bluuebunny/crossref_metadata_2025 huggingface dataset:
Cultivation of Reading Ability for Children with Disabilities in Primary School
Authors: Wang Xiaoni
Published: December 2024

Good reading ability in primary school not only helps improve students' grades, but also has an important impact on the cultivation of their thinking ability, imagination, creativity, as well as the formation of moral cultivation and values. However, disabled elementary school students face many special challenges in reading. The main purpose of this study is to explore more targeted and effective strategies to cultivate the reading ability of disabled primary school students. During the research process, it found that primary school students with disabilities face many difficulties in reading, such as classroom environment and their own types of disabilities. Second, it analyzed the factors that affected pupils with reading disabilities, such as the class environment in inclusive schools, the lack of emphasis on reading skills in Special education schools, and the family environment, whether parents have special education theory to handicap students’ own physiological factors, cognitive factors and learning preferences. Finally, three different methods were proposed to cultivate the reading ability of disabled primary school students, such as drawing mind maps, using touchable picture books, and developing personalized reading plans. The cultivation of reading ability in disabled primary school students is of great significance, as it can improve their cognitive level, enhance their confidence, open the door to knowledge for them, and better integrate into society.
Studies on the Distribution of Educational Resources for Urban and Rural Regions in China Regarding Educational Equality
Authors: Wang Jingyi
Published: December 2024

The rapid economic and technological development in China induced by the "Reform and Opening Up" has posed significant challenges to education, highlighting the inequalities between urban and rural areas. This article delves into the significant educational inequalities between urban and rural areas in China, arising from disparities in facilities, teacher resources, and e-learning opportunities. The rural areas face significant educational challenges from the inequalities presented, as they cannot retain educational resources with high quality. Following, the article discusses the impact and poses improving suggestions for the education inequality problem from the students' aspect and society aspect. Then, it is shown that inequality causes mental health problems, poor learning performance, and hinders social-economic progress. The article suggests policy reforms and targeted programs to improve rural education, focusing on equitable resource distribution, teacher training, and mental health care. Bridging this gap is crucial for constructing a more equitable and inclusive educational landscape in China.
Immunotherapy Breakthrough: Immune Checkpoint Inhibitors in Cancer Treatment
Authors: Yu Zewei
Published: December 2024

Immune checkpoint inhibitors (ICIs) have transformed cancer treatment, offering new possibilities for patients with various malignancies. This review examines the molecular mechanisms of immune checkpoints (ICs), particularly the PD-1/PD-L1 and CTLA-4 pathways, and their roles in tumor immune evasion. Major ICIs, including anti-PD-1/PD-L1 and anti-CTLA-4 drugs, are discussed, with emphasis on their effectiveness in treating both solid and hematological cancers. The review also explores combination treatment strategies that aim to improve therapeutic outcomes. Despite considerable progress, challenges such as drug resistance and immune-related adverse events (irAEs) remain. These issues are addressed, alongside an exploration of future directions, including novel ICs such as LAG-3, TIM-3, and TIGIT. The conclusion highlights the significant impact of ICIs on cancer immunotherapy while acknowledging the need for continued research to overcome existing challenges. Future efforts should focus on developing more targeted therapies, optimizing combination treatments, and identifying biomarkers to enhance efficacy and safety, ultimately advancing the field of cancer immunotherapy.
The role of CXCR2 in Alzheimer’s disease
Authors: Qin Dongxu
Published: December 2024

Alzheimer's disease is associated with widespread expression of the C-X-C chemokine ligand (CXCL) 1 and its receptor, C-X-C chemokine receptor (CXCR) 2. The surface of neutrophils and monocytes/macrophages expresses CXCR2. Through the CXCL1/CXCR2 axis, these cells can be attracted to the lesion to take part in the inflammatory response. By activating certain neuronal pathways via the CXCL1/CXCR2 axis, CXCR2 expression in neurons will harm neurons. Astrocytes also express CXCR2, and when the receptor is active, the quantity of astrocytes increases but their functionality is compromised. Understanding the mechanisms underlying the CXCR2 impact during the progress of Alzheimer's disease may offer an appealing target for therapeutic therapy, as inflammation can arise at virtually any location of damage. The primary functions of CXCR2 in Alzheimer's disease are summarized in this review. CXCR2 affects the expression of Tau and Aβ, which may work in concert through microglial cells to cause Alzheimer's disease. The primary pathology associated with Alzheimer's disease is the accumulation of Tau and Aβ proteins. CXCR2's main functions in Alzheimer's disease are classified into the blood-brain barrier (BBB) disruption, γ-secretase, and neuroinflammation pathway, CXCR2 influences the production of Aβ protein in Alzheimer's disease. Additionally, it impacts Tau protein expression in Alzheimer's disease via the GSK 3 β and ERK/MAPK pathways.
The Impact of AI Application in Education on Students
Authors: Wang Yijie
Published: December 2024

