Keynote Speakers
Jun. 2024 (Online Conference)
  • Kai Zhu, Associate Professor

    Beijing Children's Hospital Affiliated to Capital Medical University Heilongjiang Hospital, Harbin, China

    Topic: Magnetic Resonance Imaging of Prenatal Fetal Cystic Lesions of the Brain

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    2024 8th International Conference on Health, Medicine and Life Sciences

    Jun. 1-2, 2024

    Magnetic resonance imaging (MRI) has the ability to display the fetal brain and distinguish its different tissues, making it a potential diagnostic, research, and screening tool for brain development. In mid pregnancy, MRI is used to screen fetuses at risk of brain abnormalities. Fetal brain MRI is a safe and effective auxiliary tool in prenatal diagnosis. Purpose: This study investigated the magnetic resonance imaging features of prenatal fetal brain cystic lesions using single shot fast spin echo sequence (SSFSE) and diffusion weighted imaging (DWI). Result: Currently, 37 cases of fetal cystic lesions in pregnant women have been collected as the research subjects. The age range of pregnant women is 29.3 years old, with a healthy pregnancy period and a gestational age of 31.4 weeks. 37 cases of fetal cystic lesions in pregnant women, including 13 cases of arachnoid cysts; There were 12 cases of subventricular cysts, 3 cases of perforating malformation cysts, 2 cases of transparent septal cysts, 3 cases of intraventricular cysts, and 2 cases of Dandy Walker disease. Arachnoid cysts and subependymal cysts are the most common, with cystic long T1 and T2 signals. DWI images show low signal intensity, clear edges, and uniform internal signals. The signals of 37 cases of cystic lesions are the same as those of cerebrospinal fluid. Conclusion: Single shot fast spin echo sequence (SSFSE) has a fast imaging speed, enhanced signals in water containing tissues, attenuated signals in soft tissues, short acquisition time, and fewer fetal motion artifacts. Magnetic resonance diffusion-weighted imaging (DWI) has its advantages in diagnosing cystic lesions, especially in providing a signal ratio of water molecule diffusion, distinguishing the components of cysts, and helping clinical judgment of their properties, providing imaging evidence for subsequent diagnosis and treatment.

    Assoc. Prof. Kai Zhu, Master's Supervisor, graduated from Harbin Medical University, working in the Imaging Department of Heilongjiang Hospital, Beijing Children's Hospital Affiliated to Capital Medical University. Member of the provincial leading talent team, skilled in fetal and child magnetic resonance functional imaging. I have delivered multiple speeches at the Radiology Academic Conference of the Chinese Medical Association, and the first author has published 10 papers and 2 monographs; Hosted and participated in 5 projects; Received 25 provincial science and technology progress awards, medical and health science and technology progress awards, and new technology application awards; Member of the Youth Committee of the Radiology Professional Committee of the Heilongjiang Medical Association, Standing Committee Member of the Radiology Professional Committee of the Heilongjiang Medical Promotion Association, Member of the Imaging Branch of the Heilongjiang Society of Traditional Chinese Medicine, Director of the Imaging Diagnostic Physician Branch of the Harbin Medical Association, and Reviewer of the Journal of Magnetic Resonance Imaging.

  • Dr. Ting Wei, Associate Professor

    School of Physical Education, Inner Mongolia University, Hohhot, China

    Topic: Research Progress of Skeletal Muscle Electromyography Technology in the Field of Sports Medicine

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    2024 8th International Conference on Health, Medicine and Life Sciences

    Jun. 1-2, 2024

    With the leap of skeletal muscle surface electromyography technology, the advantage of observing the activity characteristics of motor units through skeletal muscle surface electromyography technology has become a core issue in academia. In order to grasp the accuracy and research progress of skeletal muscle electromyography technology, the research results show that skeletal muscle electromyography technology is mainly used to study neuromuscular recruitment characteristics, which can predict muscle strength and recognize movements; Single joint muscle strength training can induce a decrease in motor unit recruitment threshold and an increase in discharge frequency, resulting in an increase in muscle strength; Meat control function; Muscle fatigue induced by exercise leads to a decrease in the discharge frequency of the motor unit, altering the relationship between recruitment threshold and discharge frequency, recruitment threshold and exit threshold, as well as the balance and excitability of the motor unit's activity in different electromyographic frequency bands.

