bluuebunny/crossref_metadata_2025 huggingface dataset:
Multi-Armed Bandit Algorithms: Analysis and Applications Across Domains
Authors: Zhang Qinchuan
Published: June 2024

This study provides an in-depth exploration of the pivotal role of Multi-Armed Bandit (MAB) Algorithms in decision-making across diverse sectors, focusing on their theoretical foundations, real-world applications, and empirical evidence. MAB Algorithms, metaphorically representing choices among various slot machine arms with different rewards, are crucial in optimizing decisions in uncertain settings by striking a balance between exploration and exploitation. It examines four principal algorithms—Greedy, Epsilon-Greedy, Upper Confidence Bound, and Thompson Sampling—each tailored for specific types of decision-making scenarios. Their applications are extensive, particularly in fields like recommendation systems, financial strategy formulation, and network security, where they enable adaptive learning and strategic optimization. In the context of the 5G era, MAB Algorithms are instrumental in effectively managing wireless network resources amidst dynamic conditions. This is further exemplified through empirical studies, such as research on decision-making under uncertainty, which demonstrate the algorithms' effectiveness in guiding choices in experimental setups. The paper highlights the growing importance and sophistication of MAB Algorithms, emphasizing their significant role in advancing human decision-making capabilities.
Between Man and Machine: A Posthumanist Analysis of I, Robot
Authors: Ding Zhili
Published: June 2024

In Isaac Asimov’s groundbreaking anthology, I, Robot, the intricacies of human and robotic interactions take center stage, delving deep into questions of consciousness, right, morality. Characterized by Asimov’s unique blend of science fiction and philosophical pondering, the stories establish a framework to reflect on the evolving dynamics of an advanced technological society in space. Robots are capable to interact with human, to interpret complicate orders and act automatically, to help human with dull or dangerous works such as calculating and mining, even replacing the workers. Asimov also raised Three Laws of Robotics to make sure that all robots function in order. Through the lens of posthumanism, the anthology is examined for its portrayal of the blurred boundaries between human and artificial intelligences. Robots and human co-exist in the society. However, due to the limitation of “Three Laws of Robotics”, some logical contradictions inevitably appears and lead to the dysfunction of robots. As a result, I, Robot emerges as a poignant critique of humanity’s ethical and existential challenges in the face of rapid technological advancements. Building on existing research, this article attempts to forge a new perspective by reflecting on the broader implications of the artificial intelligence in Asimov’s works through the lens of post-humanism. It considers the existential questions of AI on a consciousness level, explores the egalitarian relationship between humans and machines from a rights perspective, and analyzes the concepts of “humanity” and “human-like” from a moral and ethical standpoint. It encourages readers to recognize that robots are not mere slaves to humans; instead, humans should view AI with equality and reverence towards the advancements of the era’s technology. Humanity should step away from anthropocentrism, not solely viewing humans as the measure of all things in this rapidly evolving era of AI, and properly handle the relationship between humans and non-humans. Currently, with rapid advancements in science and technology, the world of human-machine coexistence depicted by Isaac Asimov is increasingly becoming a reality. The emergence of artificial intelligences like AlphaGo and ChatGPT constantly reminds us of the advent of a post-human era. This article aims to examine the connections between AI and humans, discussing the dynamic interaction and mutual shaping between robots and human society. This article hopes to provide new thoughts and strategies for understanding and addressing the challenges brought by the age of artificial intelligence.
Research on the Teaching Model of Office Space Design in the Context of Combining Curriculum and Competition
Authors: Zhou Mengqi
Published: June 2024

The teaching philosophy of combining courses with competitions has been a hot topic in the field of education in recent years. Integrating competitions into the curriculum makes teaching more diverse. At present, many design teachers are trying to introduce this concept into curriculum teaching. However, many problems were also encountered during the integration process. This article takes the course of office space design as the carrier, studies the feasibility of introducing competition into teaching, and explores a new teaching model that combines curriculum and competition. This study aims to unify theoretical teaching with practical teaching, thereby cultivating applied skilled talents.
Dynamic Behavior Analysis of Drilling String in Horizontal Section of Deep-Sea Gas Well
Authors: Yuan Hong , Wang Baojin , Zhang Wenrui
Published: June 2024

In this paper, a mathematical model of axial vibration of drill string near drill bit in horizontal well under natural gas is established considering the effects of gravity, load and fluid on drill string system. Based on the developed drilling string dynamic test platform, the axial vibration experiments of drilling string system under different gas content and gas flow rate are carried out. The experimental results show that the axial vibration of drill string is more serious and the vibration amplitude increases with the increase of air flow velocity and gas content.
Overview of Song foreign trade policy
Authors: Ma Shuhan
Published: June 2024