Artificial intelligence (AI) is making rapid progress in education with the promise of personalized learning, intelligent instruction, and automated administration. This paper analyzes the impact of AI applications in education on students. This paper argues that this shift poses both ethical and practical challenges. For example, the use of AI may lead to data privacy and security issues for students. In addition, based on the difference in the distribution of educational resources, the use of AI makes the problem of educational inequality more obvious. Students' critical thinking skills are potentially declining due to their over-reliance on cutting-edge technology. Therefore, this paper emphasizes the need to ensure equitable access through resource allocation and enablement. At the same time, balancing the use of technology, establishing a legal framework, and implementing strong data protection safeguards are critical to maximizing the positive impact of AI in education. Students should pay attention to cultivating their own academic self-discipline and academic standards.
Discussion and Innovation of Content Marketing Based on User Portrait Generation -- Taking Salomon as an Example
Authors: Zhao Yuxi
Published: December 2024

Salomon through the collection of a large number of data to build user portraits, precise positioning of the target market, the creation of personalized content, successful on the basis of the original steady expansion of potential target customer base. The research points out that there are still some problems in the application of user portraits in content marketing, such as insufficient accuracy of user portraits and user dynamics, and the corresponding solutions are proposed. Through the construction of user portrait and content marketing integration model, interaction model and consumer behavior, user portrait and content marketing triangle dynamic model, emphasizing the importance of in-depth market research, multi-dimensional data analysis, accurate push content and continuous optimization. This study is of great significance in both theory and practice, which helps enterprises to more clearly understand the importance and existing problems of user portraits, and then formulate a more comprehensive marketing plan to improve market competitiveness and achieve sustainable development.
Analysis And Research on Overfitting and Underfitting Issues in Heart Disease Prediction Models
Authors: Hu Yuying
Published: December 2024

Research Background: Cardiovascular diseases remain the leading cause of mortality globally, necessitating the advancement of predictive models that can accurately assess heart disease risk. Factors such as cholesterol levels, smoking habits, and demographic variables add complexity and variability to modeling efforts, often resulting in overfitting or underfitting. These issues compromise the models’ applicability to new, unseen datasets, limiting their utility in clinical settings. The challenge lies not only in integrating diverse health indicators into a cohesive analytical framework but also in managing the intrinsic trade-offs between model complexity and generalizability. Study Focus and Methodology: This study addresses the pivotal challenge of overfitting and underfitting in predictive models for heart disease using a comprehensive dataset sourced from Kaggle. By employing a variety of modeling techniques, including logistic regression, random forest, K-nearest neighbors, and decision tree classifiers, this research evaluates how different models assimilate and predict based on the multifaceted data related to heart disease. Through the application of principal component analysis (PCA), this study effectively reduces dimensionality, thereby simplifying the models without sacrificing the integrity of the information. Furthermore, rigorous cross-validation methods are utilized to ensure the models maintain their accuracy and generalizability when applied to new data.
A Study on the Application of Loss Aversion Theory from the Perspective of Behavioral Economics: Taking the Fields of Business and Education as Examples
Authors: Wang Linting
Published: December 2024

People's understanding of economic behavior has gradually deepened with the development of society and the economy. From the end of the 20th century to the beginning of the 21st century, behavioral economics has gradually attracted widespread attention as an emerging discipline. The discipline combines psychological and economic theories and methods to provide new perspectives for understanding human economic decision-making. This study aims to examine the utilization of the principle of loss aversion in behavioral economics within business and education contexts. Reviewing existing literature and case studies, this study will first introduce the basic concepts of behavioral economics and how they differ from traditional economics. It will then discuss the definition of loss aversion and its importance in behavioral economics. The study will also explore the application of loss aversion and its implications from business and education perspectives. In the business context, it will examine how brand loyalty and loss aversion affect trade-in strategies and dynamic pricing for enterprises; while in education, it will consider how leveraging the principle of loss aversion can improve students' academic performance and motivation. Finally, this study will summarize the benefits of applying the principle of loss aversion in practical settings and suggest potential areas for future research.
Research on the Structural Design of a Nail-tooth Roller for Peanut Shelling
Authors: Dai Rongrong , Zhao Bo
Published: December 2024

Peanut, as an important grain and oil crop, requires shelling before oil pressing, consumption, or planting. To address the issue of labor shortages resulting from population aging, this paper presents a peanut shelling mechanism using a nail-tooth roller method to tackle this problem. Based on the structure of peanuts, the characteristics of shelling are analyzed, and a structural design employing motor-driven and a combined cleaning method of "vibrating screen + air selection" is adopted. Finite element analysis is conducted on critical components to verify their structural compliance with stiffness and strength requirements, while also validating the feasibility of the peanut sheller.
Research on the development of pension finance in China
Authors: Qiao Jinyi
Published: December 2024

