Ahmad Thib Raya  , Muhammad Suaib Tahir
Published: August 2024

Abstrak 
Penelitian ini menyimpulkan bahwa penanggulangan kleptomania dapat dilakukan dengan tahapan pendekatan terapi perilaku kognitif perspektif Al-Qur’an, yaitu : 1). Tindakan promotif berupa menjaga kesehatan fisik,  mental dan spiritual serta penguatan iman dan implementasinya. 2). Tindakan preventif (pencegahan) yaitu harmonisasi keluarga,  kondusifitas lingkungan masyarakat, dan pemahaman terhadap hak milik orang lain. 3). Tindakan kuratif (penyembuhan) dengan terapi perilaku kognitif perspektif Al-Qur’an yaitu identifikasi masalah, evaluasi sikap dan belief (keyakinan), implementasi ajaran agama Islam, peningkatan kontrol diri dan perencanaan alternatif, pengembangan pikiran positif, relaksasi, regulasi diri dan pengukuhan diri. 4). Tindakan Rehabilitasi dengan perlindungan dan pendampingan keluarga, menghindarkan dari lingkungan yang buruk serta menciptakan lingkungan yang kondusif. Dalam penelitian ini, penulis menggunakan metode kualitatif dengan mengumpulkan data mencakup ayat-ayat Al-Qur’an, hadis nabi, tafsir Al-Qur’an, hasil penelitian, jurnal, artikel, dan konferensi atau seminar. Sedangkan untuk menganalisa masalah ini penulis menggunakan metode tafsir tematik (maudhu’i).
Research on Diffraction Patterns of Smartphone Screens
Authors: Qiu Tianqi
Published: August 2024

Smartphone screen is composed of pixels which are not of uniform size and arranged evenly. When illuminated by a laser, the reflected beam diffracts, producing a diffraction pattern with structure of mesh shape that exhibits characteristics similar to a two-dimensional reflection grating.In this paper, the general diffraction formula of a two-dimensional non-uniform grating is derived, while a simplified form in a special case is explored. The influence of laser incidence angle on the diffraction pattern is analyzed. The diffraction patterns by formula calculation and Fourier transform are obtained using MATLAB simulation. The rationality of the derived formula is verified through simulation and experiments. Also, the pixel density of the smartphone screen is calculated based on the diffraction pattern obtained from the experiment. The application scenarios of the research results are proposed.Comparing the discrepancy in diffraction patterns of different types of screens whose arrangements of sub pixels in smartphones are also different, the mechanism of grating diffraction is displayed directly. Theoretical calculations, simulations and experiments are applied for comparing and confirming each other.
Uniform Convergence of Fourier Series for Hölder Continuous Functions and Functions of Bounded Variation
Authors: Wang Weiqiao
Published: August 2024

This article discusses two significant results about the uniform convergence of Fourier series. One is the uniform convergence of the Fourier series for Hölder-α(α>0) continuous functions, while the other is the uniform convergence of the Fourier series for functions that can be expressed as the sum of finitely many continuous monotonic functions. The two results are particularly useful. Because Hölder continuity condition ensures a specific regularity that facilitates the analysis and provides a robust framework for proving uniform convergence and many practical functions can be decomposed into monotonic components, making the theorem broadly applicable. By providing detailed proofs and applications, this study demonstrates the significant implications of uniform convergence in both theoretical and practical contexts. Moreover, this work paves the way for future research in higher-dimensional Fourier analysis, non-periodic functions, and adaptive Fourier techniques, underscoring the ongoing relevance and versatility of Fourier series in modern mathematics. Several well-known results emerge as corollaries of these findings, highlighting the robustness and applicability of these theorems in Fourier analysis.
Comparison of the differences in photochemical degradation of dissolved organic matter in rivers, lakes, and ponds by adding nanoparticles TiO2.
Authors: Li Xinyan
Published: August 2024

This study examines the photolysis of Dissolved Organic Matter (DOM) in urban rivers, lakes, and ponds using photocatalysis experiments. Employing a photochemical reactor and UV spectrophotometer, we investigated the precise effects of TiO2 nanoparticles and illumination duration on the degradation efficiency, rate, and kinetics in water bodies. Simultaneously, an analysis was conducted on the photochemical degradation process of DOM from various sources. The results demonstrate that the photocatalyst TiO2 can effectively improve DOM degradation and light absorption degradation efficiency, with longer illumination durations inversely correlating with DOM content. Both Dissolved Organic Carbon (DOC) and 254 nm absorbance degradation kinetics follow pseudo-first-order degradation kinetics. Notably, the pond exhibited the most significant change in degradation efficiency, reaching 96.7%. Our findings suggest that degradation efficiency in water bodies may be influenced by surrounding vegetation, population density, and rainfall conditions. This study contributes to a deeper understanding of DOM degradation processes by photocatalysts and provides a feasible method to effectively mitigate water pollution.
Analyzing the Marketing Strategy of Manchester United: A Study of Success in the Premier League
Authors: Huang ChiFai
Published: August 2024

