bluuebunny/crossref_metadata_2025 huggingface dataset:
Exploring Gender Differences in Emoji-Text Relations: A Study on the Role of Gender in Emoji Communication
Authors: Ye Jiaxin
Published: December 2024

This study delves into the selection and functionality of emojis in the context of emoji-text scenarios, with a focus on gender differences. In today’s era, emojis are increasingly being utilized on online platforms to fulfill people’s daily expressive needs. The article employs a survey method, using random sampling to gather responses from 30 participants (15 males and 15 females) on this topic. The survey categorizes emojis into seven types for discussion. The results indicate that gender influences the choice of emoji-text and suggest that there may be certain intersections in the interpretation of emojis across genders. This research sheds light on how the use of emojis is not only a reflection of individual expression but also a nuanced aspect of communication that is influenced by one’s gender, highlighting the complexity of digital communication and the role of emojis in conveying meaning.
Analysis of Female Housework from the Perspective of Emotional Labor
Authors: Song Wenjie , Zhang Shu , Zhang Yixin
Published: December 2024

Previous research has primarily examined household labor from a singular perspective of gender roles. This study approaches the topic from the viewpoint of emotional labor, focusing on the surface and deep acting involved in women’s household responsibilities. By further categorizing household labor, this research helps women adjust their moods according to different types of tasks, thereby reducing the emotional toll of labor. The author employed qualitative research methods, specifically in-depth interviews, to distinguish between surface and deep acting in household labor. Through interviews and participatory observation of subjects, it was found that common physical tasks such as cleaning, cooking, and shopping are classified as surface emotional labor. In contrast, organizing celebrations and encouraging family members, while also demanding emotional energy, still fall under surface emotional labor. Activities that involve conflict resolution, relationship maintenance, and emotional regulation require long-term deep investment and are classified as deep emotional labor. The study indicates that women often need to engage in emotional expressions to meet societal expectations within the division of household labor. To alleviate women’s emotional burdens, both society and families need to take collective action to redistribute emotional labor, such as balancing responsibilities and setting labor boundaries.
Classification of Fashion-MNIST Dataset by Using Lenet-5
Authors: Guo Jiahao
Published: December 2024

This study explores the application of LeNet-5 convolutional neural network (CNN) on the Fashion-MNIST dataset to analyze its effectiveness in complex tasks using image recognition. The Fashion-MNIST dataset, comprising 70,000 28x28 pixel clothing images across 10 distinct categories, is constituted to offer a challenging benchmark for image recognition research. In the experiment, the data is first normalized and the labels are preprocessed using the one-hot encoding technique to adjust to the model’s input specifications. The LeNet-5 network combines several fully connected, pooling, and convolutional layers before using the Softmax layer to produce the probability distribution for each category. Through a series of experiments, it is found that LeNet-5 achieves 95% training accuracy and 90% validation accuracy on the Fashion-MNIST dataset, which not only confirms its effectiveness in modern image recognition tasks, but also demonstrates its good generalization ability. The study’s findings provide new insights for the future application of traditional CNN in the field of deep learning and provide new perspectives for future applications in more complex image recognition tasks. In addition, this study also provides the possibility for the application of LeNet-5 in scenarios with limited resources or high real-time requirements, providing valuable experience and reference for subsequent research.
The Pharmaceutical Applications of CRISPR-Cas9 and Its Development Trends
Authors: Sang Yu
Published: December 2024

Originally derived from the immune system of bacteria, CRISPR-Cas9 technology has rapidly developed into a revolutionary gene editing tool that is widely used in molecular biology, drug development, and gene therapy. This technology not only provides a new treatment approach for genetic diseases such as sickle cell anemia and Duchenne muscular dystrophy, but also brings breakthrough progress in cancer treatment by enhancing chimeric antigen receptor T cell (CAR-T) therapy. CRISPR-Cas9 has also shown great potential in the drug discovery stage, especially in gene screening, development of disease models, and drug resistance research. However, with the rapid development of CRISPR technology, the scientific community still needs to solve challenges such as potential off-target effects in gene editing, inefficient delivery systems, and long-term safety. In addition, the ethical issues of gene editing have also sparked widespread discussion, especially how to ensure fair access when treating genetic diseases. Despite many challenges, CRISPR-Cas9 technology still shows great application prospects in the future of drug development and gene therapy.
The Application of ChatGPT in Improving English Education
Authors: Liu Xiao
Published: December 2024