    Dr. Ting Wei is an associate professor at the School of Physical Education of Inner Mongolia University. She received a Ph.D degree from Beijing Sport University in 2020 and was selected for the Inner Mongolia Autonomous Region Talent Project. She is the director of the laboratory at the School of Physical Education of Inner Mongolia University, the secretary of the Party branch of faculty and staff, a mentor of the National College Student Innovation and Entrepreneurship Competition, and a graduation thesis review expert. Published over 60 papers in core journals, sports special issues, and important academic conferences both domestically and internationally.

  • Dr. Weihong He, Associate Professor

    Department of Physiology, West China School of Basic Medical Sciences and Forensic Medicine, Sichuan University, Chengdu, China

    Topic: Inhibiting RUNX1 Leads to Reduced Infarct Size and Repressed Cardiac Cathepsin Levels Following Acute Myocardial Infarction

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    2024 8th International Conference on Health, Medicine and Life Sciences

    Jun. 1-2, 2024

    Acute myocardial infarction (MI) is a leading cause of death worldwide. Acute MI results in prolonged myocardial ischemia and the subsequent cell death leads to heart failure which is linked with increased deaths or hospitalizations. Cathepsins are lysosomal proteases involved in protein degradation and can also be secreted into extracellular spaces. Recent evidence has shown that cardiac release of a subtype of cathepsin (cathepsin-L) in MI patients leads to elevated serum cathepsin-L levels which are associated with reduced cardiac function and increased infarct size. However, the mechanism of the increased cathepsin-L level is unknown. Runt-related transcription factor-1 (RUNX1) is a master-regulator transcription factor, which is implicated in the transcriptional regulation of gene expression. Recent evidence demonstrated that RUNX1 plays a critical role in the heart after MI. This work sought to investigate whether inhibition of RUNX1 affects cathepsin levels in a rat MI model. MI was surgically induced by performing coronary artery ligation. Heart samples were taken at 24 hours post-MI and analyzed by LC-MS/MS operating in the data-independent acquisition (DIA) mode. We found that overall cathepsin levels were increased in control hearts after MI. In contrast, rats treated with RUNX1 inhibitors demonstrated decreased cathepsin levels. Furthermore, RUNX1 inhibition led to a reduced infarct size at 24 hours post-MI as determined through 2,3,5-triphenyltetrazolium chloride (TTC) staining. These results are in line with Dr. He’s previous study performed in isolated rat hearts which demonstrates that inhibition of cathepsin-L reduces infarct size and improves cardiac function ex vivo. The present study shows that inhibition of RUNX1 after acute MI can also reduce infarct size in rat hearts in vivo and the beneficial effects may be achieved by repressed cathepsin levels, thus suggesting the translational potential of RUNX1 and cathepsins as therapeutic targets of cardiac protection against acute MI.

    Dr. Weihong He is a principal investigator and Associate Professor at the Department of Physiology, West China School of Basic Medical Sciences and Forensic Medicine, Sichuan University. Dr. Weihong He obtained an MD (2012) at West China School of Medicine & West China Hospital, Sichuan University, and completed a PhD (2017) at the BHF Glasgow Cardiovascular Research Centre, University of Glasgow. He was an associate professor at Jining Medical University (2018-2020). Since 2020, he has led a research group to study the pathophysiology of cardiovascular diseases and to investigate novel therapeutic drugs for myocardial infarction and cerebral infarction at Sichuan University. He also teaches physiology and mentors both national and international students. He has expertise in many methodologies which span the level of biochemistry, cell biology, isolated heart, and whole animal in vivo disease models.

  • Dr. Dongyang Jiang, Research Professor

    School of Medicine, Tongji University, Shanghai, China

    Topic: Multifaceted Roles of PHACTR1 in Atherosclerosis

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    2024 9th International Conference on Biology and Life Sciences