For the past several decades, Manchester United has been deemed the most successful soccer club in the world either in their achievements or marketing. However, starting from this decade, the ranking and achievements of Manchester United have dropped into the trough, but, still, their marketing strategy is strong, and they gained a lot of commercial lubricants. This study is going to analyze the success of Manchester United’s Marketing Strategy. Especially focusing on the brand sponsors and variations, also analyzing the arena services of the team. By combining the analysis of these aspects, we could clearly identify the expedient scheme of Manchester United’s Marketing strategy whether to orientate on their potential customers or attract the potential customers. Moreover, this paper also gives a thorough analysis of the current dilemma by identifying the problem current grade of the team and providing the potential comparison strategy with other teams. On account of the current ranking of Manchester United in the Premier League does not satiate the fans, they have not won the great champions for several years, and the fandom outflow and the decreasing value of the branding is a severe problem that needs to be solved by Manchester United. Utilizing the comparison with another team could comprehensively provide a satisfactory solution to deal with the current dilemma of the team record and strengthen their marketing strategy.
Research on the Influence Factors of Heart Disease
Authors: Guo Feng
Published: August 2024

Heart disease accounts for almost 30% of all deaths worldwide and about 18 million deaths each year, making it the primary cause of death and disability worldwide. Recent research highlights variations in incidence rates and causative factors among different populations and regions, underscoring the need for detailed studies to develop effective prevention and treatment strategies. This article explores the various factors that influence heart disease. Although many studies have been done to show that the incidence of heart disease is related to dietary habits, genes, and other factors, there are still many details that should be investigated. This paper focuses on determining which factors have effects on the incidence of heart disease, such as age, gender, and some diseases. Binary logistic regression is used to statistically analyse the data and found that certain factors, such as gender, chest pain, thallium stress, exercise-induced ST depression and major fluoroscopy vessels were associated with the development of heart disease. The use of binary logistic regression modelling enabled the study to quantify the impact of these factors and provided a useful tool for predicting heart disease risk. The study’s findings serve as a valuable resource for the formulation of heart disease prevention and treatment plans.
An Analysis of the Time Travel Device for Exploring Black-White Race Relations in Octavia E. Butler’s Kindred
Authors: Wang Qian
Published: August 2024

The thesis focuses on Octavia E. Butler’s novel Kindred and employs close reading and textual analysis to explore the depiction of black-white race relations through the time travel device. It points out that Butler cleverly uses the method of temporal rescue to break the “grandmother paradox.” The dual-time setting allows Dana, while saving her white ancestors, to witness the harsh realities faced by her African American ancestors in American history. On this basis, the thesis reveals and critiques the historical roots of racial issues, highlighting the physiological and psychological experiences of racial injustice endured by African Americans, as well as the persistence and improvement of the legacy of slavery. It emphasizes the importance of African Americans confronting history to break the cycle of oppression and shape a more equitable future.
Application of Machine Learning in the field of Heart Disease Prediction and its Accuracy Study
Authors: Gao Qiantong
Published: August 2024

The application of machine learning in the healthcare sector is a prominent area of research presently. Among these, there is significant potential in employing machine learning for predicting and treating heart disease. Hence, this study aims to explore the accuracy and application of machine learning models in predictive diagnosis and treatment of heart disease. This paper first presents commonly used machine learning algorithms within relevant fields, followed by gathering data and instances showcasing the use of machine learning in predicting and treating heart disease. Through data analysis, this study summarizes current cutting-edge development directions, trends, as well as the integration of machine learning algorithms into real medical processes. Finally, it concludes by summarizing the existing prospects and challenges faced by machine learning in predicting and treating heart disease. This paper can serve as a valuable source of inspiration and reference for researchers involved in related fields concerning heart disease prediction and treatment.
Research on the Development of Small and Medium-Sized Housing Enterprises Under the Downward Trend of Real Estate Industry
Authors: Bu Hengjia
Published: August 2024

