bluuebunny/crossref_metadata_2025 huggingface dataset:
Analyzing on Luckin Coffee's Success in 2023 Based on the Marketing Mix Theory of 4Vs
Authors: Zheng Da
Published: July 2024

The coffee market in China has experienced notable changes due to rapid technological
progress and changing consumer preferences. Luckin Coffee has emerged as a leader in this
industry. This study aims to evaluate Luckin Coffee's achievements in 2023 using the Marketing
Mix Theory of 4Vs as an analytical framework. It will investigate the operational tactics and
marketing initiatives that have contributed to the brand's success in China's competitive coffee
industry. This paper examines Luckin Coffee's business strategy, product innovation, co-branding
initiatives, and dedication to sustainability to reveal how the company has successfully managed
rapid expansion while improving the customer experience and operational efficiency. This article
demonstrates that Luckin Coffee's strategy emphasis on market distinctiveness, adding value, and
establishing brand resonance with consumers has not only led to its impressive expansion but has
also established novel benchmarks for retail innovation in the coffee sector. This paper
provides a concise overview of the decisions and actions taken by Luckin Coffee in 2023
regarding their variation strategy, value strategy, and vibration strategy. It also offers
pertinent recommendations to Luckin Coffee in these three areas, providing valuable insights for
both scholars and professionals on how to effectively utilize technology and strategic marketing
to attain sustainable growth and establish dominance in the market.
Exploring the Development of Soft Science Fiction Films in the Chinese Film Market: Taking
Dune 2 as an Example
Authors: Ding Zichen
Published: July 2024

Following the cessation of the COVID-19 pandemic, the Chinese film industry has experienced
a resurgence, leading to fresh prospects for the Chinese science fiction film market. On March
8, 2024, the Chinese mainland will host the release of Dune 2, which has garnered significant
popularity in the Chinese science fiction cinema market. The goal of this study was to
investigate whether the popularity of the Dune series of movies in the Chinese film market
persists. The objective of this study was to investigate the potential influence of the Dune
series of movies on the Chinese science fiction film industry. This article provided an in-depth
examination of the film "Dune 2" as a specific example. This analysis utilized the distinctive
attributes of the "Dune 2" film series, as well as the commercial performance and value
demonstrated in the Chinese film market. It combined fundamental business theory and cinematic
art knowledge to conduct a thorough examination and observation. The study yields three key
outcomes: the successful adaptation of movies based on popular intellectual properties, achieved
by appropriately innovating the original IP; the advancement in filming technology, which
propels the growth of science fiction movies by establishing a dedicated technology park for the
film industry; the influence of film music on the coherence of movie narratives, through the
creation of music that aligns with the unique style of each film. This study aimed to
investigate the attributes of the Chinese science fiction film market and offers recommendations
for the advancement of Chinese science fiction films.
Supply Chain Risk Management Strategies in the Era of Digital Intelligence Integration:
Strategies and Insights
Authors: Liu Qiming
Published: July 2024

This study explores the impact of digital intelligence-driven developments on business
strategies and operations, and through a combination of theoretical analyses and case studies,
it provides insights into the risk landscape faced by enterprises in the context of digital and
smart transformation, offering practical solutions and insights to help them meet the
challenges. In addition, the study highlights the experience of leading manufacturing companies
such as Haier in building digital supply chains, which provides valuable experience for SMEs
seeking to improve their competitiveness and adaptability. This study also delves into key
issues that hinder the implementation of digital supply chain projects, such as financial
constraints, technological barriers, talent shortages and cybersecurity issues. Based on these
findings, this study proposes that companies adopt a phased digital transformation strategy,
focus on talent development and technology adoption, and collaborate with government and
stakeholders to create an environment that fosters digital innovation and enhances resilience.
Ultimately, successfully addressing supply chain risks in the age of digital intelligence
requires proactive strategies, flexible adaptation and cross-sectoral collaboration to drive
sustainable growth and competitiveness in the digital economy.
Research on Stock Selection Strategies Based on the Basic Value of Stocks Based on Buffett's
Theory
Authors: Chen Liuyi
Published: July 2024

The paper presented is highly significant as it explores the applicability and effectiveness
of Warren Buffett's stock value investing theory in China's A-share market. By employing five
key indicatorsdividend yield, debt-to-asset ratio, ROE, net profit growth rate, and the 200-day
moving average (MA200), the paper attempts to adjust the values of these indicators to construct
a model. This model is tested on the Chinese A-share market to verify its universality and
effectiveness. Ultimately, the author concludes that the stock value investing theory is
practical in the Chinese market, although the numerical values differ significantly from those
recommended in traditional Western literature. Specifically, the return on equity (ROE) within a
specific parameter range yields better returns, which are a quarter lower than the values
mentioned by Buffett; the forecasted net profit growth rate for the coming year shows a slight
negative correlation with excess returns within a certain range; and the latest balance sheet
debt-to-asset ratio and dividend yield are positively correlated with excess returns within a
specific range.
A Study of Debt Problems in the Chinese Real Estate Industry
Authors: Zhang Heng
Published: July 2024