Due to the huge population base in China, the aging is developing faster and faster. In addition, China's mortality rate and fertility rate are declining, and the average life expectancy is getting higher and higher. China has carried out demographic structure reform at a very fast speed, and entered the aging stage in advance. The huge population base provides opportunities for the development of old-age related industries. Financial instruments and technologies are important ways to actively respond to population aging, which has led to the creation of a specialized field of pension finance. At present, the development of China's pension finance has achieved initial results, but the top-level design and development system of pension finance has not been established, and there are many challenges. This paper first summarizes the development status of China's pension finance, then summarizes the problems encountered in the development process of China's pension finance, and finally analyzes the key path to promote the development of China's pension finance.
Analysis of the Factors Behind Tencent's Success - A Case Study Based on Honor of Kings
Authors: Dai Yiqiu
Published: December 2024

This article aims to explore the key factors of Tencent's success and take its popular mobile game "King of Glory" as a specific case for in-depth analysis. With the rapid development of mobile Internet, Tencent has made remarkable achievements in the game field with its keen market insight and excellent product innovation ability. As one of Tencent's representative works, "King of Glory" not only occupies a leading position in the domestic market but also successfully expands to the global market, with more than 200 million registered users and more than 3 billion monthly flow. This paper first Outlines the background and development goals of Tencent and "King of Glory", and then analyzes the core elements of Tencent's success in detail from the perspective of the product side, operation side, and business side. Finally, this paper summarizes the implications of Tencent's success for the industry and emphasizes the importance of technological innovation, user orientation and global vision in promoting the sustainable development of enterprises.
Alcohol and Marijuana, Risk Factors for Binge Drinking and Interaction Effect of Race
Authors: Li Qianhao
Published: December 2024

Past research has suggested the relationship between alcohol and marijuana use. However, how perceptions of marijuana risk and availability are associated with alcohol misuse and the effect of race on its relation remain unclear. This study used data from the 2022 National Survey on Drug Use and Health (NSDUH) to analyze the significance and direction of the interaction effect of race on the relation between binge drinking and marijuana use, risk perception and perceived availability among 57,169 U.S. respondents aged 12+ years. Results from weighted logistic regression and interaction modeling suggested that risk perception of binge drinking had greater effects on binge drinking behaviors among Whites compared to Blacks (p < 0.05), and similarly, perceived marijuana availability affected binge drinking behaviors to a larger extent among Whites than among Blacks (p < 0.01). Perceived risk of marijuana and use of marijuana weren't found to have interaction effects with race on binge drinking. To conclude, binge drinking was associated with not only the perceived risk of alcohol but also with marijuana regarding its use, risk perception, and availability. The presence of the interaction effect of race highlights the importance when studying a wide range of populations, of subgroup analyses to capture substance use patterns more accurately and to design and implement more efficient prevention and intervention services.
A Survey on Image Style Transfer Based on Deep Learning
Authors: Huang Mingyu
Published: December 2024

With the rapid development of deep learning technology, style transfer has achieved significant breakthroughs at both algorithmic and application levels, greatly promoting innovative interactions between content and style. This paper comprehensively reviews the fundamental concepts, classifications, and widespread applications of style transfer within neural networks, with a particular focus on the principles, diverse variants, and synthesis techniques of neural network-based style transfer. Additionally, the article explores image style transfer as a research hotspot in the field of artificial intelligence and computer vision, highlighting that traditional methods primarily rely on physical and texture synthesis techniques, which often result in coarse outcomes and poor robustness. Through comparative analysis, this paper outlines the development trajectory and latest research advances in image style transfer and proposes future research directions.
Modern Tang Poetry Education: Primary and Secondary School Students
Authors: Liu Shuqian
Published: December 2024

Poetry is one of the key contents for modern primary and secondary school students to learn at their schools, among them, Tang poetry was created by the Chinese poet of the Tang Dynasty. Educators pay great attention to the education of poetry to primary and secondary school students, but due to different times and languages, it makes difficulties in the concerning process of learning Tang poetry. For this kind of issue, this article analyzes the educational value and educational significance of teaching Tang poetry to primary and secondary school students in education. This paper analyzes Tang poetry's unique literary educational value, and it provides assistance to students in language learning and influences people's cultural and moral values of education. Based on these analyses, this text makes suggestions that adjustments can be made to the learning motivation, content, and method for modern primary and secondary school students of Tang poetry education.
The Impact of the Educational Metaverse on the Future Knowledge Society
Authors: Lu Hui
Published: December 2024