Nowadays, people are getting more aware of the importance of English education as English is the most predominant language in the world. Traditional English learning methods has their limitations. The emergence of the new Artificial Intelligence (AI) technologies gave rise to proposals on combining English education with AI. This paper discussed how learners could use Chat Generative Pre-Trained Transformer (ChatGPT) to help with their English studying in four categories. In reading and writing, this paper illustrated how the basic abilities of ChatGPT can aid in the two skills. Comparisons with commercial products and human tutoring were also made to show the advantages and drawbacks of the model. In listening and speaking, this paper introduced the app version of ChatGPT, and how its designs are specifically suitable for listening and speaking practices. This paper also mentioned how the app can work together with other softwares in detail optimization, like Text-to-Speech (TTS) tools that provide higher audio quality in listening. The applications have displayed the feasibility of this combination, despite the potential limitations and challenges caused by the lack of refinement on the model. Algorithms are designed to solve the issues, and the future in this field is only going to be more promising.
A Study of Development Strategies for Suspense Movies Remakes
Authors: Zhang Yuezichun
Published: December 2024

Nowadays, suspense movies are becoming more and more popular among the audience. This paper primarily focuses on examining the strategies for adapting suspense movies in Chinese cultural contexts. The process of remaking suspense films involves intricate choices that respect the original work’s atmosphere while catering to the cultural preferences of a new audience. Since the successful adaptation of suspense films requires a deep understanding of both the source material and the local culture, it’s necessary to analyze the important elements suspense movie remakes need to include and combine them with real examples. Through detailed investigations, this study identifies that a suspense film remake’s success is often closely linked with its cultural adaptation efforts. The research findings underscore the importance of integrating local cultural elements, such as location choices and character development, to enhance audience engagement and preserve the story’s suspenseful essence. This study highlights the creative and immersive nature of suspense film adaptations. The insights gained from this research can provide valuable guidance for filmmakers and producers, helping them make informed decisions to support the growth of both the suspense film remake industry and cross-cultural storytelling. Overall, this study emphasizes various existing articles and examples and extracts the key factors out of these examples.
The Analyses of Approaches related to Safety Enhancement of Dangerous Goods Transportation in a Science Perspective
Authors: Zhang Hexuan
Published: December 2024

Nowadays, the demand for dangerous goods and their transportation is increasing daily. Consequently, the accidents that are caused by it are also becoming more and more common, since those accidents related to dangerous goods’ transportation are usually extremely harmful and have many adverse consequences, enhancing its safety is now therefore becoming very critical. Subsequently, in this paper, three possible approaches that are possible to enhance the transportation safety of three certain kinds of dangerous goods, which are corrosive goods, explosive and flammable goods, and radioactive goods, have been brought and analyzed. A brief introduction to each approach is provided, and each of those introductions will be followed by an alanylation including but not limited to the pros and cons of those approaches, the feasibility of them, and also the further optimizing methods for them. By conducting those eventually optimized approaches, combined with other approaches, perhaps a non-scientific perspective approach, plenty of those dangerous-goods’-transportations-related accidents can be prevented, and the safety of it and the safety issues related to it can also be enhanced to a great extent.
Prediction of Depression and Anxiety based on Machine Learning
Authors: Tian Yuqiu
Published: December 2024

Depression and anxiety are prevalent and often comorbid mental health disorders, necessitating accurate prediction and timely intervention to mitigate their impact. This study focuses on leveraging advanced machine learning techniques to predict the levels of depression and anxiety, while also exploring the intricate correlation between these two conditions. Using a dataset comprising depression and anxiety scores, several Machine Learning models, including the SVM, KNN, XGBoost and CatBoost were employed to develop predictive models. The experimental results revealed that CatBoost outperformed other models, achieving an accuracy of 98.9%, followed closely by SVM. Additionally, Pearson and Spearman correlation analyses demonstrated a strong relationship between depression and anxiety scores, with coefficients of 0.6261 and 0.6208, respectively. These findings underscore machine learning’s capacity to forecast mental health issues and highlight the significant correlation between depression and anxiety, providing a robust basis for developing more effective and timely early intervention strategies to improve mental health outcomes.
The Application of Nanotechnology to Ameliorate Copper Pollution of Mine Water in China
Authors: Liu Yazhuo
Published: December 2024

Mine water pollution is a serious problem in China and has caused certain impacts on human health, water and soil. This paper talks about the applications of nanotechnology in treating copper ions in mine water, which have advantages over the traditional methods, and discusses two potential nanomaterials-graphene and zinc oxide nanoparticles based on references. The authors describe the concepts, synthesized methods, and advantages of each material. After researching, the literature revealed attractive prospects for removing copper ions from mine water using carbon nanomaterials, including the benefits of using carbon nanomaterials to adsorb copper ions, the introduction of graphene and graphene oxide, and some synthesized methods of graphene and its derivatives. In addition, the eco-friendly synthesized process of zinc oxide nanoparticles, the great performance of the absorption capacity on Cu ions, and its fundamental function in the synthesis of various nanomaterials contribute to the promising prospect of ZnO nanoparticles.
Unveiling the Influencing Factors of Advertisement and Study by Linear Regression Approach
Authors: Zhao Xirui
Published: December 2024