This paper will focus on real estate industry in China, uses Evergrande group as a case to
compare with another Chinese real estate company Vanke and a real estate company of United State
which is AvalonBay Communities, Inc. This paper will introduce the background of real estate
industry in China, and base on the case which is bankruptcy of Evergrande Group to throughout
the causes find out the issues of real estate in China, in causes is discuss of three factors:
Industry characteristics, financing channels, loan evaluation, analysing what make Evergrande
can owe a massive $2.4 trillion in debt, and analysing the United States real estate industry
not usually having such high leverage. Essay will tell the strategy of real estate companies in
China usually do. The strategy led to Evergrande group bankruptcy and compare with Vanke uses
what strategy avoid debt crisis. Finally, conclude the chaos of real estate industry in China
reflected by Evergrande group, recognise the issues of Evergrande group and prevent the
significant consequence occur again.
A Financial Analysis and Valuation of Electric Vehicle Companies
Authors: Yang Guoweiqi
Published: July 2024

This paper examines the electric vehicle (EV) industry, with a particular focus on Tesla,
NIO, and BYD. Tesla is a leading player thanks to its efficient operations and diverse product
lineup, making it a preferred choice for investors. NIO, despite having a wide range of
products, faces profitability challenges, which may discourage investors. BYD impresses with its
consistent profitability and significant market share in China. Financial metrics such as net
profit margin, operating margin, and asset turnover are analyzed to assess the performance and
appeal of each company to investors. Tesla's operational efficiency, demonstrated by its
strategically located Superfactories in major markets, reinforces its industry leadership. Its
diverse product range and global market reach inspire investor confidence. On the other hand,
NIO grapples with negative profit margins and limited production capacity, lessening its appeal
to investors. BYD's steady profitability and considerable market share in China enhance investor
confidence. Despite intense competition and market volatility, all three companies are poised to
capitalize on the growing demand for EVs, driven by global sustainability efforts. In
conclusion, Tesla and BYD appear as appealing investment prospects due to their profitability
and market dominance, while NIO struggles to attract investors. Tesla's innovative production
strategies and extensive market reach place it at the forefront of the EV industry, likely
drawing more investors in the future.
A Financial Analysis and Valuation of BYD
Authors: Zhao Ruite
Published: July 2024

In the contemporary era, the depletion of traditional energy sources has become an
increasingly pressing concern. In response, the development of new energy technologies has
emerged as a pivotal strategy to alleviate energy shortages while aligning with ambitious carbon
neutrality objectives. Understanding and properly assessing the financial landscape and risks
faced by new energy enterprises are paramount for effective management and sustainable growth.
This paper delves into this imperative by focusing on BYD, a prominent player in the new energy
sector. Employing a comprehensive approach, this study begins with a SWOT qualitative analysis,
dissecting BYD's strengths, weaknesses, opportunities, and threats. This analysis illuminates
the nuanced landscape within which BYD operates, shedding light on both its potential and the
challenges it must navigate. Subsequently, the study employs the Price/Earnings (P/E) model to
assess BYD's valuation, providing quantitative insights into its financial standing and market
positioning. Key findings from this research reveal a promising trajectory for BYD. Over the
past two years, the company has demonstrated rapid growth in operating income, coupled with an
enhanced debt repayment capacity, indicative of its robust developmental potential. However, the
evaluation using the P/E model suggests that BYD's true value may be underestimated, hinting at
further upside potential and market opportunities. This holistic examination underscores the
importance of integrating qualitative and quantitative methodologies to comprehensively evaluate
new energy enterprises, offering valuable insights for strategic decision-making and sustainable
growth in the evolving energy landscape.
The Impact Mechanism of Digital Transformation Empowering Corporate Supply Chain
Competitiveness: A Case Study of Geely Automobile
Authors: Ou Zheming
Published: July 2024