China's maritime foreign trade has a long history. During the Tang Dynasty, there was already a full-time official - the Sea Market Supervisor - in charge of overseas trade. Since the beginning of the Five Dynasties and Ten Kingdoms, Nanhan, Wuyue and Min have joined the overseas trade in order to seize greater interests, such as Guangzhou, Quanzhou and other ports even more so. By the Song Dynasty, the scale of marine foreign trade was far greater than that of the previous dynasty, and it was incomparably prosperous. This paper first analyses the reasons for the change of commercial policy in the Song Dynasty, and then briefly analyses the reasons for its development through the Song Dynasty's foreign trade and foreign policy.
A Study of Musical Influence Networks and Genre Evolution Based on the Pagerank Approach
Authors: Hu Yandong , Han Minglei , Li Yuxin , Wu Wenjia , Tian Yan
Published: June 2024

The aim of this study is to investigate the definition of musical influence networks and the construction of multilayer directed networks. By analyzing the provided dataset, the parameters of an artist's musical influence were evaluated and a musical influence network was constructed using the Pagerank method. The study also extends the single-layer network parameters to a multilayer network and proposes a centrality measure based on node degree. In terms of genre analysis, the musical eigenvalues of each genre were calculated using MATLAB software and evaluated by a similarity comparison model and an influence comparison model. The results showed that there was a high degree of similarity between certain genres, and the influence of pop/rock music was the most significant. In addition, the changes and relationships of different genres over time were analyzed through multiple spatio-temporal networks, and the results showed that new musical genres have emerged over time, some of which have similar musical characteristics to existing genres.
Prediction methods for oral diseases
Authors: Yi Zhuoxuan
Published: June 2024

With the increasing advancement of science and technology, especially the rapid development of electronic computer technology, machine learning methods have obvious advantages in predicting oral diseases. Especially in the research on oral cancer, this article uses a variety of machine learning methods for prediction and has achieved some remarkable results to provide a basis for subsequent disease treatment. In the prediction analysis of oral cancer, logistic regression, Cox regression, and machine learning algorithms were used to make a preliminary judgment on the triggering factors of oral cancer. The main triggers were dietary habits, betel nut chewing, smoking, and excessive drinking. Secondly, this article explores solutions to oral cancer prediction problems. By comparing various methods, it is concluded that Cox regression is generally used to predict patient survival or recurrence rate, while logistic regression and machine learning algorithms are used to induce Judgment and evaluation of factors, among which machine learning algorithms mainly identify factors with a wide range and high complexity, while logistic regression is used to identify some specific factors. Oral cancer is a malignant tumor. Therefore, early prediction and treatment of oral cancer are not only crucial to the patient's survival rate and oral quality but also play a major role in the progress of medicine and the development of human society.
Fintech and Digital Transformation of the Financial Industry
Authors: Liang Xuanhao
Published: June 2024

With the rapid development of science and technology, various financial products and applications were changing the operation mode of the industry soundlessly. These technologies, such as blockchain technology and cryptocurrency, are generally known as fintech. Their emergence has already greatly influenced people's traditional views on the functions and transactions of money. Meanwhile, the gradual maturity and application of artificial intelligence have also changed how data is integrated and consulting business in the stereotype of the investment industry. These cutting-edge technologies were invented to improve efficiency and provide people with fresh ideas for the traditional financial industry. Although these advanced technologies brought revolutionary progress, they also had certain risks and limitations, and surveillance and thorough laws and legislation were required. This paper aims to overview the change and impact of fintech on the business mode of the traditional financial industry, mainly focusing on Robo-Advice/Artificial intelligence, Blockchain, online payment, and P2P financing.
Research on pricing and replenishment based on optimal programming model
Authors: Chen Chaolan , Wu Xi
Published: June 2024