    Jun. 1-2, 2024

    Although compelling evidence suggested the strong association of phosphatase and actin regulator 1 (PHACTR1) with atherosclerosis, the biological function of PHACTR1 remains poorly understood. Macrophage PHACTR1 was demonstrated to be protective by facilitating efferocytosis and attenuating atherosclerotic plaque necrosis. Our group identified the pro-atherosclerotic effect of endothelial PHACTR1, contrary to macrophage PHACTR1. Global or endothelial cell (EC)-specific PHACTR1 deficiency significantly inhibited atherosclerosis in regions of disturbed flow. PHACTR1 was enriched in ECs and located in the nucleus of disturbed flow area but shuttled to cytoplasm under laminar flow in vitro. RNA-seq using EC-enriched RNA showed that Phactr1 depletion affected vascular function and peroxisome proliferator-activated receptor gamma (PPARγ) was the top transcription factor regulating differentially expressed genes. PHACTR1 functioned as a PPARγ transcriptional corepressor by binding to PPARγ through the corepressor motifs. PPARγ activation protects against atherosclerosis by inhibiting endothelial activation. Consistently, PHACTR1 deficiency remarkably reduced endothelial activation. PPARγ antagonist GW9662 abolished the effects of Phactr1 knockout on EC activation and atherosclerosis. Targeting the interaction of PHACTR1 and PPARγ will provide a promising therapeutic strategy for atherosclerosis.

    Dr. Dongyang Jiang is a research professor at Department of Cardiology, Pan-vascular Research Institute, Shanghai Tenth People's Hospital, Tongji University School of Medicine. She earned her bachelor's (basic medical science) and doctoral (immunology) degrees at Peking University and then joined Tongji University in 2014. She is the principal investigator for general and youth projects of the National Natural Science Foundation of China, a general project of the China Postdoctoral Science Foundation and a project of the Shanghai Science and Technology Committee. She also serves as the member of the Chinese Society of Immunology (CSI), the Chinese Society of Biochemistry and Molecular Biology (CSBMB), and the American Heart Association (AHA). Her research focuses on the molecular mechanisms of dynamic regulation of the endothelial barrier, exploring the roles in cardiovascular diseases such as atherosclerosis, abdominal aortic aneurysm, and pulmonary arterial hypertension. Her team recently discovered a novel mechanosensitive molecule in atherosclerosis, PHACTR1. She has published 15 research articles in scholarly journals including ATVB, Hypertension, Cancer Letters, and the British Journal of Pharmacology. She has been honored with awards such as AHA Young Scientist Travel Award and CSBMB Young Scientist Award.

  • Dr. Jun Liu, Professor

    School of Mechanical and Electrical Engineering, Southwest Petroleum University, Chengdu, China

    Topic: Failure Forms and Safety Evaluation Methods of Downhole Tools in Horizontal Well Development

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    2024 8th International Conference on Energy, Environment and Resources

    Jun. 1-2, 2024

    Horizontal well is a development technology that increases oil well production and enhances the economic benefits of oilfield development by expanding the drainage area of the oil reservoir. More and more oil&gas fields are being developed horizontally. The integrity of downhole tools, including tubing and casing, is a prerequisite for achieving horizontal well development. Due to the influence of complex wellbore structures and complex mining conditions such as faults, high temperature and pressure, the mechanical condition of the tubing and tools during drilling, completion, and production is relatively poor, and the failure mechanism is complex. In the speech, we introduce the failure forms, research progress, and urgent problems of pipe columns and downhole tools in horizontal well development.

    Dr. Jun Liu graduated with a doctoral degree in Engineering Mechanics from Chongqing University in 2011. He is currently engaged in teaching and research work in the Department of Mechanical Engineering at Southwest Petroleum University, with a research interest in mechanical analysis and safety evaluation of oil and gas well tubing. He has published over 40 SCI papers, 2 monographs, 18 authorized invention patents, and more than 10 provincial and ministerial level scientific research awards.

  • Dr. Qiming Huang, Associate Professor

    College of Safety and Environmental Engineering, Shandong University of Science and Technology, Qingdao, China

    Topic: Key Technologies for Dust Reduction at the Source of Deep Coal Seam Water Injection with Strong Permeability and Increased Lubrication

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    2024 8th International Conference on Energy, Environment and Resources