With globalisation and the diversification of market demands, companies face increasingly
complex supply chain management challenges. As a leading automaker, Geely's efficient operation
of its supply chain is critical to maintaining market share and customer satisfaction. This
study uses Geely Automobile as a case study to explore the impact mechanism of digital
transformation on corporate supply chain competitiveness. Analysing Geely Automobile's digital
transformation practices reveals the positive impact of digital transformation on corporate
performance and supply chain resilience. The findings show that digital transformation
significantly improves corporate performance, especially in key financial indicators. At the
same time, digital transformation enhances firms' resilience in the face of risky shocks, making
them more resilient to market changes and risks. However, the study also identified challenges
and limitations in the digital transformation. Future research could provide further insights
into the relationship between digital transformation and internal management factors and the
impact of new technologies on supply chain management and firm performance to guide firms to
achieve sustained growth and enhance competitiveness.
Data-Driven Personalized Marketing in E-commerce: Practical Applications
Authors: Duan Ziqi
Published: July 2024

Data-driven personalized marketing is crucial for enhancing user experience and increasing
sales in e-commerce. This paper explores the practical applications of personalized marketing,
focusing on algorithms, user behavior analysis, and associated risks. Also, the paper
illustrates how data-driven personalized marketing is implemented and its impact on user
engagement and sales. The collection and processing of large amounts of user data are essential
for personalized marketing strategies. Various algorithms, including collaborative filtering and
deep learning, are employed for personalized recommendation systems. Real-time data analysis
techniques enable e-commerce companies to adjust marketing strategies rapidly. Combining
information from several platforms, including social media, mobile apps, and websites helps in
creating comprehensive user profiles for effective personalized marketing. Analyzing user
behavior is essential to comprehending user requirements and preferences. However, there are
risks and challenges associated with data-driven personalized marketing, including data privacy
and compliance issues, over-personalization risks, and data quality concerns.
A Financial Analysis and Valuation of FedEx Corporation
Authors: Chen Shuaijun , Luo Zixin
Published: July 2024

This paper introduces the basic situation of FedEx, including its current main business,
industry, market, market segment, revenue and so on. In addition to an initial overview, this
article provides a SWOT analysis of FedEx and analyzes its strengths, weaknesses, opportunities,
and threats in various aspects, resulting in a more comprehensive and in-depth understanding of
FedEx Corporation. At the same time, based on the extraction, calculation and analysis of the
data of the NASDAQ website and the ESTIMIZE website, this paper can derive the financial ratios
related to FedEx and analyze their trends and proportions through line charts and bar charts. In
the same way, this paper obtains and calculates financial data for three FedEx competitor
companies, including UPS, J.B Hunt and CH Robinson. After comparing FedEx with its competitors,
this paper can estimate its current advantages and risks, and the results of the analysis are
very interesting. Finally, this paper makes relevant investment proposals by taking into account
the current situation in the logistics industry.
A Financial Analysis and Valuation of First Solar, Inc.
Authors: Wu Yuhan
Published: July 2024

First Solar is an American company specializing in thin-film photovoltaic solar solutions
using Cadmium Telluride (CdTe) technology. This technology offers environmental protection and
sustainability advantages. The company maintains market competitiveness through continuous
technological improvements, enhanced efficiency and durability, and expanded production
capacity. First Solar holds significant market share in the United States and India, aided by
government incentives like the U.S. Inflation Reduction Act and Indias Production-Linked
Incentive Program. The company is expanding globally through acquisitions and long-term
agreements, with plans to build new factories in both countries to boost production.
Financially, First Solar performs well in liquidity, solvency, and profitability, ranking in the
upper-middle tier among industry competitors. Its healthy short-term debt solvency is indicated
by strong current and quick ratios, while its low debt ratio and high interest coverage ratio
highlight robust long-term debt solvency. The companys gross and net profit margins are stable
and expected to grow. First Solars earnings per share (EPS) and revenue growth rates surpass
those of its peers, and its price-to-earnings (P/E) and earnings growth (PEG) ratios suggest
lower relative future earnings growth, enhancing investment appeal. In summary, First Solar
demonstrates strong market competitiveness and growth potential with its advanced technology,
sustainable business model, and solid financial performance, positioning it as a leader in the
solar energy industry.
The integration of blockchain technology and artificial intelligence: Innovation, challenges, and future prospects
Authors: Wang Yiwen
Published: July 2024

Blockchain provides a decentralised, tamper-proof and trustworthy distributed database technology that is widely used in finance and economics, IoT and big data. Artificial intelligence (AI) provides a technology that can mimic human intelligence, learn autonomously and automate decision-making, which plays a major role in enhancing productivity, solving complex problems and improving decision-making. The two represent two of the major driving forces in technology today, and their integration is redefining our digital world. The aim of this paper is to explore the integration of these two technologies and the innovations, challenges, and future prospects they bring. First, we trace their history and evolution, introduce the basic characteristics of blockchain and AI, and explain in detail how they work. We then delve into the integration of blockchain and AI, highlighting their importance and significance in areas such as finance, supply chain and healthcare. We analyse the applications and implications of this integration for these areas, as well as the challenges and dilemmas faced, including issues of security, privacy, data leakage, and technical feasibility. Finally, we explore future trends and related work, highlighting the importance of global community collaboration and innovation to realize the potential of blockchain and AI.
Performance analysis of k-Nearest Neighbors classification on Reuters news article datasets
Authors: Yang Qian
Published: July 2024