This paper studies the law and correlatoin of different categories of vegetable commodities, and makes the total amount of replenishment and pricing strategy of each vegetable category in the next week, so as to maximize the profit of supermarket. Firstly, the correlatoin between different categories of vegetable products was analyzed based on Pearson correlatoin analysis. The results showed that flower-leaf, cauliflower, pepper had strong correlatoin with edible fungi, while aquatic rhizome and solanaceae had relatively low correlatoin with other categories of vegetables. Then, the monthly and daily sales volume of each category and single vegetable were counted, and the monthly, weekly and daily distribution function of each category and single vegetable was obtained by fitting with Python software using the least square method. The vegetable category cluster analysis based on systematic clustering was used to cluster 6 categories of vegetables, and the 6 categories of vegetables were divided into 3 categories. Then the least square method was used to fit the processed data, and the fitting function expression between the sales volume and the cost plus pricing of each category of vegetables was obtained. The replenishment quantity decision model based on time series was established, and the daily replenishment quantity decision of each vegetable category in the next week was obtained. Finally, according to the correlatoin between sales volume and price, the optimal pricing model based on dynamic market demand is established, and the most reasonable pricing is obtained and the optimal replenishment decision is made to maximize the profit of supermarket.
Study on the Path of Enhancing Entrepreneurial Activity in Chinese Cities in the Context of Digital Economy
Authors: Chen Deqin , Liu Si , Du Xiangyu , Zheng Haiqin
Published: June 2024

This study aims to explore the enhancement path of entrepreneurial activity in Chinese cities in the context of digital economy. Through literature review and empirical research methods, it analyzes the influence mechanism of digital economy on entrepreneurial activeness, and proposes corresponding enhancement strategies in light of the specific conditions of Chinese cities. It is found that digital economy effectively promotes the enhancement of entrepreneurial activity through technological innovation, business model innovation and market environment optimization. Based on this , this paper puts forward the suggestions of strengthening the construction of digital infrastructure, promoting the innovation and application of digital technology, and optimizing the entrepreneurial policy environment, with a view to providing theoretical support and practical guidance for the further enhancement of entrepreneurial activity in Chinese cities.
Applied Study of Medical Image Segmentation Based on Convolutional Neural Network
Authors: Ding Shuai , Huang Zhiyang
Published: June 2024

Medical image segmentation is one of the hot topics in today's research, and researchers have found that medical image segmentation has important application prospects and potentials in the diagnosis and treatment of diseases, however, there are still some challenges and problems in the practical application. Therefore, the research topic of this paper is the research of medical image segmentation applications based on convolutional neural networks. The research methodology of this paper is to analyze the application of existing deep learning algorithms in image segmentation. It is found that the medical image segmentation method based on the convolutional neural network can effectively improve the accuracy and efficiency of segmentation results. The reliability of segmentation can be further improved by introducing medical experts' knowledge and labeled data. In summary, the research in this paper shows that the medical image segmentation method based on convolutional neural networks has the potential and advantages to improve the accuracy and efficiency of segmentation.
Research on the Price Prediction of Commercial Housing in Beijing
Authors: Zhou Yiyang , Liu Xinping , Sun Mingju
Published: June 2024

In order to determine the best appropriate housing price prediction model, this study constructs a linear regression model, a BP neural network model, and a time series model based on data on commercial housing prices and their affecting variables in Beijing during the past 23 years. A set of 12 independent factors that impact the cost of commercial housing is selected first. Then, three models are created, and their fitting effects are compared and analyzed to forecast the average cost of commercial real estate in Shandong Province. It is shown that the multiple linear regression model is more appropriate for long-term prediction and that the time series model predicts data more recently than the BP neural network model; Therefore, it can be used if the prediction period is longer. Although home prices can be predicted theoretically using these three approaches, more work has to be done to fine-tune the applicable models.
Building a Community of Shared Future through ESG Financial pathway: Fostering Green Development and Global Cooperation
Authors: Lyu Yanke , Du Qing
Published: June 2024

The world is facing unprecedented challenges. Extreme weather events such as high temperatures,severe cold,and heavy rains are becoming more frequent and violent. The resulting natural disasters,such as droughts, floods, and wildfires, seriously threaten the ecosystem and human safety. Melting glaciers, rising sea levels, resurgence of ancient viruses, and disruption of the natural food chain will plunge the entire earth into an unprecedented crisis. The Chinese government proposed cooperation initiative to build the"the Silk Road Economic Belt and the 21st-Century Maritime Silk Road" respectively to jointly create a destiny for mankind that benefits political mutual trust, economic integration, cultural inclusion, community. In the context of "the Belt and Road initiative", building a community with a shared future for mankind through green development and cooperation with the help of ESG (environment, society and governance) is currently an important issue for the sustainable development of the entire region. The initiative aims to promote economic cooperation and exchanges among countries along the route and promote common prosperity and development. With the help of ESG concepts and practices, a framework for green development cooperation can be built for countries along the "the Belt and Road initiative" to achieve sustainable development goals. The research team recently conducted extensive research in Europe and gained two outstanding insights. First, although Europe does not have a complete industrial system,it has its own characteristics in the implementation and promotion of ESG models.The most important reason is that they attach great importance to the ESG concept , it has advantages in terms of corporate strategy, technology and financial management scale. Second, as a developing country, China has the most stable policy system and the most complete industrial system. These two points of view have important implications for thinking about building a community with a shared future for mankind through green development and cooperation through ESG paths in the context of "the Belt and Road initiative".
Simulation Computation of Two-dimensional Hexagonal Honeycomb Photonic Crystals Energy Band Structure Based on COMSOL
Authors: Cui Tong , Xin Haoran
Published: June 2024