    Jun. 1-2, 2024

    Coal, as a fundamental energy and industrial raw material in China, has long provided strong support for economic and social development. However, the coal mining industry is also a high-risk industry with frequent accidents. The 14th Five Year Plan for Mine Safety Production emphasizes that coal mine production should adhere to safe development, source control, and precise prevention and control. Coal seam water injection is an effective technical means to achieve the source control of dust disasters. However, compared to Western coal producing countries such as the United States and Australia, China's coal seam permeability is generally low, which seriously restricts the effectiveness of coal seam hydraulic disaster prevention. Traditional coal seam water injection technology cannot effectively solve such problems, and it is necessary to develop efficient, accurate, and reliable key technologies for coal seam hydraulic disaster prevention. In response to the engineering problems of poor permeability and difficulty in water injection in deep coal seams in China, the principle of "automation and integration" was first integrated into the research and development of dust reduction technology and equipment at the source of low-permeability water injection. Based on a large amount of laboratory testing and on-site industrial test data, a key parameter optimization algorithm for strong permeability and increased lubrication in deep coal seams was established. Based on the physical and chemical properties of low-permeability coal seams, a series of materials for clean and composite efficiency enhancement of coal seam water injection were developed from two aspects: crack structure transformation and interface wetting optimization. By combining hydraulic slotting with high-pressure water injection technology, a key technology of hydraulic strong infiltration and lubrication integration has been proposed, forming a systematic analysis and judgment method for key technical parameters. A coal seam hydraulic strong infiltration and lubrication integration technology equipment has been developed and successfully applied in coal seam water injection dust reduction projects in typical disaster mining areas in China.

    Dr. Qiming Huang is an associate professor at Shandong University of Science and Technology, serving as the scientific editor of the Journal of Coal (English version) and a young editorial board member of Coal Geology and Exploration and Metal Mines. Hosted one National Natural Science Foundation Youth Fund project, one China Postdoctoral Science Foundation general funding project, one Shandong Province Postdoctoral Innovation project, one open project of the Key Laboratory of Industrial Dust Prevention and Occupational Safety and Health Education of the Ministry of Education, and four horizontal projects commissioned by enterprises. In the past 5 years, he has published 20 SCI papers as the first or corresponding author, and has been granted 12 invention patents and 5 utility model patents for the first time; The first published monograph titled "The Mechanism of Influence of Water-based Fracturing Fluid on Coalbed Methane Flow". The research work has won the second prize of Chongqing Science and Technology Progress Award and the first prize of China Occupational Safety and Health Association Science and Technology Award.

  • Dr. Shunli Wang, Professor

    School of Electric Power, Inner Mongolia University of Technology, Hohhot, China; Smart Energy Storage Institute, China

    Topic: Core State Factor Monitoring of Smart Energy Storage Systems

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    2024 8th International Conference on Energy, Environment and Resources

    Jun. 1-2, 2024

    As an important component of the smart grid energy storage system, high-precision state of health estimation of lithium-ion batteries is crucial for ensuring the power quality and supply capacity of the smart grid. To achieve this goal, an improved integrated algorithm based on multiple layer kernel extreme learning machine and genetic particle swarm optimization algorithm is proposed to estimate the SOH of Lithium-ion batteries. Kernel function parameters are used to simulate the update of particle position and speed, and genetic algorithm is introduced to select, cross and mutate particles. The improved particle swarm optimization is used to optimize the extreme value to improve prediction accuracy and model stability. The cycle data of different specifications of LIB units are processed to construct the traditional high-dimensional health feature dataset and the low-dimensional fusion feature dataset, and each version of ML-ELM network is trained and tested separately. The numerical analysis of the prediction results shows that the root mean square error of the comprehensive algorithm for SOH estimation is controlled within 0.66%. The results of the multi-indicator comparison show that the proposed algorithm can track the true value stably and accurately with satisfactory high accuracy and strong robustness, providing guarantees for the efficient and stable operation of the smart grid.

    Dr. Shunli Wang is a Professor, Doctoral Supervisor, Executive Vice President of Smart Energy Storage Institute, Academic Dean of Electric Power College at Inner Mongolia University of Technology, Academician of Russian Academy of Natural Sciences, IET Fellow, Provincial Senior Overseas Talent, Academic Leader of the National Electrical Safety and Quality Testing Center, Tianfu Qingcheng Provincial Scientific and Technological Talent, Academic and Technical Leader of China Science and Technology City, Top 2% Worldwide Scientist. His research interests include modeling, state estimation, and safety management for energy storage systems. 56 projects have been undertaken, supported by National Natural Science Foundation of China and the Provincial Science and Technology Department et al. 258 research papers have been published with RIS value of 11617 and h-index value of 29. 52 intellectual property rights have been approved. 9 monographs have been published by famous publishers of Elsevier and IET and so on. The total print number of New Energy Technology and Power Management reaches 6300 copies that are reprinted 4 times. He has guided students on 29 science and technology innovation projects with 6 excellent completion and 34 awards in science and technology competitions. He has won 13 scientific and technological awards, including the Gold Award at the 48th Geneva Invention Exhibition.