The k-Nearest Neighbors (k-NN) algorithm is a fundamental and widely-used classification technique that has found applications in various domains, including text classification. In this paper, we present a comprehensive analysis of the k-NN classification algorithm applied to the Reuters news article dataset. Our study includes the data, implementation k-NN classification with different parameters, performance evaluation, and statistical analysis to draw meaningful conclusions. In a comprehensive analysis of the k-NN classification algorithm used for the Reuters news article data-set. A variety of metrics is used to evaluate the performance of the k-NN algorithm, such as accuracy, precision, recall, and F1 scores. These metrics provide a comprehensive view of how well the algorithm classifies news articles. Our statistical analysis reveals significant performance differences between various k-NN configurations. This can help researchers and practitioners make informed decisions when choosing the best parameters for their specific text classification tasks. In conclusion, our study provides valuable insights into the application of k-NN classification algorithms to textual data, highlighting the importance of parameter tuning and rigorous evaluation. These findings can guide practitioners to effectively use k-NN for text classification tasks and inspire further research in the field.
Snapchat for user privacy and emotional communication phenomenon
Authors: Yang Jizhuo
Published: July 2024

The article describes Snapchat as an example of a social software that violates user privacy and protects user privacy, which can be reflected from it. The article collates some of Snapchats feature innovations and unique features (compared to other social software) and explains why it has been successful in a short period of time. Most of the papers on Snapchat have focused on Snapchats marketing strategy, rather than the software itself and its impact on users. Therefore, the author of this paper considers from the perspective of users to supplement Snapchats use and protection of user privacy. In addition, this paper discusses Snapchats protection of user privacy and the innovation of its functions, and compares it with Chinese social media, which puts forward more possibilities for the development of social media.
Cops and robbers game and applications of its variant
Authors: Bao Rui
Published: July 2024

Pursuit-evasion game is a game with a pursuer player and an evader player, it has numerous applications including artificial intelligence, robot motion planning and so on. The cops and robbers game is a type of pursuit-evasion game played on graphs, and its variant is a very fruitful research area in graph theory. The purpose of this paper is to find the specific relations between pursuit-evasion game applications and different types of variants of the cops and robbers game. The research method is to find variants with different game rules and winning strategies and classify them. Then compare these rules and strategies with the applications of pursuit-evasion games to find their relationships. The comparison result shows that there are many differences between the variants and the applications, which lead to their inability to be directly related. The application of the pursuit-evasion game is mainly based on route planning and object distance, and generally contains multiple variant types, which is different from the current research direction of variant.
Fully homomorphic encryption in PPMLAn review
Authors: Liu Jingting
Published: July 2024

Fully homomorphic encryption (FHE) in privacy-preserving machine learning (PPML) is a current area of research value, aiming to achieve the protection of users private data by applying the concept of full homomorphic encryption to machine learning privacy preservation. The integration of the two involves extensive model modifications and performance issues. The current difficulties mainly focus on how to improve encryption efficiency through hardware or software, and how to apply homomorphic encryption to neural network models such as RNN that process sequence data. This paper introduces this complex research field, outlines two machine learning service models (MLaas and AIaas) that are concerned by the industry, summarizes the most advanced research technologies based on these two models in recent years, and discusses the technical difficulties and future research directions. As a difficult problem that has never been overcome in cryptography in recent decades, homomorphic technology has received extensive attention from experts and scholars and ushered in new opportunities in the current explosive development of machine learning.
Research on time-series financial data prediction and analysis based on deep recurrent neural network
Authors: Yuan Feng
Published: July 2024

Time series data is widely available in a variety of industries. By forecasting time series, decision-makers can better grasp future trends and make more effective decisions. Financial time series data exhibit non-stationarity and high volatility. High-frequency fluctuations in financial products such as exchange rates, bonds and equities may reflect external shocks and risks in global financial markets, which are potentially dangerous and may threaten national economic security or even trigger financial crises. For financial time series data, a deep recurrent neural network first progressively processes each data point in the time series through its recurrent unit. Each recurring unit can adjust its own weights to better predict or analyze future values. Over time, these recurrent units continuously update their internal state, resulting in a comprehensive understanding of the characteristics of the entire data sequence. In addition, we add a gating mechanism to further improve the network's ability to control the flow of information, so that the model is more effective when retaining long-term dependencies, so as to improve the accuracy of prediction and the stability of the model. Experimental results show that our recurrent neural network model shows higher prediction accuracy and stability than other baseline models on financial time series datasets.
Integrating threshold models with Markov chains for information diffusion in social networks
Authors: Liang Zhichao
Published: July 2024