This study employs COMSOL software, integrating the plane wave expansion method and finite element method, to simulate and analyze the energy band structure of two-dimensional hexagonal honeycomb photonic crystals. By setting parameters and conducting scans, this paper not only maps out the electric field intensity and energy band distribution but also discovers a significant enhancement of electric field intensity at the lattice's high symmetry points, indicating a higher likelihood of electromagnetic waves' presence at these points. Furthermore, the notable energy gaps between the second and third energy bands provide directions for subsequent research. The findings of this study are of significant value for research and development in optoelectronic integration and communication, demonstrating an effective comprehensive method for analyzing the energy band structure of two-dimensional hexagonal honeycomb photonic crystals.
Random Walk Regression Problem in One and Two Dimensions
Authors: Jia Chunyao
Published: June 2024

This paper examines the previous discoveries and research on the random walk problem, considers the practical application of random walk. This paper starts from the basic questions and conducts a more detailed study of the basic regression problem with one-dimensional and two-dimensional situations. Markov chains and Markov property are introduced, and then the method and important properties of series convergence are properly explained and demonstrated. Through the introduction of Brownian motion, the key part of the article is introduced, and the explanation and proof of Stirling's formula are carried out, then the proof of one-dimensional cases is entered, and the regression is proved by the above knowledge and deduction, and then the same idea is extended to the two-dimensional case for proof. Through the research and proof of this paper, the basic problem of random walk will be solved and well interpreted, laying the foundation for further research and development.
Research Progress on the Application of Machine Learning in Oil and Gas Exploration and Development
Authors: Zhang Jiarui , Zhang Jianfang , Huang Sizhe
Published: June 2024

Machine learning becomes a powerful tool for large-scale data processing and analysis in the oil and gas industry with its automation, intelligence, efficiency and high accuracy. This paper summarized the current status of the application of machine learning in oil and gas exploration and oil and gas field development in recent years.  This paper discussed the current problems faced by the application of machine learning in oil and gas exploration and development. Besides it looked forward to the future. It was found that machine learning helped to improve the efficiency and accuracy of exploration and production and reduce the risk of exploration. Apart from that, machine learning also changed the operation mode of E&P to a certain extent.
Research on the Effectiveness of Policy Interventions in Illegal Wildlife Trade Based on System Dynamics and Logistic Regression Models
Authors: Zhang Yayang
Published: June 2024

This study is dedicated to assessing the long-term impact of policy interventions on the illegal wildlife trade system. To this end, we have constructed a System Dynamics model capable of simulating the complex interactions between key variables such as illegal trade demand (D), supply (S), enforcement strength (E), public awareness (A), and project intervention (P). By understanding the dynamic relationships among these variables, we can predict the effects of policy changes on the illegal wildlife trade market. Furthermore, we have employed a Logistic Regression model to quantify the probability of project success, considering multiple dimensions including increased enforcement efforts, enhanced public awareness, project interventions, and external factors. The combination of these two models not only enhances our comprehension of the dynamics of illegal wildlife trade but also provides policymakers with a scientific framework for evaluating and optimizing strategies. Parameter estimation based on historical data and expert opinions, along with sensitivity analysis of the models, enables us to provide a basis for the effective allocation of resources and precise policy adjustments. The findings indicate that reasonable policy interventions can significantly reduce the incidence of illegal wildlife trade while raising public awareness of wildlife conservation.
Automatic Extraction of Standard Multimodal Knowledge for the Petroleum Field
Authors: Huang Shan , Yue Wangkai , Jun Liuzhu , Fei Wangyi , Xin Yangxin
Published: June 2024

As the development of network and digitalization is accelerated, huge amount of multi-modal data is generated in the standardization activities of petroleum industry exploration and development, and the number of standards is large, covering a wide range of domains and being specialized. Based on the inherent characteristics of multi-modal data and standard knowledge organization framework, this paper proposes a method for automatic knowledge extraction of standard information from standard data of petroleum industry exploration and development. This paper advances the theory depth of knowledge organization of multi-modal standard knowledge and provides effective support for standard knowledge ordination, precise knowledge service and deep knowledge discovery in petroleum industry.
Hotspots and Frontier Analysis of Green Building Research based on CiteSpace
Authors: Yue Dongyang
Published: June 2024