The real estate industry in China, once a key driver of economic growth, now faces significant challenges following the implementation of the “Three Red Lines” policy in 2021. This policy, aimed at controlling the debt levels of real estate companies, has particularly impacted small and medium-sized enterprises (SMEs), exacerbating their pre-existing issues such as limited financing channels, poor internal governance, and low corporate credibility. SMEs are now compelled to navigate a market downturn while meeting stringent regulatory requirements, making their survival and growth increasingly difficult. This study investigates the strategies that SMEs in the real estate sector can adopt to thrive under these conditions. It explores potential avenues such as entering less saturated markets, innovating business models, and leveraging local opportunities. The research underscores the importance of policy compliance, improving internal management, and strategic innovation. By adopting these strategies, SMEs can enhance their resilience and adaptability, contributing to the sustainable development of China’s real estate market. The findings offer valuable insights for policymakers and industry stakeholders aiming to support the sector’s stability and growth.
A Study of Premodern Folk Women’s Narrative Literature in Female Script
Authors: Gong Qinmengtai , Jin Xiukun
Published: August 2024

Folk women’s literature has always been a field of little research in the literary academic community. Due to the lack of seriousness in its texts, difficulty in collecting, and insufficient representative texts, many literatures analyse these texts from cultural and social perspectives. However, this article aims to explore the literary value behind these texts and prove that folk women can also achieve self-empowerment through literary creation.
Music support for gender equality campaigns
Authors: Wang Jiayi
Published: August 2024

Can music be a force for gender equality? With the development of time, people’s attention to gender equality has gradually increased, and many efforts have been made to change the various kinds of discrimination that have existed for a long time. What role does music play in these efforts? This thesis explores the role of music in promoting gender equality, gives examples of musicians and musical works that have had a significant impact on gender equality, and analyses how these examples have challenged and changed gender stereotypes. Through case studies and literature analysis, the paper also explores the role of music education in fostering gender equality awareness, analysing in-depth the various parts of the music industry from a number of perspectives, including creation, performance, advocacy and education. It is found that music not only reflects social change, but also positively contributes to the process of gender equality. These findings are intended to inform future research and practice and to promote the further development of the potential of music as a tool for social change.
The Influence of Gender Diversity Management Policies on Employee Work Perceptions: Critical Analysis of “Gender Diversity Greenwashing” at Goldman Sachs
Authors: Zhang Jiashen
Published: August 2024

This study explores the impact of gender diversity management policies on employees’ work perceptions and critically examines the phenomenon of “gender diversity greenwashing.” In recent years, gender diversity has become a critical focus for many organizations, aiming to enhance morale of workers, decision-making quality, and corporate competitiveness in a globalized market. Using Goldman Sachs as a case study, this research employs a literature review and secondary data analysis to assess the effectiveness of these policies. The findings indicate that while gender diversity policies can enhance job satisfaction and career development, some companies engage in superficial practices that fail to bring substantial changes. This phenomenon, termed “gender diversity greenwashing,” negatively impacts employee perceptions and trust. By analyzing Goldman Sachs’ initiatives and the associated criticisms, the study underscores the need for genuine and effective gender diversity policies. Recommendations are provided to improve these policies, ensuring they contribute meaningfully to both employee well-being and organizational performance.
A Study on the Construction of Brand Storytelling and the Emotional Connection of Generation Z
Authors: Feng Xinye , Wang Pinjia , Wang Suiyue , Zhang Kemeng
Published: August 2024

This study explores the characteristics and effects of Chow Tai Fook’s (CTF) brand storytelling, as well as the current situation and trend of Generation Z’s (Gen Z) emotional connection to the brand. The results show that CTF’s brand storytelling is unique and able to attract the attention of Gen Z. Gen Z has high awareness and emotional connection to CTF, and most of them highly recognize the importance of the background of the brand story. In terms of willingness to buy, a significant proportion of respondents believe that brand storytelling is one of the reasons why they buy jewelry and precious metal products, and that brand storytelling and creation are more appealing to consumers than simple sales pitches. Emotional resonance, uniqueness, quality assurance and social responsibility, and lifestyle leadership were all seen as important factors in terms of brand cultural characteristics. As for story construction, compelling plot construction and authentic and believable content presentation are the most significant attractions for Gen Z consumers, while all other aspects have significant impacts as well.
An Examination of Wireless Charging Technologies for Electric Vehicles Powered by New Energy
Authors: Li Jiashu
Published: August 2024

In recent years, the increasing prevalence of new energy electric vehicles in the automotive industry has led to a yearly growth in the number of electric vehicles. This trend highlights the increasing importance of wireless charging technology. This paper centers on the advancements in wireless charging technology for new energy-efficient vehicles. It assesses the current state of the technology, both domestically and internationally, and delves extensively into the operational principles of the pivotal wireless charging technology. The findings indicate that wireless charging, as a novel charging approach for electric vehicles, possesses considerable potential and warrants additional research and implementation. The objective of this paper is to provide a significant point of reference for the advancement of wireless charging technology.
Analyzing the Short-term and Long-term Effects of Mergers and Acquisitions on Stock Prices: A Comprehensive Study of Acquiring and Target Companies
Authors: Jiang Yutong , Deng Xiwen , Lu Haoxuan , Chai Yiwen , Ji Manshu
Published: August 2024