In this paper, I introduce an agent-based approach that leverages Markov models to formalize and understand information propagation within social networks. This methodology aims to explain the internal information states of agents and employs probabilistic model checking to analyze these models. Initially, I provide a comprehensive overview of the current research on information diffusion in social networks. Following this, I delve into the fundamentals of model checking and illustrate how this technique can be used to assess model accuracy, particularly in managing large networks with high precision. To demonstrate the effectiveness of this approach, I conduct a series of experiments. The results show that this paper provides a robust and effective method for analyzing complex information diffusion and network behavior.
Weight class prediction based on sparrow search algorithm optimised random forest model
Authors: Sun Yuanming
Published: July 2024

In this paper, we improve the traditional random forest model by optimising the random forest algorithm based on sparrow search algorithm and compare the effectiveness of the two models for weight class prediction. Initial exploration of the data revealed that age, height, weight and BMI play an important role in weight class prediction. Correlation analyses showed a strong correlation between age and BMI and weight class. The experimental results show that the random forest model optimised based on the sparrow search algorithm achieves 100% in prediction accuracy, which improves the accuracy by 1.2% compared with the traditional random forest algorithm, and has better prediction effect. The significance of this paper is that a random forest algorithm optimised based on the sparrow search algorithm is proposed and experimentally demonstrated to have better performance in weight class prediction. This is of great significance in the fields of weight management, health assessment, and disease risk assessment. In addition, this study demonstrates the value of data analysis and machine learning methods in solving real-world problems. In conclusion, this paper provides new ideas for further improvement and application of machine learning algorithms, and provides references and lessons for researchers in related fields.
A review of the development and application of RF technology and its sub-technologies
Authors: Wang Bojun , Li Jingyi , Wu Tianqi , Qu Changjia
Published: July 2024

With the acceleration of industry reform, new communication technologies are required to have larger bandwidth, faster transmission speed and more comprehensive applications. As a mature and effective high-frequency technology, RF band technology can meet many communication requirements in practical applications and plays an irreplaceable role in current production and life. At the same time, RF technology is also an important part of modern communication system, which has a good development prospect and has been widely used in many fields. In order to let more people understand the importance of radio frequency technology and promote the further development of radio frequency technology, this paper will introduce the important applications of radio frequency technology in practice from four aspects: the application of radio frequency in satellite, radio frequency identification, radio frequency ablation technology and radio frequency integrated circuit, and treat the application of radio frequency technology in practice from different angles, and illustrate the significance and development prospects of radio frequency technology.
A review of research about automatic navigation system of mobile robots based on ROS
Authors: Yu Qiuyang
Published: July 2024

With the rapid development of technology, robotic technology is continuously updated and iterated. In this process, mobile robots are gradually entering different fields and playing important roles in people's daily lives. In this context, research on path planning for mobile robots has become a priority in order to meet the various tasks that mobile robots need to handle in different situations. This paper proposes a ROS-based mobile robot autonomous navigation system, which uses the gampping algorithm to implement SLAM technology for building environment maps. It addresses the accuracy issues found in traditional map construction methods and improves localization accuracy by combining IMU with laser odometry. The paper focuses on the problem of path planning for mobile robots and mainly compares and analyzes the advantages and disadvantages of the A* algorithm and Dijkstra algorithm in path planning algorithms, aiming to find a more suitable path planning algorithm. This paper provides support for the development of the modern mobile robot field.
Exploring Extra-Curricular Bootcamps: A Qualitative Study on Accelerated Learning in Higher Education
Authors: Rietveld Jacqueline , Waalkens Jan
Published: July 2024

In response to the persistent challenge of study delay in higher education in the Netherlands, innovative approaches such as extra-curricular bootcamps have emerged. These dynamic and intensive programs offer an alternative to traditional education, providing accelerated learning experiences for students. Teachers are increasingly taking on coaching roles, guiding students through their study progress and choices. This article presents the findings of a qualitative research project of graduation bootcamps during three study years with 225 last year students with substantial study delay. We used open coding to get to the themes of key elements such as collaboration, peer interactions, teaching methods, motivation, and coaching within the context of bootcamps. We subsequently used selective coding based on the Self Determination Theory to further analyse the data. Although the implementation faced challenges, the results show that ongoing support and a community of like-minded individuals are essential for success. This study confirms the literature on the need for motivation and structured support in overcoming academic delays and provides practical insights for the development of effective educational interventions.
Impact of Technology in Classrooms in the Colleges of Kathmandu: Challenges and Policy Recommendations
Authors: Acharya Tulasi , Dhungana Gopi Krishna
Published: July 2024