To examine the worldwide progress of green building and identify the areas of research focus and emerging trends over the last ten years, employed CiteSpace software to quantitatively analyze a selection of literature on green building from 2013 to 2023 in the WOS core collection. The key journals, major institutions and countries involved in the study were sorted out, and the research topics of literature high citation analysis were carried out. The research hotspots and frontiers were obtained through keyword co-occurrence, clustering, emergence and timeline analysis: 1) consumption, strategy, thermal performance, emissions are four words of the highest centrality; 2) The five major research topics are new building materials, sustainable development, green innovation, environmental impact, and building information model; 3) The combination of green building and intelligent building is the development trend; 4) Three frontier research directions are green finance, energy simulation and geopolymer concrete. Based on the above analysis, it can be concluded that: 1) Promote the further integration with BIM technology; 2) Sustainable development is still a hot topic; 3) Focus on the exploration of green building materials; 4) AI green buildings will become a trend.
Epidemiology, Diagnosis and Reconstruction of Anterior Cruciate Ligament Injury
Authors: Wang Zhe
Published: June 2024

Both female athletes and physically active persons are susceptible to anterior cruciate ligament (ACL) rupture, a common sports-related injury. The ACL is structurally complex and is considered to be an important proprioceptor, as well as limiting tibial translation. The standard test for ACL tears is magnetic resonance imaging (MRI); however, there is currently no suitable method to accurately determine the severity of the injury. Numerous factors, including gender, muscle strength, and exercise habits, are linked to the causes of ACL tears. ACL tears prevent athletes from playing sports in the near future. They could eventually develop psychological problems, chronic knee disease, and blocked nerve signals, all of which would lower their post-ACL repair return numbers and performance. Reconstruction and recovery are the two stages of ACL treatment, and the therapy plan should be tailored to each patient's unique needs. Athletes' leg muscles should be strengthened as the primary means of preventing ACL injuries, but venues and coaches should also be taken into account.
Study of Humic Acid Organic Liquid Mulching Film on Promoting Green Agriculture Development
Authors: He Tianyi
Published: June 2024

Mulching film is an important measure to promote agricultural production income and increase, the current widely used plastic mulching film has high stability, difficult to decompose, resulting in "agricultural white pollution", the development and application of degradable mulching film has become a solution. This case focuses on the study of organic multifunctional liquid mulching film with humic acid as the main raw material, which plays a unique role in promoting biological activity and soil improvement, the application of "liquid" spray film, the integration of fertilizer, pesticides, mulching film in one multi-functional comprehensive effect, to clarify its functional characteristics, alternative feasibility and the promotion of green agricultural development, and put forward the existing problems and countermeasures. This paper provides technical support and practical demonstration for the elimination of exogenous pollutants in farmland, and looks forward to the broad application prospects of this liquid mulch film in environmental protection and other aspects.
Monte Carlo simulation-based simulation of shadow occlusion efficiency of a heliostat field
Authors: Qin Tao , Hou Tianyu , Lin Yixin
Published: June 2024

Tower solar photovoltaic power plant has a broad application prospect as a sustainable energy solution, in which the shadow occlusion efficiency, as an important part of the optical efficiency of the mirror field, has always been a computational difficulty. In this paper, the geometric projection method and Monte Carlo algorithm are used to explore the shadow occlusion efficiency of a heliostat field, and the two parts of shadowing and occlusion are simulated based on the coordinate transformation under the mirror field coordinate system. By calculating the shadow occlusion efficiency, the energy loss of the heliostat system can be evaluated, and then the system design can be optimized to improve the energy harvesting efficiency of the system.
The Transformative Role of AI and Machine Learning in Retail: Enhancing Consumer Experience and Engagement - A Case Study of Morrisons
Authors: Wang Qingze
Published: June 2024