In this study, Microsoft’s acquisition of linkedin on June 13, 2016 is taken as the research object, focusing on the impact of mergers and acquisitions on stock prices. A hybrid approach is adopted, combining quantitative analysis of stock price data and financial performance indicators with qualitative evaluation of strategic results. Preliminary results show that the stock price fluctuated in the short term after the merger event, but then gradually stabilized. This paper emphasizes that this research provides valuable insights for business decision makers, investors and financial analysts. More importantly, this study provides empirical evidence to support the trend that M&A gradually stabilizes after short-term fluctuations in stock prices, and provides a practical basis for understanding the impact of M&A on corporate strategic decision-making. Therefore, this work not only has guiding significance for the decision-making of investors, but also provides an important reference for the formulation of corporate strategy, and helps to improve the decision-making wisdom of decision makers.
Research on the Development of Fashion Brands Under the Trend of Digital Economy: Taking Shein and Zara as Examples
Authors: Huang Yifan
Published: August 2024

With the emergence of the digital economy and the shift in consumer buying patterns, the global fashion industry is undergoing significant changes. This study aims to explore how two fast-fashion brands, Shein and Zara, have leveraged the digital economy trend to create effective and efficient fashion branding strategies and to analyze the differences in their approaches to provide success lessons for other fashion retailers. The study first evaluated the impact of the digital economy on the fashion industry, especially fast fashion, and then used case studies to identify similarities and differences between Shein and Zara and to explore lessons that can be learned by fashion brands that have succeeded in the digital age. The research focused on comparisons of technology, data analytics, and innovative supply chain management, as well as analysis of business models and critical success factors. The study found that Shein and Zara have successfully adapted to the digital economy through different strategies. Shein relied on data-driven product development and a flexible supply chain, while Zara maintained its competitive advantages through a vertically integrated system that responded quickly to market trends. Both emphasized the importance of online marketing and social media in brand promotion. The study also points out that there are negative social and environmental impacts of the fast fashion model despite its commercial success, therefore fashion brands need to find a balance between digitalization and responsible fashion.
The Effect of NBA Attendance on Teams’ Performance
Authors: Wang Chenzhao
Published: August 2024

This paper analyzed how attendance in the NBA during the COVID-19 pandemic, specifically, in the 2020-2021 seasons, affected team performance. To answer this question, we used team data of all 30 teams from 2015 to 2022, and attendance data for the 2020-2021 season; we separated team attendance into three levels: Full (or almost full), Partial, and Empty. We used logistic models and the Bradley-Terry Model to analyze each team’s strength coefficient (compared to one baseline team) using the Win/Loss data as the determining factor. Our result showed a slight advantage for home teams when audiences were present. However, results revealed that home court advantage became less evident when there was partial or no audiences.
Parametric Design Method of Buildings Based on Convolutional and Deep Neural Networks
Authors: Huang Ke
Published: August 2024

The application of AI technology in architectural software has brought various innovations and changes to the industry. By introducing convolutional neural networks and deep neural networks, architectural design software is expected to automatically identify and generate complex architectural images, optimize the design process, and provide intelligent design assistance. Through literature research, this paper aims to discuss the specific application of CNN and DNN in parametric design and the innovation brought by them, and analyzes the application of these technologies in architectural image recognition, generation, design optimization and other aspects. This paper aims to provide a comprehensive reference for researchers in related fields and promote the innovative application of AI technology in architectural design. The application of AI technology in architectural software has brought numerous innovations and changes to the industry. By introducing convolutional neural networks and deep neural networks, architectural design software is expected to automatically identify and generate complex architectural images, optimize the design process, and provide intelligent design assistance. Through literature research, this paper aims to discuss the specific application of CNN and DNN in parametric design and the innovation brought by them; it also analyzes the application of these technologies in architectural image recognition, generation, design optimization, and other aspects. This paper aims to provide a comprehensive reference for researchers in related fields and promote the innovative application of AI technology in architectural design.
An analysis of the viability of the Buffet restaurants’ model using SWOT analysis
Authors: Zhu Xiaomin
Published: August 2024