The linear regression method is important in natural science. This method is widely used in economics, data science, management, medicine, biology, sociology and so on. This statistic method helps people to find the relationship between inputs and outputs and classify massive data. In the following article, some basic theories, formulas and real problems with solutions will be mentioned. This essay firstly introduces some methods about linear regression, and then use the formula and basic theories to calculate and analyze the relationship between independent and dependent variables of some real massive data. Finally, it can be found that all of data have relationship and people can use these conclusions to predict or give a suitable strategy, so it is really useful for people to prepare solutions ahead of schedule. It is one of the most fundamental methods in dealing with data, because the model of linear regression is quite easy, and provide understandable mathematical formulas, then create some scientific results.
The Study of Public Health Policies for Alzheimer’s Disease Based on the Pathogenesis
Authors: Qu Zhentao
Published: December 2024

In the current social context, the increasing aging population has led to a rising incidence of Alzheimer’s disease (AD). Today’s research primarily focuses on the development of new drugs for AD, exploration of its causes, and the formulation of reasonable policies for AD patients. As of now, there is still no curative drug available for AD. This article mainly analyzes the pathogenesis of AD, discussing its causes, symptoms, diagnostic methods, corresponding public strategies, measures, and care aspects, providing insights for the development of public health policies related to AD. Through this article, people can gain a better understanding of the mechanisms and pathology of AD, as well as the methods and policies for addressing it, while also recognizing the importance of improving public health policies for AD. It offers a general research direction for future studies, particularly concerning unresolved issues related to AD medications. It is hoped that future research will make further progress in developing new drugs specifically for AD.
Depth of Understanding of Virtual Reality Among Chinese Young People
Authors: Ye Xiaotian
Published: December 2024

Background: With the rapid development in recent years, virtual reality technology has been applied in many life scenes. Young people in China have also establish a basic cognition of virtual reality through these. However, the depth of cognition still varies between different people. In order to further analyze, this article conducted relevant research. Method: Based on the survey data obtained from the 2023 “Chinese Young People’s Awareness and Acceptance of Virtual Reality Technology”, this article collected information on the application patterns of virtual reality in various fields and negative feedback from Chinese young people on virtual reality technology. The article analyzed the sources of Chinese young people’s cognition of virtual reality and the reasons for the varying levels of cognitive depth. Result: Chinese young people’s understanding of virtual reality comes from virtual reality technology applied in fields such as entertainment, home furnishings, education, and healthcare. The reasons for uneven cognitive levels can be divided into internal and external factors. Internal factors include expensive and difficult to carry VR devices, difficult to find suitable scenes, and unsatisfactory promotional effects. On the other hand, external factors include the prevalence of other equipment in the same industry, low cost-effectiveness in development, and users’ persistent doubts.
The Establishment of Female Imagery in Agnès Varda’s Film “Vagabond”
Authors: Fang Yufei
Published: December 2024

With the advancement of film studies and theory in China, theoretical directions such as the establishment of female perspectives and female imagery have become increasingly significant. Research on female directors within the French New Wave movement will be strengthened and occupy a larger proportion. In the past, understanding of feminist aspects within the New Wave was largely confined to interview materials with Agnès Varda, lacking an in-depth exploration of the female characters in her works and the intended meanings they conveyed. This paper intends to adopt textual analysis, visual language analysis, and sociocultural context analysis to investigate these issues and proposes solutions to address some of the methods employed by Varda in establishing female imagery. It is hoped that this study will contribute to the development of research on the portrayal of female imagery in Varda’s works within the context of the French New Wave, and promote an increased proportion of feminist perspectives in Chinese film studies.
Research on the Weather Forecasting using ARIMA and SARIMA Model
Authors: Yang Yichen
Published: December 2024

Weather predicting is important nowadays as it can not only significantly diminish the uncertainty regarding the future, but also provide valuable information for people to make decisions in advance in different areas. ARIMA, SARIMA and SARIMAX models are typical predicting models, which are favored and used by scholars from various nations. This essay aims to compare the predicting performance of them through data processing, parameters selecting, performance measuring and so on. The conclusion is as follows: the seasonal factors incorporated by SARIMA model can greatly improve the accuracy of prediction with smaller errors compared with ARIMA model. Besides, when considering the exogenous variables like longitude and latitude, the predicting performance of models can be enhanced as well. These findings can provide good suggestions for further research. Therefore, research in the future is recommended to exploit the full potential of SARIMAX model in other areas with more exogenous variables and also can attempt to find the best method for selecting exogenous variables.
Analysis of the non-market treatment faced by CATL and its coping strategies
Authors: Lai Yang
Published: December 2024