  • Dr. Xueyong Tian, Professor

    School of Environmental and Chemical Engineering, Shenyang University of Technology, Shenyang, China

    Topic: Modeling and Optimization of Wastewater Treatment Process Based on Artificial Intelligence Technology

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    2024 8th International Conference on Energy, Environment and Resources

    Jun. 1-2, 2024

    With the development of the economy and the deepening and strict requirements of the dual carbon goals, new technological challenges have been proposed for sewage treatment processes and processes. This requires the combination of new technologies and methods in sewage treatment processes to expand both theory and application. The rapid development of artificial intelligence technology has brought new growth momentum to the field of water treatment. The sewage treatment process involves complex chemical, physical, and biochemical processes, making it difficult to establish accurate mathematical models. The traditional ASM model series applied to activated sludge processes is an approximate model under many constraints, and its scope of use is limited. The widely used membrane technology lacks relevant model-based analysis. Many key parameters and indicators in the sewage treatment process lack real-time and accurate measurement techniques, resulting in delayed measurement data and affecting precise process control. Artificial intelligence technology can utilize historical, real-time data, and other algorithms such as machine learning, neural networks, and deep learning to achieve process modeling, soft measurement of key parameters and indicators, process control, and optimization of many sewage treatment processes, thereby helping to solve new challenges encountered in sewage treatment.

    Dr. Xueyong Tian was born in Linyi, Shandong Province, China in 1979. He received the Ph.D. degree in 2011. He is currently a professor and the director of the Institute of Intelligent Environmental Protection Technology at Shenyang University of Technology, member of the Environmental Perception and Protection Automation Professional Committee of the Chinese Society of Automation. He has led sub projects of the National Key R&D Program, key R&D projects in Liaoning Province, and key scientific and technological research projects in Liaoning Province, and has led more than ten achievement transformation projects. He has participated in more than ten major projects, including the National 973 Project, the National 863 Project, and the Military Key Equipment Reform and Promotion Project. He has published more than 30 papers and obtained more than 20 patents and software copyrights.

  • Dr. Weiwei Wu, Professor

    School of Management, Harbin Institute of Technology, Harbin, China

    Topic: How Do Latecomer Firms Achieve Catch-up Through Technology Management: A Comparative Analysis

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    2024 7th International Conference on Innovation Management and Entrepreneurship

    May 31-Jun. 1, 2024

    The catch-up of latecomer firms has been a topic of interest because it is closely related to the changes in industry leadership. The reason why some countries are more successful in catch-up is because of their increasing mastery of technology management (TM). Therefore, to ensure successful catch-up, it is imperative for latecomer firms to understand the TM practices and TM modes across national boundaries. This paper aims to reveal the differences in TM practices and TM modes between latecomer firms and forerunner firms. This paper collected data from Chinese firms and Korean firms as latecomers and forerunners, respectively, to examine the differences in TM practices and TM modes. The results show that latecomer firms place more emphasis on grasping the condition of firms’ equipment, understanding technology talents required by business, and completing files on technology information. While forerunner firms stress learning from other competitors, effective training, and constructing detailed technology information management system most. Furthermore, the relationship between TM and product innovation performance is more integrated for forerunner firms compared to latecomer firms. A key contribution of this paper is to reveal the differences in TM practices and TM modes between latecomer firms and forerunner firms, which enriches the catch-up literature from an international comparative perspective. As such, this paper is of great importance in broadening the understanding of how latecomer firms transform into global leaders.