The topic of the viability of buffet restaurants remains under-researched. This study summarised the history of buffets and provided key insights into buffets by analysing their viability using the SWOT model (Strengths, Weaknesses, Opportunities and Threats). Additional suggestions for the future development of buffets were also proposed. A survey of 378 respondents about public opinions on buffets, two interviews with restaurant managers, and secondary research were used as the main research methods. The results suggest that buffet restaurants can remain viable in the future by capitalising on their strengths such as “a Good cost-quality ratio (value) for customers”, “Suitable for catering to a group of people” and “Reducing the labour cost for buffet restaurants”; Minimising and avoid their weaknesses such as “Dishes are extensive but not refined”, “Overeating and Food waste phenomenon” and “The dining environment could be too noisy and informal, and lack of “ceremonious feeling”; Catching up opportunities such as “Creating a scenario-based dining experience”, “Specialising buffet restaurants to a small category” and “Exploring the “set menu” mode buffet”; and find solutions to alleviate the effects of threats such as “Evolving public opinion and policies that are unfavourable for buffets” and “Increasingly fierce competition in China’s catering market”. Overall, as the economy recovers and pro-consumption policies are implemented post-COVID-19, the catering market is experiencing a rapid rebound, which could also benefit the buffet restaurant market.
Research on the Application of Machine Learning in Cancer Prediction and Diagnosis
Authors: Wang Chenyu
Published: August 2024

Due to the continuous development and advancement of artificial intelligence technology, the application of machine learning in the medical field, particularly in cancer treatment and prediction, is becoming increasingly widespread and profound. By utilizing machine learning algorithms, healthcare professionals can analyze large volumes of medical data more accurately through specific models. This paper discusses the application of machine learning in cancer diagnosis and treatment, with special attention to prediction, diagnosis and treatment. By analyzing a large number of clinical and genomic data, machine learning, which provides support for early diagnosis, reveals the complex pattern of cancer development. Deep learning technology can help doctors diagnose and predict cancer more accurately in medical image analysis and genome data analysis. Ensemble learning methods such as the random forest model improve the accuracy of prediction. It also introduces semi supervised learning, which provides a new perspective for cancer prediction: enhancing model training by using unlabeled data. The paper also introduces the application of cox-net and survival support vector machine in survival analysis.
The Application of Transfer-Appropriate Processing for Enhancing Reading Comprehension of Chinese High Schoolers
Authors: Sun Shaoying
Published: August 2024

Improving reading comprehension via proper reading skills is crucial to English learning. Nevertheless, the dearth of educators on reading strategies and other factors poses a challenge to the long-range development of high school students’ ability of reading comprehension. Transfer-appropriate processing (TAP) is highly consistent with advancing high schoolers’ comprehensive application of English, but its introduction into practice has been an under-investigated domain. In light of this, the present study offers some TAP-based pedagogical recommendations for learning and teaching to facilitate reading comprehension. It is broken down into vocabulary memorization and text understanding. TAP states that three factors--the level of processing and the uniformity of activities and situations during memory encoding and retrieval--will modify memory performance. Generating questions involving intensive contemplation boosts the grasp of reading resources; employing initial tests (retrieval practice) and engaging in congruent physical activities during encoding and retrieval aid in nurturing enduring vocabulary retention. Educators and learners may integrate the aforementioned strategies into practice.
Research on the Impact of the Advancement of Emerging Technology on the Economy
Authors: Zhang Wei
Published: August 2024

The advancement of emerging technology has become an important engine to promote economic progress in our time. This paper aims to explore how modern technology shapes and influences the new pattern of economic development. Through an in-depth analysis of cross-border trade cooperation, changing the employment structure, and changing the issuance and circulation of money, this paper reveals the positive role of these technologies in improving production efficiency, optimizing resource allocation, and promoting innovation-driven development. At the same time, it also pays attention to the challenges brought about by the development of science and technology, such as unemployment caused by the changing employment structure and the widening of the digital divide, and puts forward corresponding suggestions. The results show that the rational use of modern technology can not only accelerate economic growth but also promote the overall progress of society. Therefore, modern science and technology should be actively developed to achieve sustainable development.
UAV forest fire early warning and inspection plan based on multiple nests
Authors: Wu Haotian
Published: August 2024

Forest fires are sudden and destructive, and it is difficult to deal with and extinguish them after they occur. Therefore, effective forest fire prevention measures are very important to protect forests. The development of drone technology in recent years, especially the emergence of drone nests(airports), has given a new idea of forest fire early warning. This article proposes a UAV forest fire early warning inspection plan based on a multi-UAV automatic nest. Three sets of UAV nest equipment are used to cover a specific range and inspect. The main purpose is to ensure that the target area is inspected. While covering inspections, it also improves the efficiency of drone inspections and the utilization rate of the nest, for reference.
Determining the Disengagement of Accomplices in Telecom Network Fraud Crimes
Authors: Zhao Yuqi , Zhao Jing , Fan Ying , Huang Xiao
Published: August 2024