The exploration and experimentation of educational metaverse theory have received widespread attention, but no articles have been placed in the context of knowledge society to study knowledge ontology. This article analyzes the impact of the education metaverse on the future knowledge society from the perspectives of knowledge production, dissemination, and application. In the future knowledge society, knowledge and innovation will be the core. In the context of the education metaverse, knowledge production will present a decentralized and boundaryless form, forming a more free and advanced learning field; The dissemination of knowledge is achieved through embodied cognition that 'perception is truth'. In the application training of knowledge, technical support is provided to achieve higher practical training, and the application of knowledge is further explored in the simulation of biochemical research experiments. Based on the application of the metaverse, this article proposes a solution to the problems of technological barriers and educational equity, virtual addiction, and technology dependence, from funding tilt and technological assistance to built-in monitoring and customized systems, and the combination of virtual and real experiences.
Analysis of the Influencing Factors and Consequences of E-commerce Return Rate
Authors: Jiang Peikun
Published: December 2024

E-commerce, as an important component of the global retail market, has deeply integrated into modern people's lives. However, in recent years, the issue of high return rates has become a major challenge faced by the e-commerce industry. This not only directly affects the sales profits and brand image of retailers, but also impacts the operational efficiency and customer satisfaction of e-commerce platforms. Therefore, this article analyzes the main factors that lead to an increase in e-commerce return rates from the perspectives of retailers and consumers and reveals the consequences that high return rates will bring to the future development of the e-commerce industry—for example, high hidden costs, unsolvable vicious cycles, and distorted business models. Meanwhile, based on the above analysis and thinking, relevant coping strategies have been compiled. This includes recommending a probability sales strategy to merchants and a Buy Online and Return in Store (BORS) strategy, proposing to the platform to establish consumer trust, targeted supervision of its merchants, and developing relevant incentive measures.
Multiple Linear Regression with Applications in College Admission Rate
Authors: Zuo Peiyu
Published: December 2024

The relevance of comprehending the factors influencing admission rates has increased due to the intensifying rivalry for college admissions. The goal of this research is to use multivariate linear regression analysis to identify and quantify the variables that significantly affect college admission rates. Using information from Kaggle, this study examines several variables, such as the cumulative grade point average (CGPA), the letter of recommendation, the statement of purpose, the university rating of the undergraduate school, the scores on the Graduate Record Examination (GRE) and the Test of English as a Foreign Language (TOEFL). This essay will use python to complete the multiple linear regression model, get the basic dataset as well as preliminary conclusions, and produce and analyze the residuals and fit tables, correlation heatmaps, plot each independent variable's relationship to the dependent variable can help to better understand how these factors affect people’s response or the dependent variable, and evaluate the findings in the results. Ultimately, the results of this study indicate that the chance of admission was mostly predicted by CGPA, GRE, letter of reference, and research experience scores; the likelihood of admission was most significantly influenced by CGPA and GRE scores. By using this information to optimize their admission approach, the institution may utilize the model to assist them determine which factors are most essential in influencing an applicant's chances of being admitted.
Improved small-world network --model definition and generative function derivation in infectious disease scenarios
Authors: Fang Yinyue
Published: December 2024

In recent years, there has been growing interest in predicting and simulating the spread and prevention of infectious diseases. The most commonly used model is the SEIR model, which characterizes the spread process by introducing parameters such as the infection rate, contact numbers, incubation period, and recovery rate. Despite its widespread application, this model has some limitations. Firstly, it is a quantity-based model that only reflects changes in quantity and cannot capture the spatial spread of the disease. Secondly, in the transmission of infectious diseases, there is a noticeable threshold phenomenon in terms of quantity, which the SEIR model cannot depict. The use of SEIR in specific scenarios can partially address the aforementioned issues. Common approaches include considering individuals as organized within a small-world network, where the proximity of individuals on this network influences the spread of infectious diseases. The model constructed in this paper attempts to introduce geographical space on this basis, defining a small-world network in geographical space and providing a generating function for the percolation phenomenon of disease transmission within it.
Exploring the Dual Impact of Green Bond Issuance on Corporate Financial Performance and Environmental Performance - The Case of BYD
Authors: Yuan Yuan
Published: December 2024