The integration of technology in classrooms has transformed educational practices globally, accelerated notably by the COVID-19 pandemic. This study examines the impact of technology in colleges throughout Kathmandu, Nepal, focusing on both its benefits and challenges. Technology, including platforms like Google Classroom and educational apps, has significantly enhanced engagement and learning experiences for students, as highlighted by educators and learners surveyed. However, persistent challenges such as inadequate infrastructure, limited access to devices, and technical issues like unreliable internet connectivity hinder widespread adoption and effective use. Through a mixed-methods approach, utilizing surveys and narrative analysis, the article interprets experiences and insights from teachers and students and discusses themes that underscore the critical role of technology in improving educational access and quality in Nepal. Teachers express varying degrees of confidence and readiness in integrating technology, while students report increased engagement and improved learning outcomes facilitated by digital tools. The discussed results reflect on both the challenges and opportunities of technology in classrooms which suggest Policy recommendations, such as enhancing infrastructure investment, providing professional development for educators, and fostering digital literacy among students to bridge the digital divide and maximize the benefits of technology in education. This research contributes to understanding the nuanced dynamics of technology integration in a developing country context, offering insights for policymakers, educators, and stakeholders to optimize educational practices and ensure inclusive access to quality education in Kathmandu and beyond.
Prevalence of Toxoplasma gondii and Cytomegalovirus in Sera of Aborted Women in Zawia City
Authors: Mabrouka A Khalleefah
Published: July 2024

Toxoplasmosis is caused by the parasite Toxoplasma gondii. This disease is widespread and is considered a zoonotic disease. Infection with this disease leads to stillbirth, miscarriage, or a birth defect during pregnancy. Aim of the study is to determine the seroprevalence of Toxoplasma gondii in the city of Zawia. Over ten months Two hundred and eleven serum samples were collected from pregnant women To be examined for Toxoplasma gondii and cytomegalovirus at Al-Zawiya Hospital, Al-Zawiya city, Libya, and the Toxoplasma gondii parasite and cytomegalovirus were examined. The majority of aborted women were in the age group of 21-30 years (53.1%), followed by the 31-40 years age group (31.7%). Toxoplasmosis infection was more prevalent (32.7%) than cytomegalovirus (CMV) infection (15.2%), with a relatively low co-infection rate (6.6%). IgG (past/chronic infection) was present in 50.7% of cases, and IgM (recent/acute infection) in 59.2%. CMV: IgG was present in 35.5% of cases, and IgM in 69.7%. No significant association between toxoplasmosis IgG and CMV IgG. Significant association between toxoplasmosis IgG and CMV IgM, indicating a relationship between past/chronic toxoplasmosis and recent CMV infection. Highly significant association between toxoplasmosis IgM and CMV IgG, suggesting a link between recent toxoplasmosis and past/chronic CMV infection. Highly significant association between toxoplasmosis IgM and CMV IgM, indicating a strong relationship between recent infections of both pathogens. A serological screening program for early detection of toxoplasmosis and cytomegalovirus (CMV) infection in pregnant women and aborted women in Libya is considered essential to avoid all causes that pose problems for women.
Ստամոքսի լապարասկոպիկ երկայնակի մասնահատման մոտակա և հեռավոր բարդությունները․ժամանակակից պատկերացումներ
Authors: Շահբազյան Ս․ Ս.
Published: July 2024