The incorporation the accomplice disengagement theory cases of cross-border telecom network fraud crimes is crucial for the objective and comprehensive assessment of the actions of accomplices who opt out of criminal activities midway. Nevertheless, the foundational theory of accomplice disengagement is still incomplete, leading to inconsistencies in the application of laws and disparities between the severity of sentencing and the leniency of conviction decisions in judicial practices. This study investigates this matter from a comparative legal standpoint, juxtaposing the key principles of civil law and common law jurisdictions with the theories on accomplice disengagement within China’s legal framework. Through this examination, the study the current approaches to addressing concerns related to accomplice disengagement. Subsequently, the discourse delves into defining concepts, elucidating principles, outlining fundamental elements, and deliberating on conviction and sentencing, with the objective of refining the processes for determining accomplice disengagement. The ultimate goal is to ensure fairness in disengagement determinations and to devise innovative strategies to crimes related to telecom network fraud.
Research progress on the adsorption of pollutants in water by oxidized graphene
Authors: Liao Hongjuan
Published: August 2024

As a novel nanomaterial, oxidized graphene has attracted attention due to its unique physical properties and abundant oxygen-containing functional groups. This paper analyzes the structure of oxidized graphene, and around its structure and properties, explains the main adsorption mechanisms of oxidized graphene for metal ions and organic matter in water. It discusses and summarizes the main factors that affect the adsorption capacity of oxidized graphene, and looks forward to its application prospects and future research directions in the field of water treatment.
Quantitative Easing and Climate Change: A Case Study
Authors: Zhang Zeyu
Published: August 2024

In the context of increasing global climate change, this article takes an in-depth look at how central banks can use quantitative easing to help address this issue. Based on three research methods: Green Bond, SDGs Bond, Carbon Trading Market and Carbon Reduction Project, this paper analyzes the pros and cons of specific measures of quantitative easing in dealing with climate change. The study found that the above three types of quantitative easing policies can effectively guide funds to green industries, promote green economy and sustainable development, and thus mitigate the economic impact of climate change. This research not only provides a new perspective for central bank policy making, but also provides investors with new opportunities for green investment. This paper suggests that the central bank should increase its support for green projects when formulating quantitative easing policies, and encourage investors to actively participate in green investment to jointly promote the response to climate change.
Exploration of the Reasons for the Federal Reserve’s Interest Rate Hike in 2022 and Evaluation of Policy Effectiveness
Authors: Wang Mengqi
Published: August 2024

After the global economy experienced the impact of the new crown epidemic, the US economy recovered in 2022, but inflation rose rapidly, prompting the Federal Reserve (FED) to take interest rate hikes. This paper analyzes the background and reasons for the Fed’s interest rate hike in 2022, and evaluates its policy effect, aiming to provide experience and lessons for future monetary policymaking. The main findings include: that the interest rate hike significantly reduced the inflation rate in the United States, from 8.0% in the first quarter to 5.67% in the fourth quarter; In the short term, interest rate hikes will hinder the economy, but in the long term, they will help promote stable growth; The interest rate hike led to stock market fluctuations and bond market yields rising, the credit market tightening, and increased the instability of the global financial market; Urge other countries to adjust their monetary policies and increase global economic uncertainty. The significance of this paper is to expand the theory of international financial and monetary policy and provide comparative research value for the policy-making of emerging market countries and developing countries. The policy recommendations include: the United States should strengthen policy transparency and financial supervision to promote the optimization of economic structure; Other countries should strengthen macro policy coordination, improve financial regulatory capacity, achieve economic diversification, maintain monetary policy flexibility, and promote the healthy development of cross-border capital flows.
Stock Selection Analysis of Innovative Multifactor Model in New Energy Sector
Authors: Shao Jiaxuan
Published: August 2024

As of 2024, China’s new energy sector has made significant progress, ranking first in the world in terms of installed photovoltaic (PV) and wind power capacity. The proportion of new energy in the energy mix has increased significantly, driving China’s energy transition and sustainable development. Meanwhile, with the rapid development of Internet technology, quantitative investment strategies based on artificial intelligence technology are expected to show great growth potential in the future financial sector. In this context, this paper will construct a multi-factor model with the help of machine learning, combine value analysis and technical analysis, select candidate factors, develop exclusive factors for the characteristics of the new energy industry, test the validity of the factors, construct a multi-factor stock picking strategy and carry out backtesting analysis. The results demonstrate that the strategy can effectively manage risks and achieve excess returns, which is theoretically and practically instructive for the construction of investment portfolios. The results provide an effective investment strategy reference for financial institutions such as banks, brokerage firms and fund companies.
LSTM-Based Forum Topic Classification Model
Authors: Liang Leo
Published: August 2024