Green bonds have assumed a distinct and pivotal role in the global wave of sustainable development. As the green bond market continues to expand annually, it is imperative not to underestimate developing countries' influence. China has emerged as a dominant force in the global green bond market. This paper focuses on the Chinese market and analyses the financial and environmental effects of two successful green bond issues issued by BYD, a head of a new energy vehicle enterprise in China. Regarding the financial effect, this paper employs a three-dimensional analytical approach to assess the solvency, profitability, and operating capability of the enterprise, aiming to elucidate the positive impact of green bond issuance on its financial status. Concerning the environmental effect, several key environmental indicators from pollutant emissions, energy use efficiency, and water resource management are selected to scientifically assess the positive effect of green bond issuance on corporate environmental performance. It can be concluded that green bonds issuance can enhances both financial and environmental performance of enterprises, providing a useful reference for the green transformation of other enterprises.
Feynman Integral Problem Solving Techniques: Application on Parametric Integrals
Authors: Li Jiaqi
Published: December 2024

This paper focuses on parametric integration in Feynman integral solving technique. This paper mainly introduces the theory of integration and the method of solving the problem. This paper mainly introduces the methods and techniques of indefinite integral method and definite integral method, and introduces the methods under these two categories in detail. Different methods and techniques are adopted in this paper, and many application examples are listed. Parametric integrals have many advantages, such as rich expressions. Parametric integrals can represent a wide range of functions, including important functions in theory and practice, and have important applications in many fields. Secondly, complex integrals can be solved. For some complex integral problems, especially when the original function is not an elementary function, it may be very difficult to solve them directly. However, parametric integrals provide a new way to solve such problems by introducing parameters and exchanging operation order. Moreover, it can effectively solve practical application problems and promote the development of mathematics. The study of parametric integral not only enricheth the content of mathematical theory, but also enables mathematicians to have a deeper understanding of the properties of functions, the nature of integrals and the internal relations between them through the study of parametric integral.
Application of Large Language Models in Power System Operation and Control
Authors: Zhang Yiqian
Published: December 2024

The introduction of "carbon peak" and "carbon neutrality" targets and the vigorous advancement of national energy market construction, renewable energy sources like wind and solar power are experiencing rapid development. However, this also brings challenges in accounting for uncertainties in various operational scheduling and optimization control processes of the power system, especially for the theoretical control methods. Fortunately, Large language model (LLM) with rapid development has shown promising prospects in the power sector. This review summarizes the application of LLM technology in power system operation and control, outlining the new power system's demand for AI technology, the impact of LLM on system management, and the technological foundation including network architecture, training methods, and data configuration. Finally, it explores the applications of LLM in power system operation and control from the perspectives of generation, transmission, distribution, consumption, and equipment.
Linking Viral Marketing to Brand Awareness: The Case of Red Bull
Authors: Zhang Qinyao
Published: December 2024

Viral marketing deeply reveals the mechanism by which information spreads naturally in social networks. Through viral marketing, brands are able to achieve better results in terms of brand awareness compared to traditional marketing methods. This paper examines and analyzes how Red Bull used viral marketing strategy to increase its brand awareness in the global market. The study demonstrates the importance of this strategy in an era of globalization of markets and digitalization of information. Using the Red Bull marketing case as a backdrop, the article examines Red Bull's marketing activities and performance based on a case study approach and analyzes the reasons for its success in conjunction with data. The results of the study show that Red Bull has succeeded in expanding brand awareness globally and increasing consumer loyalty through the creation and sponsorship of extreme sports and compelling cultural events, as well as the effective use of social media platforms to enhance consumer interaction and connectivity. The conclusion of the study emphasizes the effectiveness and importance of viral marketing in modern branding strategies by analyzing Red Bull's marketing strategies.
Delivery of mRNA Vaccine and its Application for COVID-19
Authors: Chen Haozhen
Published: December 2024

mRNA vaccine has potential to bring a revolutionary change to conventional vaccines due to its high eﬃcacy, minimal risk proﬁle, less time needed for development, and potential to be manufactured substantially. This innovation comes to spotlight as it successfully demonstrated its capacity to treat severe pandemic like COVID-19. Over decades of research on mRNA vaccine, a crucial focus has been the eﬃcient delivery of mRNA vaccines into the cytosol to facilitate protein synthesis, and thus several diﬀerent methods of mRNA delivery have been developed. This passage reviews ways of mRNA delivery, especially lipid-based nanoparticle (LNP) and its application in treating COVID-19.
Research on Food Tourism Consumer Types and Characteristics
Authors: Chen Haiming , Wu Shanshan
Published: December 2024

In recent years, food tourism has received increasing attention. This study conducts empirical exploration, targeting food tourism consumers in Guangdong Province, and collected 350 questionnaires using the questionnaire survey method. The data was analyzed using spss22.0 software for descriptive analysis, reliability and validity testing, cluster analysis, and difference analysis. Ultimately, food tourism consumers were divided into four types: general food tourism, food enthusiasts, food experience, and food exploration. Their characteristics were summarized. The study also identified the demand characteristics of tourists based on different genders, ages, and monthly incomes. Furthermore, suggestions were made for the development of differentiated food product designs, the development of characteristic foods that align with tourist destinations, improving the quality of food tourism products, and extending the food tourism industry chain.
Interaction with Consumers in Brand Community Influence and Enhance Brand Loyalty- A Case Study of Lululemon
Authors: Zhang Haoxuan
Published: December 2024