The retail industry is undergoing significant changes driven by technological advancements in Artificial Intelligence (AI) and Machine Learning (ML). Traditional retailers are faced with the challenge of adapting to these technologies, hence new entrants who leverage from these technologies gain competitive advantage over them, the report focuses on the case of Morrisons, a UK based supermarket chain which began as a traditional supermarket and implemented these technologies recently with the aim to enhance customer experience and operational efficiency. Morrisons has embraced AI and ML to optimize stock levels, predict demand, and improve customer service. The partnership with tech firm Blue Yonder resulted in a system that accurately predicts store-specific markets by analysing sales data and weather patterns. As a result, Morrisons achieved a 30% reduction in shelf gaps, significantly enhancing the overall shopping experience. The study analyses how Morrisons implemented AI and ML technologies in their retail operations, types of technologies adopted and their practical applications. The methodology uses a qualitative case study approach, utilising document analysis of Morrisons corporate publications, industry reports and primary data from surveys. The research highlights Morrisons strategic implementation of AI-driven systems through partnerships with leading technological companies leveraging data. also addresses the challenges faced during this digital transformation, such as staff adaption and data privacy concerns, proposing a balanced approach to the retail landscape. The findings indicate that AI and ML technologies offer a competitive advantage, but each year, they are becoming essential for survival and growth in the retail sector. Morrisons case provides critical insights into the future of the retail market through technological innovation, ethical considerations, and an improved focus on the customer shopping experience.
The Impact of Orienteering Sports in Universities on the Psychological Cognition of College Students
Authors: Hu Mengmeng , Wu Xifeng , BaiWurihan
Published: June 2024

Orienteering, as an emerging sport, has developed rapidly in China. In addition to the continuous emergence of a large number of orienteering clubs, major universities across the country are also gradually popularizing and offering this course. Through research, it has been found that the mental health status of contemporary college students is not optimistic, especially for some students whose cognitive abilities such as attention, perception, and thinking need to be improved. Orienteering can effectively improve the attention ability of college students, with a significant promoting effect on attention allocation, attention breadth, and attention stability. Orienteering is beneficial for the development of sensory perception ability among college students, with significant improvements and improvements in time perception, distance perception, and height perception.
Preface: 6th International Conference on Innovations in Economic Management and Social Science (IEMSS 2024)
Authors: Giles Burgess , Zhang Wen
Published: June 2024

The organizing committee is proud to present the proceedings of the 2024 6th International Conference on Innovations in Economic Management and Social Science (IEMSS 2024) held in Seoul, South Korea during February 24-25, 2024.
IEMSS 2024 aims to bring together researchers, scientists, engineers, and scholar students to exchange and share their experience, new ideas, and research results about all aspects of innovations in economic management and social science, and discuss the practical challenges encountered and the solutions adopted.
By submitting a paper to IEMSS 2024, the authors agreed to the review process and understood that papers would undergo a peer-review process. Manuscripts were reviewed by appropriately qualified experts in the field selected by the conference committee, who took detailed comments and-if the submission was accepted-the authors would submit a revised version that took into account this feedback.
Hopefully, all participants and other interested readers will benefit scientifically from the proceedings and also find it stimulating in the process.
With warmest regards,
IEMSS Conference Organizing Committees
Seoul, South Korea
Research on Supplier Selection of Fresh Food Supermarkets under New Retail Mode
Authors: Zhao Yang
Published: June 2024

Under the new retail mode, the market competition in the fresh produce industry is fierce. Optimizing the procurement of fresh agricultural products and selecting high-quality suppliers are conducive to reducing costs and enhancing market competitiveness of fresh supermarkets under the new retail mode. This paper constructs a supplier selection index system for fresh produce supermarkets, uses hierarchical analysis and entropy weight method to determine the comprehensive weight of the indexes, and establishes the TOPSIS supplier selection model with gray correlation improvement. And the model is applied to A fresh food supermarket under the new retail mode, and the best supplier is selected for this supermarket from four strawberry suppliers.
Application of MOF-based membrane in oil-water separation
Authors: Shen Yitian
Published: June 2024

In addition to being a serious threat to human health and the natural environment, the rising volume of oily wastewater and oil spills also causes resource depletion. Thus, there is a lot of interest in effective oil-water (O/W) separation. Scientists have looked at and suggested a variety of creative separation techniques in an attempt to address this issue. Unfortunately, the majority of these techniques have technical issues with low separation efficiency and significant energy usage. It is crucial to develop an effective oil-water separation membrane in order to address this issue. Because of their large surface area, low density, high porosity, controllable wettability, and variable pore size, have a lot of potential in this sector. This paper first categorizes several different MOF-based membranes and describe in detail their different synthesis methods, including solvent thermal method, ultrasonic method, microwave method, etc. Then, the physicochemical properties of MOF-based films are summarized in detail. The mechanism by which MOF-based films can separate oil-water mixtures is also explained. Finally, the modification of stainless steel mesh, sponge, aerogel and filtration membranes by MOF-based films, respectively, is emphasized and their applications in O/W separation are discussed.
A Study of the Financial Crisis and Relevant Monetary Policies
Authors: Wang Nianxi
Published: June 2024