With the rapid rise of the new energy vehicle industry around the world, leading companies represented by CATL are constantly exploring and innovating at the forefront of battery technology. However, CATL is not only enjoying glory, but also facing unprecedented pressures and challenges. Especially in the face of policy barriers and market access problems in key regions such as the United States, CATL’s strategic wisdom and adaptability have become the key to determining its future direction. This article aims to deeply analyze CATL’s competitive problems and challenges in the global market, especially its non-market treatment in the United States market and the corresponding strategic adjustment strategies. It also put forward forward-looking suggestions on the future development path of CATL, emphasizing that in the wave of globalization, continuous technological innovation and social responsibility fulfillment are crucial to the long-term development of enterprises. In addition, companies also need to work together to step out of their comfort zone.
Using graphene and its derivatives to remove copper ions from mine water
Authors: Ji Chenming
Published: December 2024

China’s mining industry plays a significant role in the country’s economy but also poses environmental challenges, including pollution from heavy metals like copper. Traditional methods for removing copper ions from mine water have limitations in terms of effectiveness and cost-efficiency. This study explores the potential use of graphene and its derivatives as an alternative solution for adsorbing copper ions. Graphene oxide, in particular, shows promise due to its high surface area, chemical stability, and ease of production. The research findings demonstrate that graphene oxide has a high adsorption capacity for copper ions and can effectively remove them from mine water. This environmentally friendly approach offers a viable solution for mitigating copper pollution in China’s mining industry while contributing to sustainable mining practices and enhancing water quality management. By advancing these technologies and exploring low-cost manufacturing methods for carbon nanomaterials, this research addresses industrial pollution challenges not only in China but also globally.
Theoretical and applied research progress of breakpoint regression method
Authors: Qiu Frank
Published: December 2024

Breakpoint regression is closer to quasi-natural experiments in design, and the estimated results are more accurate, which has attracted widespread attention from the academic community in recent years. This study systematically sorts out the theoretical and applied research of breakpoint regression in the field of policy evaluation. The research results show that the theoretical research on breakpoint regression mainly focuses on model applicability, bandwidth selection, data accumulation problems, etc., and breakpoint regression is in higher education, ecological environment, fiscal taxation, scientific and technological innovation, etc. The field has been widely used. This article aims to provide new ideas for the application scenarios of breakpoint regression, and research combined with machine learning can be added in the future.
PID Control and Simulation Analysis of a Servo Motor for Intelligent Guide Machinery
Authors: Sun Zhaohan
Published: December 2024

This study primarily focuses on the enhancement and improvement of guiding robots, aiming to enable these devices to provide precise navigation and timely obstacle avoidance, thereby ensuring the travel safety of individuals with disabilities. Traditional guiding robots predominantly emphasize obstacle avoidance as their main function, without considering features such as route re-planning. Additionally, the slow response rate of conventional robots is one of their significant drawbacks, often failing to provide a high level of safety for individuals with disabilities during their travels. This research concentrates on addressing the issue of slow response rates by integrating a proportional-integral-derivative (PID) control algorithm into the guiding robots. The intention is to accelerate the navigation speed of the robotic system, allowing it to respond more swiftly to real-time situations, thereby enhancing the safety of individuals with disabilities while traveling. The outcome of this research is the integration of PID technology with traditional guiding robots, resulting in an improved response time of approximately 1-2 seconds, enabling the robots to react more quickly in complex environments. The emphasis of guiding robots lies in rapid and accurate navigation, and the incorporation of the PID algorithm can effectively improve their response times, further ensuring the travel safety of individuals with disabilities.
Chinese Online Readers’ Perceptions of Character Portrayals in Fan Fiction: A Content Analysis
Authors: Shen Yue
Published: December 2024