In the modern market, a brand is not merely a symbol of products or services but serves as the core of a consumer community. With the widespread adoption of social media and digital interactions, the building of a brand community has become a critical strategic tool for companies to increase consumer engagement and loyalty. Lululemon, a sports brand that started with yoga apparel, has successfully attracted loyal consumers worldwide through its strong brand community. By organizing regular offline yoga classes, online social media interactions, and community events, Lululemon has not only created a powerful brand image but also fostered a deep sense of community belonging among consumers, significantly enhancing brand loyalty. This dissertation reveals how brand-consumer interactions foster emotional connections and a sense of belonging, thereby greatly boosting brand loyalty. Research shows that Lululemon has successfully leveraged multi-channel community activities to cultivate strong emotional identification with the brand and drive continuous purchasing behavior.
Comparing David Chalmer’s and John Searle’s Attitudes Toward Strong Artificial Intelligence
Authors: Li Kam Seng , Tian Jiahe , Xiong Beijun
Published: December 2024

With the rapid development of artificial intelligence, the public and academic understanding of AI capabilities are also constantly changing. This change has triggered discussions about whether AI can have consciousness, understanding, or subjective experience. The definition of consciousness itself also remains controversial in philosophy and science, further complicating the issue. This article will discuss John Searle and David Chalmers’ thoughts on whether artificial intelligence has consciousness from the three dimensions of the differences between philosophers on the development of machine learning, the relationship between consciousness and matter, and the nature of consciousness, and deeply analyze their thoughts on whether artificial intelligence has consciousness. Conscious views and opinions.
Coronary Angiography: Current Clinical Application Status and Future Prospects
Authors: Zhao Shengjie
Published: December 2024

Coronary angiography is a key technique in the diagnosis and treatment of coronary heart disease in modern cardiology. This review comprehensively discusses the principle, operation process, clinical application and important position of this technology in the diagnosis and treatment of cardiovascular diseases. As the "gold standard" for the diagnosis of coronary heart disease, coronary angiography can visually display the anatomical structure and lesions of coronary arteries, providing an important basis for treatment decision. However, its limitations such as invasive characteristics, high cost and limited ability to diagnose early lesions should not be ignored. In recent years, the development of emerging technologies such as intra-coronary ultrasound imaging (IVUS) and optical interference tomography (OCT) has provided new ways to overcome these limitations. The indications, contraindications, preoperative preparation and other clinical practice issues of coronary angiography are also discussed in this paper, aiming to provide a comprehensive understanding for medical professionals and look forward to the future development direction of this technology.
The Role of Nutrition and Dietary Patterns in Managing Type 2 Diabetes
Authors: Li Zemeng
Published: December 2024

Nowadays, type 2 diabetes(T2D) has become one of the most popular chronic diseases around the world. Then, most people who have an unhealthy diet have a higher chance of getting T2D. Most studies focus on the medical methods to treat chronic diseases like T2D, such as taking tablets or injecting insulin. However, the dietary pattern should be the primary important factor that may be firstly taken into account. In this paper, it mainly discusses the relationship between T2D and nutrition. Eventually, the paper claims that people with T2D need low carbohydrates, USFAs, fiber, vitamin C, vitamin D, and plant protein as their major nutrition. In addition, the Mediterranean diet and the dietary approaches to stop hypertension are the two main diets, which include that nutrition and suitable for T2D patients, this paper aims to remind people to realize the importance of a balanced diet and how to avoid T2D. In the future, more and more studies should pay attention to the connection of T2D and T2D because a balanced diet plays an essential role in people’s daily lives. Finally, the issue of dealing with T2D still exists so researchers may focus on the genetical factors that affect T2D and discover more different dietary patterns.
A Comparative Study of Early Childhood Education Between China and the UK
Authors: Huang Sirui
Published: December 2024

As an integral pillar of basic education, early childhood education has garnered ever-growing attention in international comparative studies. Yet, the systems and their harmonious integration continue to reveal areas for improvement. This essay meticulously explores the convergences and divergences, as well as the underlying societal and cultural factors, that shape early childhood education in China and the UK. Through a nuanced analysis, it concludes that China's approach to early education underscores knowledge acquisition and skill mastery, fostering a holistic development paradigm. At the same time, the UK emphasizes nurturing children's individuality, fostering a culture of self-discovery and independent learning. Furthermore, it recognizes the potential for cultural exchange to enrich both systems, emphasizing the importance of global perspectives in shaping effective early childhood education strategies. Based on these insights, the paper advocates for strengthened collaborations and knowledge sharing between China and the UK, encouraging a mutual learning process that leverages the strengths of both educational systems.
Ecological Risk Assessment and Environmental Policy Analysis Based on Bayesian Networks
Authors: Ma Chiyue
Published: December 2024