Целью данного обзора литературы является обобщенный анализ наиболее частых осложнений при продольной резекции желудка (ПРЖ). Нами предпринято обобщенное изложение данных о международном опыте наблюдения и ведения пациентов с осложнениями наиболее популярной бариатрической процедуры – лапароскопической ПРЖ, имеющихся в русской и английской литературе, опубликованных за последние 13 лет. Проанализировано 59 источников. Выбор осуществлялся по принципу соответствия тематики исследований современным представлениям об указанных аспектах современной бариатрической хирургии. Оценка опубликованных данных показала, что все ранние и поздние осложнения бариатрической хирургии представляют собой несколько «тупиковые» ситуации, поскольку обусловлены не столько техническими ошибками, сколько изменениями метаболизма и биодинамики желудочно-кишечного тракта, непосредственно вызванными хирургическим вмешательством. Все вышесказанное привело нас к заключению об актуальности разработки усовершенствованных модификаций бариатрической хирургической техники и дифференцированного подхода к послеоперационному ведению больных.
The purpose of this literature review is a generalized analysis of the most common complications of longitudinal gastrectomy. We have undertaken a generalized presentation of data on international experience in monitoring and managing patients with complications of the most popular bariatric procedure - laparoscopic longitudinal gastrectomy, available in the Russian and English literature, published over the past 13 years. 59 sources were analyzed. The choice was made based on the principle of compliance of the research topics with modern ideas about these aspects of modern bariatric surgery. An assessment of published data showed that all early and late complications of bariatric surgery are somewhat “dead-end” situations, since they are caused not so much by technical errors as by changes in the metabolism and biodynamics of the gastrointestinal tract directly caused by surgical intervention. All of the above led us to the conclusion about the relevance of developing improved modifications of bariatric surgical techniques and a differentiated approach to postoperative management of patients.
Inspection and Analysis of the Implementation Effect of Long-Term Care Insurance in Jinan City
Authors: Sun Xiying , Min Rui
Published: July 2024

The proportion of elderly population in China is increasing, and the degree of aging is further deepening. The extension of life expectancy for the elderly is a major influencing factor in the deepening of aging. In this context, a phenomenon of "longevity but unhealthy" has emerged, making "longevity and unhealthy" gradually an undeniable survival state for the elderly. The problem of caring for disabled elderly people has become an urgent problem to be solved. This article selects the operational effect of long-term care insurance in Jinan City as the research object, analyzes the current situation of long-term care insurance in Jinan City, tests the implementation effect of long-term care insurance policies in Jinan City, and aims to further improve the long-term care insurance system.
Oppression and Awakening: Female Body Writing in A Stroke of Good Fortune
Authors: Yu Jiali
Published: July 2024

A Stroke of Good Fortune is one of many short stories by the famous American Southern female writer Flannery O’Connor. However, many critics have paid little attention to this short story and the body of the heroine “Ruby”.  Based on this, the author combines the body-related theories and analyzes the physical dilemma and fertility anxiety faced by women represented by Ruby in the novel from the perspective of feminism. This paper aims to analyze the physical oppression women face from traditional ideas, patriarchal society and capitalist system, and point out the issues of abortion rights and reproductive freedom. It expresses O ‘Connor’s sympathy and humanistic concern for the tragic fate of women, and shows her thinking on how women can get rid of the physical predicament and fertility anxiety.
Study on Teacher Questioning in Senior High School English Reading Class Based on the Development of Thinking quality
Authors: Luo Ruihuan
Published: July 2024

Teacher questioning is the most effective and intuitive English teaching tool preferred by teachers, and the quality of teacher questioning design directly affects their classroom effectiveness. The National Curriculum for Common Senior High Schools (2017 Edition) (herein after referred to as Curriculum Standard 2017) emphasizes the purpose of the high school English curriculum is to develop students' English key competence, including thinking quality, which is closely related to reading teaching. Therefore, based on the Bloom’s taxonomy of educational objectives and relevant researches on teaching questioning, this paper attempts to read and sort out relevant literatures to find out two main current problems of teacher questioning in senior high school English reading class based on the development of thinking quality. Then, this paper also puts forward the corresponding solutions so as to optimize teacher questioning in reading class and achieve the teaching objective of developing students’ thinking quality.
The Analysis and Evaluation of Task-based Language Teaching
Authors: Luo Ruihuan
Published: July 2024

This paper attempts to present the theoretical basis, definitions, and design structure of task-based language teaching by sorting out articles related to task-based language teaching and learning. Combining the author's own understanding and thinking, this paper analyzes the advantages and disadvantages of TBLT by taking parts of the task design of Unit 5 Why do you like pandas? in the second book of Grade 7 as an example. Finally, this paper draws a conclusion: We are in the post-method era. There is no one-size-fits-all method that can be adapted to every situation. So English teachers should be ready to use the most effective aspects of the various methods according to their own style, experience and ability to adapt to the various variables in teaching.
Research on the Factors of College Students' Choice of Tourist Destinations in Sichuan Province
Authors: Zhuo Yumei , Yang Simin
Published: July 2024

College student tourism has become a hot topic, and at the same time, college students have become one of the main forces in the source market of tourism destinations. In this paper, by investigating and studying the factors of college students' tourism destination choice in Sichuan Province, we analyze the 18 influencing factors affecting college students' tourism destination choice in Sichuan Province by using factor analysis and put forward a series of targeted recommendations based on this, which will help the development of tourism in Sichuan Province and promote the development of China's domestic tourism industry.
How to Improve High School Students’ L2 Writing Enjoyment
Authors: Liu Qian
Published: July 2024