The objective of this study was to explore the potential differences in readers’ understanding of characterization in Chinese novels, specifically between those who read original novels and those who read fan fiction. This was done through a semantic analysis of readers’ character-related comment texts from both types of novels. The aim was to gain a deeper understanding of the impact of fan creations and the psychological kernel of such recreations. This study employs a content analysis method to investigate users’ perceptions of character portrayals. The initial step involves the selection of user comments from several popular Chinese online novels. These comments are then summarized and organized into a coherent structure. Secondly, the software NVivo was employed to disassemble the statements and calculate the word frequency of the comment texts about the user’s character portrayals. Subsequently, the character portrayals are encoded and sorted, the users’ character cognition after reading the novels is quantitatively analyzed, a character portrayal bias model is constructed, and the model results are applied and verified. By analyzing the reader’s character perception, it is possible to quantitively assess the potential differences in the understanding of character portrayals. This enables a deeper understanding of the psychological causes of fan creation and provides a basis for additional research into the creation of fan content.
The application of conductive hydrogels for self-powered wearable devices: medical field
Authors: Geng Chenxiao
Published: December 2024

Wearable devices are playing an increasingly important role in various fields, particularly in healthcare. These devices not only detect vital signs but also quantify health indicators and thus play a crucial role in disease prevention. The demand for flexible wearable devices continues to rise. In this context, conductive hydrogels (CHs) have emerged as a novel flexible material that has garnered significant attention from researchers due to its excellent flexibility and biocompatibility. This article will focus on the applications and recent advancements of conductive hydrogels in the medical field, particularly in self-powered devices. Based on their functions, the applications can be categorized into two main areas: medical detection and treatment. In the realm of medical detection, conductive hydrogels can monitor physiological signals in real-time, such as electrocardiograms (ECG), electromyograms (EMG), and skin temperature. Researchers have successfully combined conductive hydrogels with flexible electrodes to achieve highly sensitive signal acquisition. This technological advancement enables long-term monitoring, greatly enhancing patient comfort and convenience. In terms of treatment, conductive hydrogels are applied in electrical stimulation therapies and drug delivery systems. They not only effectively conduct electricity but also can interact with drugs to achieve precise therapeutic effects. Despite their promise, challenges remain, including long-term stability, material integration, and scaling up manufacturing processes. Overall, the future of conductive hydrogels in wearable devices is promising, poised to advance personalized medicine and smart health management.
Defense Strategies and Development Status of Near-Earth Asteroid Impact on the Earth
Authors: Deng Keke
Published: December 2024

The impact of asteroids on the Earth has always been a matter of great concern in the fields of astronomy and planetary science. It is one of the causes of many biological extinction events in the history of the Earth. In recent years, with the rapid development of science and technology in various countries, human beings’ research and detection capabilities on asteroids impacting the Earth have been significantly improved. This article starts with how to destroy asteroids and change their orbits and conducts research on near-Earth asteroid defense technologies to analyze the basic principles of three defense technology approaches. The first is the OTM/HOTM method, which focuses on solving the changes in materials under real impact conditions in a unified framework, which significantly improves computational efficiency in multiple dimensions. The second is to establish a magnetic plasma sail-asteroid combination model for simulation calculations and change the orbit of the asteroid through the interaction between the “magnetic bubble” and the plasma in the solar wind. The third is to use multiple interceptors to directly collide with weak characteristic points on near-Earth asteroids to make them non-threatening. Based on the current status and development ideas of asteroid defense technology, combined with the existing technical foundation, this article discusses suggestions for developing effective asteroid defense and briefly describes the current status of the development of near-Earth asteroid defense.
The Impact of Music Therapy on Individuals with Autism
Authors: Weng Qixuan , Yan Lipu , Zhang Jingxuan
Published: December 2024

Autism is a complex condition, and researchers have long debated potential treatments for this diagnosis. Autism, also known as autism spectrum disorder (ASD), encompasses a range of neurodevelopmental disorders affecting brain development. While some characteristics can be detected in early childhood, autism is often not diagnosed until later. The disorder is primarily characterized by difficulties in social interaction and communication. Other features include atypical behaviors and patterns, such as challenges in transitioning between activities, hyper-focus on details, and abnormal responses to sensory stimuli.Among the various therapeutic options, music therapy has emerged as one of the most promising approaches, with numerous studies yielding significant findings. This paper aims to provide an overview of the key findings and therapeutic approaches in the field of music therapy for individuals with autism.The therapies discussed in this paper include improvised music therapy and family-centered music therapy (FCMT). By tracking feedback from relatives, conducting clinical observations, or performing medical evaluations, clinicians can help individuals with autism using these targeted techniques and assess their effectiveness. Some therapies, such as FCMT, have been shown to improve social connections and strengthen family bonds in autistic individuals. However, they do not necessarily enhance language skills or sensory responsiveness. Additionally, therapies like Orff music therapy have been found to influence patients’ moods, offering psychological benefits such as calming, stimulation, and emotional regulation.
Predictive Analysis of Diseases Using Bayesian Inference and Markov Chain Monte Carlo Methods
Authors: Chen Sirong
Published: December 2024