At present, ecological and environmental problems are becoming increasingly serious. Traditional risk assessment methods are difficult to fully integrate the complex relationships among multiple variables and lack the ability to dynamically analyze uncertainty and conditional dependence, which affects the scientific nature of environmental policies. To address this problem, this paper proposes an ecological risk assessment and environmental policy analysis framework based on Bayesian networks, aiming to effectively quantify ecological risks and provide support for policy decisions. In terms of methodology, first, a Bayesian network structure is constructed with ecosystem elements as nodes and causal relationships as edges; second, the conditional probability table is determined by combining expert knowledge with historical data; then, node sensitivity analysis and scenario simulation are carried out to identify key risk factors and sources of uncertainty; finally, the regulatory effect of policy intervention on risks is evaluated. The study took a typical river basin as an example, and the results showed that driven by pollutant concentrations and land use changes, the river basin ecosystem risk index reached 0.72, among which water quality deterioration and biodiversity decline were the main sources of risk; policy simulation showed that by increasing sewage treatment rate and vegetation coverage rate, the risk index could be reduced to 0.48, a reduction of 33.3%. Studies have shown that Bayesian networks can effectively reveal causal relationships and the impact of policy interventions in complex ecosystems, providing a scientific basis for the precise formulation of environmental policies.
Current Higher Education Personnel Training Model: Problems and Suggestions
Authors: Zhuang Qi
Published: December 2024

In the current period of fast social growth, higher education is not just charged with cultivating high-caliber experts for society, however, also bears the responsibility of progressing clinical and technological technology and promoting lasting societal development. As a result, better focus must be placed on the development of innate worth and the enhancement of academic high quality. This paper reviews the significance of higher education, assesses the inequality between the existing skill training setting and the social need, and explains the troubles existing in the ability training setting. Based on these troubles, this paper puts forward a collection of reform ideas, including educational program upgrades, sensible training, reinforcing employment skills training, advertising interdisciplinary education and learning, and personalized education and learning. The purpose is to enhance instructional excellence, boost useful guidelines, and cultivate a closer placement between scholastic pursuits and the demands of the labor market, therefore making certain that tertiary education better resolve the demands of both people and culture at large.
How Does Green Finance Contribute to the Green Economy is Growing Again After the Outbreak of the Pandemic?
Authors: Liu Fengkai
Published: December 2024

The outbreak of the COVID-19 epidemic at the end of 2019 had a huge impact on the global economy and finance. The economic maturity of natural environment after the epidemic has attracted extensive attention from scholars. Solving the problem of green finance is of vital strategic vital for achieving the coordinated development of economy, environment and society and building a sustainable future. Through literature review, this paper focuses on the picture of today's development, problems and countermeasures of environmental finance after the epidemic. The results show that in the process of post-pandemic economic reconstruction, countries should strengthen the formulation and implementation of green finance policies, strengthen environmental protection technology and green industry through financial innovation and market mechanism, and make greater contributions to the realization of climate for global change response goals and sustainable development goals. The development of sustainable finance not only helps to promote the transformation of the economy into a low-carbon, clean, green and sustainable model, but also provides important support for the global response to climatic variation and the realization of long-term and stable economic development.
A Novel Feature Fusion Method Based on RSCU and K-mer to Classify the SARS-Cov-2
Authors: Ye Fuqiang , Zhou Jianhua , Zhang Hao , Wang Lili
Published: December 2024

The SARS-Cov-2 virus exhibits a high mutation rate, which makes the prediction and classification of its genetic evolution and variation trends highly significant. Accurate classification methods not only contribute to epidemiological studies of the virus, but also play a crucial role in vaccine development and antiviral drug discovery. This study aims to systematically evaluate the accuracy and generalization capability of the RSCU (Relative Synonymous Codon Usage) and K-mer encoding techniques in the classification of the SARS-CoV-2 genome. We extracted genomic data from two major SARS-CoV-2 variants, Alpha and Beta, and applied the Support Vector Machine (SVM) classification algorithm to train the data and assess the impact of different feature encoding methods on classification performance. Furthermore, we introduce a novel multi-feature fusion method, KRSCU, which combines the sequence position information from K-mer with the synonymous codon compositions from RSCU. This method effectively captures subtle differences in genomic data, significantly improving both the accuracy and generalization capability of the classification model. Experimental results demonstrate that the KRSCU method outperforms traditional single-feature encoding approaches in SARS-CoV-2 subtype classification tasks. Our research offers new insights into genomic data analysis, with potential applications in viral mutation monitoring.
Performance Analysis and Comparison of Heart Disease Prediction Models
Authors: Jin Jiayi , Zhao Chengyun
Published: December 2024