For a long time, Second Language Acquisition (SLA) research focused on the influence of individual differences, such as cognition and motivation on language learning. It treated emotion as an irrelevant and irrational factor. In the last decade, however, the rapid growth of Positive Psychology in SLA has led to an "emotional movement". More and more scholars focus on both learners’ learning outcomes and individual well-being. Enjoyment as one of the positive emotion, many scholars have focused on it. Writing is considered as the most difficult part of five English skills. This essay explores high school students’ L2 writing enjoyment and provides some measures to improve their enjoyment in writing, so that teachers can improve students’ writing performance.
The Evolution and Effectiveness of Communicative Language Teaching: A Comprehensive Literature Review
Authors: Yang Lingyu
Published: July 2024

Communicative Language Teaching (CLT), as a pedagogical approach that prioritizes the practical application of language, has exerted a profound influence in the field of foreign language instruction both domestically and internationally since its theoretical underpinnings were established in 1966.This article summarizes recent domestic and international research on CLT, explores its theoretical foundation and practical application in teaching, compares the similarities and differences between CLT and other teaching methods, and analyzes the advantages and challenges of CLT in foreign language teaching. At the same time, the article looks ahead to the future development trends and research directions of CLT, aiming to provide theoretical support and practical guidance for foreign language educators.
An Inquiry into English Reading Teaching in Senior High School in the Context of Themes
Authors: Zhao Xin
Published: July 2024

In the introduction part, this paper first expounds the importance of reading teaching based on topic context, and then analyzes the current problems faced by reading teaching based on topic context in senior high school English: This paper summarizes the necessity of reading teaching based on the topic context. Finally, combining with practical reading teaching cases, this paper discusses how to teach English reading in high school according to the topic context provided by the text.
Can Family Policies Affect Fertility Behavior?
Authors: Jin Jing , Zhu Jiaming , Lu Erpo
Published: July 2024

Low fertility is an issue that many countries, including most of Europe, North America, and Confucian regions, have been facing for decades. In response to low fertility rates, many regions have implemented pro-natal family policies to encourage population growth. The impact varied: family policies can affect most Western countries and have less effect on Confucian regions. This difference stems from the significant pressure faced by young individuals in Confucian regions due to rapid industrialization. Consequently, regions influenced by Confucianism need to adopt more complex strategies to combat declining birth rates.
Graphic design in public places under digital transformation
Authors: Tao Weiming
Published: July 2024

Today, in the digital transformation, graphic design in public places is facing a series of challenges and problems, and the issue of readability of graphic design has gradually become important. Graphic design in public places needs to take into account the needs of all users, including the elderly and special groups, to ensure that the graphic design is well-readable and can be convenient and practical. The research aims to explore the ease with which contemporary graphics can build a graphic language environment for accessible recognition and humanistic care in public places in order to make information and instructions easily accessible to all user experience groups in public places.
The Other Half of the Sky or The Other Half of the West A Study of Women's Dilemma in the Third World Based on Western Centrism Theory
Authors: Zhao Xueying
Published: July 2024

This study explores the multiple dilemmas faced by women in the Third World within the framework of Western centrism theory. Western centrism, as a cultural, political, and economic system, has been continuously strengthened in the process of globalization, exerting a profound impact on the survival and development of Third World women. Through various methods such as literature review, questionnaire survey, and in-depth interviews, this study reveals the negative effects of Western centrism on Third World women in education, employment, health, family, and social status. The study finds that Western centrism not only exacerbates gender inequality but also restricts Third World women's pursuit of their cultural identity and self-worth. This study aims to provide a new theoretical perspective and practical guidance for understanding and addressing the plight of Third World women, promoting global gender equality and sustainable development.
Prediction of national carbon emission efficiency based on ARMI-Convolution LSTM*
Authors: Zhang Lele , Yang Zhihui
Published: July 2024

In this paper, convolutional long and short term neural network model(LSTM) and ARIMA model are used to fit and forecast China's carbon emission efficiency, and the weights of the two in the combined prediction are set to different values to observe the optimal fitting results and predict the future trend. First of all, in terms of prediction accuracy, the results show that the prediction accuracy of the long-term and short-term neural network model and the time series ARIMA model is less than the combined prediction accuracy. Compared with each single prediction, the combined prediction not only considers the complementarity of linear and nonlinear, but also considers the combination of mathematical model prediction and influencing factor prediction, which makes the prediction result more practical significance. Finally, the analysis results have certain enlightenment significance for the future trend.