Predictive Analysis of Diseases Using Bayesian Inference and Markov Chain Monte Carlo Methods” focuses on applying Bayesian inference and Markov Chain Monte Carlo to make prediction and analyzation of certain disease, including a general case study and Alzheimer’s Disease. The first application shows how, in the event that a patient receives a false diagnosis, the Bayesian inference can be used to test the likelihood that the patient has a condition. This example demonstrates how Bayesian inference can lead to a closer objective reality by iteratively modifying the prior probability to the posterior probability depending on new information. In the second application on Alzheimer’s disease, the regression model parameters (intercept and slope) are estimated using the Gibbs sampling approach and two datasets including data on Alzheimer’s patients. The final model, tested on a separate dataset, achieved an accuracy of 62%. The study demonstrates the potential of Bayesian and MCMC approaches in disease prediction, suggesting a pathway to more robust models in medical analytics.
Study of the Multimodal Emotional Metaphors Contained in Cat Meme Video
Authors: Chen Kailin , Sun Zijian
Published: December 2024

A cat meme is a kind of multimodal internet meme. It often spreads through videos with pictures, words, and audio. Although this meme is popular, there is relatively little research on the topic. This study uses qualitative research to analyze high-volume cat meme videos on Bilibili, a famous video platform in China. Therefore, the study can explore how these multimodal videos achieve emotional metaphors through different modalities. The study shows that cat meme videos achieve metaphor by human-like expressions and behaviors, as well as emotional audio and text. Therefore, cat meme videos can fulfill narrative and communicative functions.
Progress in studying the bioactive functions of Phyllanthus emblica L.
Authors: Huang Jingyao
Published: December 2024

Phyllanthus emblica L., belonging to the Phyllanthaceae family, is extensively distributed across tropical and subtropical regions. PE exhibits a range of therapeutic properties, including anti-inflammatory, antioxidant, and neuroprotective effects. It is laden with a high concentration of various bioactive compounds such as phenolic acids, flavonoids, and terpenoids. Notably, flavonols are among the most copious flavonoids present in PE fruit. Its potent antioxidant activity is primarily attributed to its high content of polyphenols, which comprise 45% of the dry fruit’s mass.Polyphenols in PE possess the capability to neutralize free radicals or chelate iron ions and are considered as good antioxidants. The phytochemicals such as tannins and terpenoids in PE are antibacterial and can act as natural antimicrobial agents to inhibit bacterial growth by destroying the bacterial cell wall or preventing the synthesis of key enzymes. Furthermore, PE possesses notable anti-inflammatory attributes, mitigating inflammation through the suppression of critical enzymes integral to the inflammatory cascade, including COX-1, COX-2, and 5-LOX. The antioxidant, antimicrobial, and anti-inflammatory characteristics of PE render it a promising candidate for a variety of applications within the realms of food and medicine.
“Evolution of Western Stereotypes and Media Portrayals of Chinese People: From Orientalism to Inclusion„
Authors: Gu Yusheng
Published: December 2024

In the past century, the West‘s attitude towards the Chinese has changed significantly, reflecting a wider social change, to be inclusive, and a deeper understanding of Chinese culture. Initially, Western concepts believed that Chinese culture was uncivilized, inferior, etc. This view led to the introduction of his laws such as the Chinese Evans Act. Stereotype. However, in recent decades, under the promotion of the rise of China‘s economic rise, Asian Americans to fight for equal rights, and the increasing attention of Western media in China‘s positive image, these views have gradually changed. Movies like „Golden Parcel“ marked the departure of traditional stereotypes, showing a Chinese role with different identities and ambitions. Today, the media plays a dual role in challenging and continuing stereotypes, but more and more trends are to describe more accurately and respect for the Chinese, thereby promoting a more balanced understanding of the world.This article will attempt to explore this issue and propose relevant viewpoints.
Research on Design Methods for Immersive Games Based on Virtual Reality
Authors: Cui Jin
Published: December 2024

Virtual Reality (VR) technology has rapidly advanced, offering immersive gaming experiences previously unattainable. However, creating truly immersive VR games remains a challenge despite improved hardware. This study investigates effective VR game design with a focus on environment design, interaction mechanics, and narrative and user interface (UI) design. The paper highlights that detailed environments enhance immersion but must balance visual quality with performance to avoid discomfort. It emphasizes the necessity of natural interaction mechanisms while considering system constraints and explores the importance of combining narrative depth with intuitive UI design. The findings suggest that successful VR game design requires a multifaceted approach that integrates detailed environmental elements, natural interactions, and a cohesive narrative. Additionally, the study underscores the significance of audio design and its role in enhancing realism and immersion. These design strategies are essential for achieving high levels of immersion and meeting the growing demand for engaging VR experiences. The research also points out the importance of testing and iterative refinement to ensure that the final product is both functional and enjoyable for users.
Research on the impact of recommendations from beauty opinion leaders on social platforms on women’s consumption intentions
Authors: Guo Guo
Published: December 2024