Since cardiovascular diseases (CVDs) are the leading cause of death, it is significant for people to detect them early and take certain precautions. As a result, the paper performs the study of heart disease prediction with statistical models. In this study, the researcher analyzed a dataset from four different regions, including Cleveland, Hungarian, Switzerland, and Long Beach. Each of the regions is used as one testing dataset and the rest of the three regions are used as one training dataset, with a total of four sets of training and testing datasets. The goal is to predict heart disease with various variables using three main statistical techniques, lasso regression, random forest, and logistic regression (with feature selection). The paper will compare aspects such as accuracy, confusion matrix, and roc-auc for the models created. The results show that the models tested on the Hungarian dataset performed best overall, while the random forest algorithm achieved the highest prediction accuracy.
A Comprehensible Proof for Fermat's Last Theorem
Authors:   (Retired Executive Engineer, Energy Conservation Cell), Tamil Nadu State Electricity Board, Tamil Nadu, India., P. N Seetharaman
Published: December 2024

Fermat’s Last Theorem states that it is impossible to find positive integers A, B and C satisfying the equation An + Bn = Cn where n is any integer > 2. Taking the proofs of Fermat for the index n = 4, and Euler for n = 3, it is sufficient to prove the theorem for n = p, any prime > 3. We hypothesize that all r, s and t are non-zero integers in the equation r p + sp = tp and establish contradiction. Just for supporting the proof in the above equation, we have another equation x 3 + y3 = z3 Without loss of generality, we assert that both x and y as non-zero integers; z3 a non-zero integer; z and z2 irrational. We create transformed equations to the above two equations through parameters, into which we have incorporated the Ramanujan - Nagell equation. Solving the transformed equations we prove the theorem.
KNOWLEDGE, ATTITUDE AND PRACTICES OF INTENSIVE CARE UNIT NURSES ABOUT PHYSICAL RESTRAINT AT TERTIARY CARE HOSPITAL LAHORE
Authors: REHMAN NU , SADDIQUE H
Published: December 2024

Physical restraint is a common intervention in intensive care units (ICUs) to ensure patient safety and prevent harm. However, its inappropriate use poses ethical and clinical challenges, particularly in resource-constrained healthcare systems like Pakistan. Objective: To assess the knowledge, attitudes, and practices of ICU nurses regarding physical restraint in a tertiary care hospital in Lahore, Pakistan. Methods: A descriptive cross-sectional study was conducted among 137 ICU nurses using a structured questionnaire. The data were analyzed using SPSS version 26, with results presented as frequencies and percentages. Results: The study revealed that 47.1% of nurses demonstrated moderate knowledge of physical restraint, while 33.1% exhibited good knowledge. Attitudes were mixed, with 52.2% displaying positive attitudes and 47.8% exhibiting negative attitudes. Good practices were reported by 61.8% of nurses, whereas 38.2% showed poor adherence to recommended protocols. Nurses with higher qualifications and greater experience demonstrated significantly better knowledge and practices. Conclusion: Despite moderate knowledge and adherence to some practices, gaps in attitudes and inconsistent protocol adherence remain challenges in ICU settings. Targeted education, institutional support, and clear policies are essential to enhance nurses' competency in the ethical and effective use of physical restraints.
ASSESSMENT OF THE CRITICAL CARE NURSING COMPETENCY FOR PATIENT SAFETY IN ICU SETTING
Authors: ANAS M , SADDIQUE H , TASNEEM SS
Published: December 2024

Critical care nursing competencies are vital for ensuring patient safety in ICU settings. This study aimed to assess the knowledge, attitudes, and practices of nurses regarding critical care competencies in a tertiary care hospital in Lahore, Pakistan. Methods: A descriptive cross-sectional study was conducted among 133 ICU nurses. Data were collected using a validated questionnaire assessing competencies in preparation, patient assessment, communication, role recognition, and organization. Descriptive and inferential statistics were used to analyze the data. Results: The majority of nurses demonstrated high competency in preparation (87.2%), patient assessment (82.0%), and equitable care (88.0%). However, gaps were observed in the documentation of communication with patients’ families and consistent adherence to documentation protocols. Nurses with higher qualifications (Post RN and BSN) and more clinical experience performed significantly better than their counterparts. Conclusion: The study identifies key strengths and gaps in critical care nursing competencies. Targeted interventions, including structured training programs and the implementation of standardized protocols, are recommended to enhance competency levels and ensure patient safety in ICU settings.