    Dr. Weiwei Wu is a Professor at Harbin Institute of Technology, China, where he received his Ph.D, master’s and bachelor’s degrees in management. He was a SPURS (Special Program for Urban and Regional Studies) fellow from 2011 to 2012 at Massachusetts Institute of Technology, USA, and served as the consultant of Asian Development Bank (ADB) from 2021 to 2024. His research focuses on technology management and technological innovation. His research has been supported by the National Natural Science Foundation of China, National Social Science Foundation of China, Ministry of Education of China and etc. He has published more than 100 articles in journals, including Information & Management, Journal of Manufacturing Technology Management, Telematics and Informatics, Journal of Knowledge Management, among others. He serves as the Associate Editor of Journal of Management Science. He is the Council Member of Chinese Society of Technology Economics, and the Founding Member of Asia Entrepreneurship Education Association.

  • Dr. Jian Chen, Associate Professor

    Belt and Road School, Beijing Normal University, Beijing, China

    Topic: Analysis on China’s Investment Distribution and Risk Prevention of "the Belt and Road" Countries

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    2024 8th International Conference on Economics, Finance and Management Science

    May 31-Jun. 1, 2024

    The study first analyzes the necessity of country risk assessment for "the Belt and Road" investment. Then the author presents the investment distribution characteristics of "the Belt and Road" countries, thus builds up "the Belt and Road" investment country risk evaluation index system with 5 dimensions and 25 indicators and Evaluation model. At last, the authors concludes with some dynamic characteristics of national investment and risk prevention strategies.

    Dr. Jian Chen is an Associate Professor at Belt and Road School, and International Business Faculty, Beijing Normal University, Visiting Scholar at De Montfort University (UK) Business School(2004), Visiting Scholar at Gloucestershire University (UK) (2006.9-2007,2), Visiting Scholar(2016.3-2017.3) supported by the Chinese National Scholarship Council(CSC), Research Fellow in the Institute of Energy and Sustainable Development and the School of Business and Law, De Montfort University (UK). She received her doctorate degree in Management from Huazhong Agricultural University and her master degree from Wuhan University. She has participated in 4 international projects, 8 provincial projects, chaired 10 city projects, 7 school-level projects; 1 social science project in Hubei Province, and 2nd excellent economic and social development research project in Meizhou City Awards, Guangdong Province, presided over the University’s Teaching Quality Project of the school-level by the courses of: "Organizational Behavior", "Principles of Management", "Enterprise Strategic Management". She has published 91 academic papers, including 3SCI journals,4 CSSCI journals, 3 ISTP papers, and 4 core journals of CSTPCD, with 2 works, 1 textbook, and 3 joints.

  • Dr. Peiwen Bai, Professor

    School of Economics, Xiamen University, Xiamen, China

    Topic: Digital Economy Development and Markup of Firm

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    2024 8th International Conference on Economics, Finance and Management Science

    May 31-Jun. 1, 2024

    The integration of the digital economy with the real economy is a major issue for sustainable economic development in the new era. A large amount of economics literature focuses on the benefits of digital economy, such as increased productivity, increased innovation and improved organizational structure of firms. However, little literature has explored the costs of digital economy development to firms, such as increased competition and rising cost pressures. In this paper, we use the markup of firms as a combined reflection of the net value of these two effects, and theoretically construct a variable markup model to explore the mechanism. Further, this paper uses data on Chinese industrial firms from 2004-2013, combined with the newly developed imperfect instrumental variables method. It is found that digital economy development significantly reduces markup of firms, with a robust upper bound of -0.31%. The analysis of the mechanism reveals that the increase in competition among firms and the imperfect transfer of cost pressures by firms are important channels. The heterogeneity analysis shows that the negative impact of digital economy development on markup is larger for firms with characteristics such as less digitalization, tighter financing constraints, and weaker cost-saving capabilities. The study also finds that digital economy development reduces the dispersion of markup and significantly improves the efficiency of resource allocation. The findings of this paper have important implications for understanding the significance of digital economy and real economy integration, and how to further promote digital economy development effectively.

    Dr. Peiwen Bai currently works as a professor and doctoral supervisor at the School of Economics of Xiamen University, deputy director of the Economic Research Institute, deputy editor of "China Economic Issues", visiting scholar at Monash University, chief expert of major projects of the National Social Science Fund, and vice president of the Fujian Economic Association. He received a doctorate in management from Shanghai Jiao Tong University in 2006. His research areas are the digital economy and income distribution. He has published over 80 papers as first author in domestic and foreign journals. He has participated in and chaired research on multiple projects, including the National Social Science Fund Major Project and the Ministry of Education Major Project.

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