This essay examines several pivotal moments in recent economic history in order to demonstrate the significant influence of monetary policy on global financial crises. Exploring the complex relationship between central banks, particularly the Federal Reserve, and the various crises that occurred, the study navigates through the consequences of monetary policy interventions. Beginning with an overview of the Federal Reserve's roles and mechanisms, the narrative unfolds into critical periods, including the stagflation of the 1970s, the subprime crisis in the 2000s, and the unprecedented challenges posed by the COVID-19 pandemic. Each crisis serves as a crucible for evaluating how well monetary policies can stabilize the economy in turbulent times. The examination centers on the application of diverse financial tools, encompassing interest rate modifications, open market operations, and non-traditional actions like asset acquisitions. Through meticulous examination, this paper seeks to explain how monetary policies, often evolving in response to economic paradigms, have shaped and reshaped the global financial landscape during times of crisis. By identifying the commonalities across these different crises, the study highlights the evolution of the Federal Reserve's strategies, underscoring its adaptability and resilience. These monetary interventions have broad implications for global financial stability, emphasizing the critical role of central banks in navigating the complexities of a rapidly evolving economic environment.
Local Environmental Officials Change and Corporate Green Innovation
Authors: Yang Peiyue
Published: June 2024

This paper analyzes the impact of environmental policy uncertainty caused by changes in local environmental officials on firms' green innovation within the theoretical framework of political cycle theory and promotion tournaments, and the impact of changes in local officials on firms' incentives to innovate by internalizing firms' environmental externality costs through two policy instruments: environmental regulations and environmental subsidies. On the other hand, subsidies are provided to firms for green innovation. On this basis, this paper tests the above theoretical analysis with a sample of A-share listed companies in China from 2010 to 2020. The study finds that the change of local environmental officials has a significant positive impact on corporate green innovation, and the positive impact is achieved by increasing environmental regulations and subsidies after the change of local environmental officials. In terms of heterogeneity, the change in local environmental officials has a positive effect on green innovation in non-state owned, non-eastern, and close regulatory proximity firms.
Urban Governance Research in China (2012-2022): Progress and Reflections
Authors: Qu Ran
Published: June 2024

Since the 18th Party Congress, urban governance has gained more and more academic attention. By combing through the Chinese urban governance research literature in the last decade (2012-2022), this paper aims to describe the current status of research in this field and point out the development direction of future research. After screening 519 core Chinese journals, a comprehensive analysis of qualitative and quantitative methods was conducted with the help of the software Cite Space. The results of the analysis show that, in terms of the construction of "invisible academy" and academic community, the participation in the field of urban governance research is on the rise, but the construction of cooperative network of researchers and research institutions needs to be improved. In terms of research themes, the number of theoretical and motivational studies has increased significantly and accounted for a large number of studies, while value-level studies have received less attention and have limited content; in terms of research types, there are more exploratory and descriptive studies and fewer explanatory studies. Overall, during this decade, the academic community of urban governance research has been gradually improved, the research themes have been refined, and the research types have been enriched. However, there is still a need to further improve the value-level and interpretive research on urban governance and to enhance interdisciplinary communication.
An Empirical Study on the Impact of Urban Digital Level on Regional Innovation Ecology in the Yangtze River Delta
Authors: Hu Rui
Published: June 2024

This paper conducts an empirical analysis based on the regional innovation ecological index and digital index of cities from 2020 to 2022 in the Yangtze River Delta jointly issued by the Institutes of Science and Development, Chinese Academy of Sciences and other research institutes. The research finds that the digital level has significantly improved the regional innovation ecological level. The promotion effect of digital level on different indicators to measure regional innovation ecology is different, and the promotion effect on innovation resources is the best. The multiple regression results show that the financial environment, social security environment, and ecological environment will affect the ecological level of regional innovation. Heterogeneity analysis shows that there are significant regional differences in the innovation ecological spillover effects at the digital level. The calculation results of the Moran’s I further verify that the digital level has a promoting effect on the regional innovation ecology. Based on the above research, this article suggests that the country should formulate relevant policies to effectively improve the digital level of cities, mobilize the enthusiasm of investors and financiers, increase environmental supervision, increase investment in social security environments, fully utilize the leading role of advanced cities to improve the ecological level of regional innovation.
Study on the Impact of Financial Decentralization on China's Green Welfare
Authors: Lu Ningjia
Published: June 2024