Based on the continuous development of marketing in the field of beauty and cosmetics, the recommendation form of beauty opinion leaders has become prevalent on social platforms. Beauty is one of the most representative industries, where women are the primary consumers, and their emerging consumption personalities are also prominent. This study proposes an investigation into how the suggestions of beauty opinion leaders have influenced the consumption psychology of female consumers. The focus of this article’s study is a phenomenon occurring on social platforms, employing a questionnaire survey method. Its research is more aligned with the social reality of internet users.
The Influence and Function of Industry-University-Research Cooperation (IURC) Mode on Financing of Private Colleges and Universities
Authors: Shang Ziyi
Published: December 2024

At present, the financing channels of private colleges and universities have attracted wide attention. Most of the studies are about the analysis of external channels such as social donations and financial means, and few analyze the financing channels of private colleges and universities from the perspective of organic unity and sustainable development of internal activities and financing. Moreover, in the field of industry-university-research, most scholars pay more attention to personnel training and other aspects, and few people look at the impact of the development path of industry-university-research on the financing of private universities from an economic perspective. This paper analyzes the influence of the development path of production, university, and research on the funding of private universities and points out the existing problems and development countermeasures. This paper analyzes and concludes that the development mode of production, university, and research has an important impact on the financing of private colleges and universities, such as expanding financing channels, improving economic income, and promoting sustainable development. Based on this, this paper puts forward the following suggestions: strengthen government policy guidance, promote the transformation of scientific research achievements, and build cooperation between industry, university, and research parks.
Research on the Differences in the Dissemination Characteristics of Fan Terminology and Internet Buzzwords: A Case Study of the Weibo Platform
Authors: Wu Zihe
Published: December 2024

Internet neologisms refer to new words, phrases, or expressions created by netizens and rapidly disseminated in the online environment, following the popularization of the internet and the rise of social media. With the rapid development of digitalization and globalization, the relationship between the cultural industry and internet neologisms has become increasingly interdependent, resulting in a phenomenon of mutual influence and collaborative development. Since the emergence of the Weibo Platform, which facilitates free expression of opinions and emotions, it has become the most widely used social tool. Two representative types of newly coined online language are fan terminology and internet buzzwords. This paper examines the differences in dissemination characteristics between “fan terminology and internet buzzwords” on the Weibo platform. The findings indicate that fan terminology spreads primarily within fan clusters, such as ‘fan super topics’, where discussions focus on specific subjects and demonstrate a high degree of uniqueness. In contrast, internet buzzwords spread across society, covering a broad and diverse range of topics and displaying weaker irreplaceability. The study further concludes that the dissemination range of fan terminology is relatively narrow, but its density is higher, making it more prone to emotional polarization. In contrast, while the dissemination range of internet buzzwords is broader, their density is sparser, resulting in a more diverse emotional spectrum and a lower likelihood of emotional polarization. This research offers valuable insights for future studies in this field and equips the cultural industry with knowledge about the dynamic shifts in social culture.
Investigating the Impact of Residual Connections and the Integration of VGG19 Architecture on U-Net for Car View Segmentation
Authors: Wang Yunyang
Published: December 2024

This study investigates the performance of three computer vision neural networks architecture, which are the standard U-Net, Deep Residual U-Net(ResU-Net), and VGG19 Integrated U-Net (VGG19U-Net) on car view segmentation. The models are trained with 4000 images and their masks and are tested at different stages of training. The validation criterion includes training and validation loss, Intersection of unions and Dice coefficient. The results demonstrate that ResU-Net outperforms the other models in segmentation accuracy while maintaining competitive prediction speeds. The VGG19U-Net shows improved performance over the standard U-Net, highlighting the benefits of deeper architectures in semantic segmentation tasks. Additionally, the research underlines the importance of architectural modifications like residual connections and deeper convolutional layers for enhancing segmentation accuracy. This study offers valuable insights into optimizing U-Net variants for vehicle segmentation, which can be extended to other real-world applications, including autonomous driving. These findings provide a view for future improvement in real-time image segmentation for complex environments.
Challenges and Prospects of Implementing C NNs in Healthcare Diagnostics
Authors: Jin Jing
Published: December 2024