With the rapid development of information technology, forums have become an important platform for information exchange. However, the manual classification of forum topics consumes a significant amount of human resources and is prone to classification errors. To address this issue, this study proposes a forum topic classification model based on Long Short-Term Memory (LSTM) networks. By leveraging LSTM’s capability in text processing, the accuracy and efficiency of topic classification are significantly improved. This study used approximately 68,000 entries from 29 topic categories, scraped from Zhihu, for the experiments. Preprocessing steps such as text cleaning, tokenization, and word vectorization were performed, and a classification model with LSTM and Dropout layers was designed. The experimental results indicate that the model performs well in most topic classifications, although overfitting remains an issue for certain categories. The paper concludes by summarizing the advantages and limitations of the model and discusses the potential for improving classification accuracy through increasing data volume and optimizing the model in the future.
Standards of Femininity in Traditional and Contemporary China: Stereotypes and Beliefs on Women’s Appearance, Roles and their Cultural Influences
Authors: Chen Camille
Published: August 2024

Technological advancements have advanced patriarchal society. Modern society is bombarded with media, which introduces new styles and trends daily. These new fashion standards often have negative effects and reinforce social norms and stereotypes. Female roles and fashion trends are stereotyped worldwide, but they are rarely rigid. However, many in Eastern Asia, especially China, are concerned about this issue because cultural and media influences shape many stereotypes and perceptions about women’s physical appearances and social roles. People used to embrace their own beauty standards. However, modern society has adopted a standardised ideal, leading many to undergo extensive plastic surgery procedures like nose bridge enhancement, V-shaped face, skin lightening, and double eyelids. It seems like everyone is identical and can be easily replicated. Without inner beauty and values, outer beauty is just a decorative vase. Beauty, like anything else, is harmful in excess. Self-improvement and personal values should be prioritised before cosmetic enhancement. Through impact of social media, Chinese people set beauty standards and keep them for female generations .
Application of Machine Learning in the Field of Diabetes
Authors: Wei Churong
Published: August 2024

Diabetes, a prevalent chronic disease worldwide, poses significant challenges to healthcare systems, with its cases steadily increasing. Machine learning has emerged as a promising tool in diabetes research, offering opportunities for prediction and diagnosis through analysis of vast clinical datasets. This paper systematically reviews and analyzes the latest research progress in ML applications for diabetes, encompassing risk prediction and clinical diagnosis. Various ML techniques, including neural networks, supervised learning, semi-supervised learning, deep learning, and ensemble learning, are explored in their application to diabetes research. While ML has shown promise in improving diagnostic accuracy and efficiency, several challenges remain, such as data quality, model interpretability, and computational requirements. Recommendations for future research focus on addressing these challenges to further advance ML’s effectiveness in diabetes management. Through this review, we aim to provide valuable insights for researchers and clinicians, promoting the continued development and application of ML technology in diabetes care, improving efficiency and accuracy.
MLB league marketing: MLB in the Chinese market development analysis and future strategy
Authors: Li Ziming
Published: August 2024

Baseball is a “Global sport” with strong viewership ratings and widespread participation in many countries. For a very long-time, Major-League Baseball (MLB) has been a vital component of American sports culture. Baseball is a “Global sport” with strong viewership ratings and widespread participation in many countries. However, the company’s entry into the Chinese market has presented both fresh possibilities and difficulties.  This paper will start with a summary of baseball’s history in China, examine MLB’s initiatives there, and attempt to make sense of the sport’s tactics, meaning, and potential strategic importance. The research employed a hybrid methodology to gather qualitative data from Major League Baseball’s marketing efforts in China, which it then used to explore customer behavior and market trends. The results demonstrate how MLB engages with Chinese consumers in a variety of ways, including digital marketing tactics, grassroots development initiatives, and cultural adaptation.  This research also clarifies the difficulties caused by cultural disparities, legal restrictions, and competition from domestic sports leagues.  In summary, this paper will provide a thorough analysis of the current market conditions and offer some recommendations for MLB’s future growth in China.
Research on the Relationship Between the Cryptocurrency Greed Index and Liquidation Amounts
Authors: Zhang Xiaoxuan
Published: August 2024