The 20th Party Congress pointed out that development should be planned on the basis of the harmonious coexistence of human beings and nature. A reasonable allocation of financial resources is a crucial guarantee for achieving the growth of green welfare. This paper empirically examines the impact of financial decentralization on green welfare based on panel data of 30 Chinese provinces from 2005 to 2019. Results demonstrate that: (1) Financial decentralization significantly promotes regional green welfare, and the effect is more significant in the eastern region than in the central and western region; (2) In terms of specific sub-welfare dimensions, financial decentralization can significantly foster economic welfare, social welfare and environmental welfare, but not resource welfare; (3) Furthermore, political incentive cannot enhance the contribution of financial decentralization to green welfare, and fiscal incentive can significantly reduce the contribution. The findings of this paper provide a new reference for deepening the financial decentralization system reform, ameliorating the assessment system of local governments and upgrading the level of green welfare of Chinese residents.
How does Financial Misallocation Affect Enterprise Transformation and Upgrading based on the Perspective of Digital Transformation
Authors: Lu Ningjia
Published: June 2024

Financial misallocation deviates capital factors from prices which should be determined by market supply and demand. Not only does it exacerbate economic instability at the macro level, but also reduces the operating efficiency of enterprises at the micro level. Using China A-share listed enterprises from 2008 to 2020 as the original research sample, this paper empirically investigates the impact of financial misallocation on the digital transformation of enterprises and its mechanism of action, and conducts heterogeneity analysis based on enterprise characteristics. Findings demonstrate that: (1) Financial misallocation significantly inhibits the digital transformation of enterprises; (2) Financial misallocation decelerates the transformation process by obstructing the innovation capability of enterprises; (3) The inhibitory effect of financial misallocation on digitalizations of non-SOEs and SMEs is far more evident. This study provides a meaningful empirical basis and policy enlightenment for financial resources to effectively empower the real economy and promote the high-quality development of China’s economy.
Research on the Noumena of Intellectual Property Rights from the Perspectives of Law and Economics
Authors: Yuan Haozhe
Published: June 2024

This paper aims to explore the noumena of intellectual property rights through the analysis of law and economics, examining the functions of establishing the intellectual property rights system and its independent significance compared to other rights. A new approach to goods analysis is proposed to analyze the noumena of intellectual property rights and understand the functions and construction methods of the intellectual property rights system. By comparing intellectual property rights with other noumena such as data property rights, virtual property rights, and information rights, the independent significance of intellectual property rights is explored. Furthermore, an analysis of the creating process of right noumenon leads to the establishment of the principle of primacy for the original acquisition of intellectual property rights. Based on this principle, it is argued that the noumena of intellectual property rights should be the result or the certificate of "confirming rational significance.
Under the banner of heritage conservation: The gentrification of dilapidated low-income neighborhoods in the Daming Palace Protection and Renovation Project
Authors: Li Tongxi
Published: June 2024

Understanding the dynamics and implications of urban redevelopment projects, particularly in the context of China's rapid urbanization, could inform sustainable and inclusive urban development strategies. This abstract provides an overview of the Daming Palace Protection and Renovation Project (DPPRP). Unlike other redevelopment projects that prioritize economic benefits, the DPPRP is predominantly driven by political interests, with cultural and economic factors playing supporting roles. As part of the broader integrated conservation and redevelopment program, the DPPRP holds political significance, and its implementation demonstrates clear state involvement, led by the local government. The response from residents reflects the failure of China's attempts to promote citizen participation in local governance, suggesting challenges even for participatory authoritarianism. These developments have negative implications for Chinese citizens' pursuit of their right to the city, hindering their ability to shape urban spaces and participate meaningfully in decision-making processes. The purpose of this study is to analyze the Daming Palace Protection and Renovation Project (DPPRP) in China, providing insights for policymakers and urban planners to enhance the effectiveness and inclusivity of urban redevelopment projects.
The Review of Modeling and Rendering 3D Environment: A Survey
Authors: Lin Yufei
Published: June 2024

This paper explores several topics in the field of 3D Environments, including ray tracing, rendering techniques, algorithms and optimization, data processing, real-time rendering, modeling, physical simulation, and material modeling. The paper covers a large variety of applications and techniques that are widely used in computer graphics and visualization. This paper also points out that significant progress has been made in ray tracing, texture filtering, image processing, motion synthesis, geometric modeling, and physical simulation. These advances have improved the visual quality, performance, and fidelity of computer-generated images. In addition, the article mentions the trend of integrating machine learning, deep learning, and data analysis techniques into computer graphics and visualization, especially in data processing and analysis models, to improve the results of rendering and simulation. Overall, this article explores details of the current state of the computer graphics and visualization field, highlighting the various technologies and applications which shapes the field.