Healthcare is closely related to human life, and it is one of the most important research fields in contemporary science. Healthcare is everywhere in human life. There is no doubt that when people have a disease, timely treatment is required. This article discusses a kind of Artificial intelligence which is the deep learning called Convolutional neural networks in healthcare. Doctors use Convolutional Neural Networks (CNNs) in disease prediction and detection like some kinds of common disease and cancer. CNNs reached a pretty great performance in healthcare. It has high efficiency and accuracy. This article shows common diseases such as pneumonia, heart disease and diabetes also this article demonstrates cancer such as lung cancer, skin cancer and prostate cancer. As results, those different disease prediction applications have shown CNN is a powerful and useful tool for healthcare. However Artificial intelligence still has lots of big challenges which include explanation, interactivity, adaption, privacy and so on. In the future, AI in healthcare is still bright even if there are so many difficulties. With continuous investigations, the explanation of algorithms is going to become clear, transfer ability would be better so that could save a lot of money and labors. It is expected to bring to more robust, safe, and widely applicable medical diagnostic tools.
Transparent electrodes in neuroscience: Review
Authors: Zhang Zhanwen
Published: December 2024

Transparent electrodes have received increasing attention in neuroscience area such as neural interfaces, optogenetics and implantable neural sensors due to their unique ability to combine electrical conductivity with optical transparency, enabling simultaneous neural recording and stimulation without hindering optical techniques. This review concludes transparent electrodes into five categories including metal oxide-based, metal nanowire-based, conductive polymer-based, carbon-based as well as Hybrid materials and composite structure. Starting from the most widely used and earliest transparent material ITO, this review progressively covers the latest advances in hybrid materials and composite structures. For each classical material in different categories, their drawbacks, merits and current situations are introduced. Then the applications of transparent electrodes in the field of neuroscience are introduced, especially in relation to specific disease treatments. The application prospects of transparent electrodes in the field of neurology are broad, but they still face many technical challenges and problems. The future research should explore long-term implanted neural interfaces.
Application status and development trend of two-photon polymerization technology in 3D printing field
Authors: Zhang Weilin
Published: December 2024

Two-photon polymerization (TPP) technology has garnered significant attention in the field of 3D printing due to its exceptional sub-micron resolution capabilities. This paper provides a comprehensive overview of the fundamental principles of TPP, material development, system construction, and explores its applications in micro-optics, biomedicine, and micro-electromechanical systems (MEMS). Additionally, this study analyses the technological challenges and future development directions, highlighting the importance of material innovation and interdisciplinary integration. The findings suggest that TPP technology holds immense potential in the field of high-precision manufacturing.
Research on the impact of Internet consumer credit on the consumption behavior of college students – to Take Ant Credit Pay as an example
Authors: Lin Jiayu
Published: December 2024

Internet consumer credit products, such as Ant Credit Pay, have become an important tool for college students to consume, and their impact has attracted wide attention. This article aims to discuss Ant Credit Pay ‘s specific impact of college students’ consumption behavior includes the promotion of advanced consumption, challenges to financial management, and potential credit risks. Through literature review, questionnaire survey and empirical analysis, this article reveals that Ant Credit Pay’s profound changes in the consumption pattern of college students, and put forward corresponding policy suggestions. The study found that Internet consumer credit not only improves the frequency and amount of consumption of college students, but also brings high financial management difficulty and credit risk. To this end, this article recommends helping college students better manage their personal finances and reduce the negative impact of improper use of credit products by improving the level of financial education, optimizing credit management strategies and policy interventions.
Activation of Different Brain Regions in the Resting State in Parkinson’s Patients Analyzed by fNIRS
Authors: Lu Yufei
Published: December 2024

Despite the difficulties associated with data processing, fNIRS technology shows promise for advancing cognitive studies and Parkinson’s disease research through the integration of deep learning techniques. The veracity and dependability of fNIRS data are contingent upon meticulous data collection, robust signal processing, and an acknowledgement of its inferior spatial resolution and restricted penetration depth in comparison to fMRI. The integration of resting and task state analyses using fNIRS provides a detailed insight into Parkinson’s disease, elucidating both the intrinsic brain connectivity disruptions and the dynamic responses to cognitive challenges. This enhances the diagnostic and treatment strategies employed in this field. The integration of fNIRS with EEG, motion capture, and advanced data analysis techniques markedly enhances the diagnostic accuracy of Parkinson’s disease. This is achieved by revealing distinct brain connectivity states and movement patterns, thereby paving the way for more sophisticated diagnostic and treatment approaches. The effective management of motion artefacts in fNIRS data for Parkinson’s disease research is achieved through the utilisation of advanced algorithms, including single-channel MAR, band-pass filtering and PCA. Collectively, these algorithms enhance the signal quality and facilitate the interpretability of brain activity patterns.