Nowadays, the price of cryptocurrencies, especially its representative currency Bitcoin, has risen sharply. However, the high volatility of Bitcoin makes it easy for many contracts to explode in a short period. Meanwhile, the Greed Index is a virtual currency platform launched to measure the emotional state of various cryptocurrency users towards the currency, whether they are greedy or fearful. This paper aims to explore the specific relationship between the amount of Bitcoin’s exposure and the greed index by exploring the linear programming model. Nowadays, many studies and theories have been launched to study the factors that affect cryptocurrencies and to speculate on the price trend of cryptocurrencies. However, what many studies fail to note is that the contract market for cryptocurrencies is also very active, and many cryptocurrency users attempt to use leverage to make high profits, and this behavior is very influenced by emotions. This article finds a relationship between the amount of cryptocurrency Liquidation and the Greed Index. This paper hopes to use the quantitative model to explain the specific trend and influence relationship, and at the same time for investors and market regulators a new way of thinking.
Automated Artist Identification Using Deep Learning and Transfer Learning Techniques
Authors: Xu Ke
Published: August 2024

Traditional methods of art analysis rely heavily on human expertise, which can be subjective and limited by an individual’s familiarity with art history.This paper introduces an innovation of art style recognition using deep learning and transfer learning techniques. We use the pre-trained ResNet50 architecture to identify artists based on their work. The study aims to show how convolutional neural networks (CNNs) can be applied to complex image recognition tasks, such as identifying artists from their paintings. Our model is trained on a large dataset of digitized artworks with astonishing accuracy, demonstrating the effectiveness of transfer learning in dealing with the high variability of artistic styles.
Influence of “Coal-to-Gas” Policy in the Beijing-Tianjin-Hebei Region and Surrounding Area on the Air Quality
Authors: Hu Jiarui
Published: August 2024

In recent years, extreme weather, such as haze, has occurred frequently; air pollution has been aggravated; and the concentration of inhalable particulate matter in the air has been very high in China, especially in Northern China. The problem of atmospheric environment needs to be solved urgently. Meanwhile, the energy problem pertains to the country’s major strategy. Adjusting the energy structure can not only solve the problem of environmental pollution, but also change the energy pattern of our country. Thus, the “Coal-to-Gas” policy has been implemented. This paper examines the influence of the “Coal-to-Gas” policy on the air quality in the Beijing-Tianjin-Hebei Region, which also has important practical significance for further optimization and control of the policy.
Few-shot Learning using Data Augmentation: A Literature Review
Authors: Jiang Guanhong
Published: August 2024

This paper examines few-shot learning, a machine-learning approach that allows models to generalize well with scarce labeled data. It overviews few-shot learning concepts and reviews data augmentation techniques tailored for this scenario. It evaluates these image and object recognition techniques and discusses their benefits and limitations. An experimental setup is described, with selected datasets and metrics to assess the augmentation strategies. Baseline models are analyzed, and the comparative results are presented, identifying key trends and areas for further research in few-shot learning.
Culture-Led Regeneration in the UK——A Case Study on Hull
Authors: Wang Wenzheng
Published: August 2024

Culture-led regeneration is an important development of cultural policy in recent years. This paper takes the city of Hull, which was selected as a British cultural city in 2017, and discusses the strategy and implementation process of cultural regeneration. Analyzes the cultural activities of Hull City, and assess its impact on economic growth, social solidarity, and resident well-being. The study found that cultural regeneration significantly promoted the local economy, enhanced community cohesion, and improved the quality of life of the residents. However, Hull City also faces challenges in resource allocation and long-term sustainability. The conclusions of this paper show that cultural regeneration has reference value for other cities intentionally implementing similar strategies and helps to achieve sustainable and inclusive urban development.
Status and Market Evaluation for New Energy and Conventional Vehicles of China
Authors: Zhong Yi
Published: August 2024

Contemporarily, China’s automobile market has expanded rapidly and become one of the world’s largest automobile producers and consumers. However, facing the environmental pressure and the demand of energy structure transformation, the automobile industry is experiencing a profound change from traditional fuel vehicles to new energy vehicles. This study analyzes the development status and market assessment of traditional fuel vehicles and new energy vehicles in China, and explores the changes and differences between the two. The sales of new energy vehicles show significant growth, and the market share is also rising year by year, while the sales of fuel vehicles show a downward trend. Despite the rapid expansion of the new energy vehicle market, it is still facing problems such as profitability issues, uneven investment in R&D, regulatory mechanisms to be improved and lagging infrastructure construction. In contrast, the fuel vehicle industry is gradually contracting amidst policy restrictions and changes in market demand, and companies need to accelerate their transformation and upgrading, and improve their research capabilities. China’s automobile industry is in a key stage of transformation and upgrading. The traditional fuel vehicle industry needs to shift towards new energy, strengthen collaborative innovation, optimize industrial structure, and focus on the expansion of after-market services. Overall, China is expected to lead the global automotive industry in the direction of green, intelligent and low-carbon development, and realize the historic leap from a large automotive country to a strong automotive country.