During the transition from industrial production to intelligent, there are still a large number of manufacturing industries in the traditional production mode. The problems of slow information transmission, difficult integrated production management, and complicated process parameter control have led to disconnect decision-making from actual production. In addition, the current manufacturing industry is more of a traditional management method, and the upgrade and iteration speed are slow, and it is not combined with the technology of the Internet of Things. Therefore, the purpose of this article is to use the Internet of Things monitoring technology to explore the improvement of high-end manufacturing and analyze the problems and solutions in the process of consistency of ecological environment and economic effects. This article will use the research methods of specific problems and specific analysis to compare the data and draw conclusions. This article will discuss the technical mechanism of the Internet of Things monitoring and introduce the collection and data of production status data of each station equipment in the production workshop during the production process: improving the current production model, learning foreign experience at the same time, quickly carrying out load curve and data center data accumulation on the service capabilities of the park, verifying multiple operating models, and simultaneously exploring new management models. Based on comparative advantage analysis, the study draws similarities and differences in the development of high-end manufacturing industries at home and abroad, learns advanced experience, proposes improved methods and paths, combines new environmental protection paths, and finally proposes energy operation in the park. Build a green and intelligent park to provide a theoretical reference for sustainable development. The research results show that computer monitoring technology and methods have effectively improved the production environment of high-end manufacturing, combined with the development status of the existing ecological and intelligent composite production system; the infrastructure construction of industrial parks in the new era, IT support, services, manpower resources, and industries has developed rapidly. With the fast grow and in-depth use of new information technology like Internet of things, Internet plus, and AI, people's quality of production and life has been greatly improved, which not only promotes the economic development but also provides technical support for the transformation and upgrading of the economic structure. The current smart parks also focus more on smart logistics and IOT construction but lack quality monitoring and supervision. In order to better elevate the green and high-quality development of manufacturing industry, it is necessary to establish a complete monitoring system. In the organizational structure of the monitoring system in the green smart park, monitoring nodes are arranged according to the actual monitoring needs to ensure that the monitoring of the environment in the area and the collection of data and information can be met. It has made great contribution to the sustainable development of high-end manufacturing green smart park.In the development process of high-end manufacturing industry, smart park has become a new trend and new requirement for the development of industrial park. With the promotion of comprehensive national strength, we are improving our quality of life step by step. But at the same time, we cannot damage the ecological environment , 2. GeneSince the 1950s, researchers in developed countries and regions have carried out a variety of targeted scientific research experiments on industrial park monitoring and environmental quality improvement . ResearcStarting from the meaning and traits of the Internet of Things, this paper explores the sustainable development of high-end manufacturing green smart park, expounds the environmental problems brought by the current economic production and construction, mainly existing problems of the industrial park, finds out the reasonable solutions and the balance basis point in line with the monitoring characteristics, and organically combines the two. In the research, the application of the Internet of Things technology to the intelligent monitoring of the park enables the high-end manufacturing industry in the intelligent industrial park to operate more greenly and efficiently. This paper will discuss the mechanism of the monitoring technology and introduce the collection and implementation of the production status data of each station equipment in the production workshop during the production process. Improve the current production mode, learn from foreign experience, quickly carry out the data accumulation of load curve and data center's service ability to the park, verify various operation modes, and simultaneously explore new management mode. Through comparative advantage analysis, this paper studies the similarities and differences in the development of high-end manufacturing industry both at home and abroad, studies advanced experience, puts forward improvement methods and paths, combines the new path of environmental protection, and finally puts forward the experience accumulated based on this mode to explore the optimal mode of energy operation and management in the park, build a green smart park, and provide theoretical reference for sustainable development.Internet of Things refers to the use of a variety of information collection terminals and information collection technology to obtain all kinds of information needed by the system and through the Internet and other carriers to upload these information data to the processing center for centralized analysis and processing, to get the corresponding results and make reasonable regulatory decisions based on them, and finally to transmit the control instructions to each terminal equipment to achieve intelligent control system. Through radio frequency identification technology and intelligent perception technology, data collection of all elements of the factory workshop, including workers, equipment, materials, and environment, is completed. According to the on-site situation, an appropriate networking mode is formulated, and the information of each station scattered in the workshop is collected and aggregated to the upper computer for processing, so as to realize the monitoring and automatic management of industrial production. In the production supervision of many production workshops, they are often faced with complex working conditions and excessive environmental interference. These environmental factors, as well as the operation status and parameter data of equipment, are the key factors affecting product quality. The use and popularization technology can achieve intelligent scheduling by setting up multiple sensor nodes to collect and supervise the data of idle and working state of the equipment and improve the utilization rate of the equipment; meanwhile, it can also collect the parameter data of the temperature and speed during the operation of the production equipment that will affect the product quality in real time, based on which the production process, and adjust and control the parameters to improve the production efficiency.A sensor refers to a measuring device that can convert the measured nonelectrical quantity into a corresponding quantity of electricity or an electrical parameter output that is easy to handle accurately according to a certain law. According to its basic sensing function, it can be divided into ten categories: heat sensitive element, light sensitive element, gas sensitive element, force sensitive element, magnetic sensitive element, humidity sensitive element, sound sensitive element, radiation sensitive element, color sensitive element, and taste sensitive element. In order to obtain information from the outside world, people must rely on the sense organs. However, people's sense organs alone are not enough to study the natural phenomena, laws, and production activities.Data acquisition refers to the process of automatic acquisition of nonelectricity or electricity signals from intelligent acquisition equipment, such as all kinds of sensors and other devices to be tested and other analog or digital units to be tested. Data collection is the combination and interaction of information technology and physical level. The traditional data collection method is very single. From the initial manual input, equipment supervision, and other manual operation methods to the later development of data collection using collection devices, the low efficiency of the process has been restricting the industrial production. Up to now, the production demand is growing day by day, and the amount of data in production is huge, which brings great difficulties for data collection and data specification and cleaning after it; at the same time, the protocol of industrial data is not standard, including Modbus, OPC, can, control net, PROFIBUS, ZigBee, and other types of industrial protocols, which leads to great difficulties in the interconnection of industrial protocols. The emergence of technology brings great innovation to the methods of data collection, processing, and analysis.In different periods and at different levels of social and technological development, the specific manifestations of high-end manufacturing industry are different. The difference in high-end manufacturing is mainly reflected in the way and method of manufacturing, and with the high-end manufacturing, pollution will gradually decrease. Every great change in the field of science and technology has led to a leap in the quality of manufacturing industry: during the first industrial revolution, “high-end manufacturing” means mechanical manufacturing instead of manual manufacturing; during the electrification revolution, large-scale production activities appear and become increasingly mature; “high-end manufacturing” represents the production of electrification and automation; with the popularization and application of computer technology, the production is gradually intelligent and large scale. The advantage of “informatization” is outstanding, which represents the “high-end” manufacturing mode in the new era. From the industrial point of view, the manufacturing industry that is emerging or is likely to develop into an emerging industry, with high technology content, high-added value, and strong market competitiveness of finished products, is defined as high-end manufacturing industry, which is often referred to as “new energy” and “new material” industry. For example, there are “new energy” industries, such as solar photovoltaic industry, marine wind power, and lithium-ion energy storage battery manufacturing, and “new material” industries, such as nanobiomaterials, high-performance carbon fiber composite materials, and additive printing technology.n iterations, each training set is classified by a classification algorithm, and the classification error rate isωiI is the weight of the ith sample and Gn is the nth classifier.In the process of monitoring the production status, understanding the production data, comparing with the green standard, gradient lifting tree is one of the excellent methods, which has been widely concerned and applied in industry and other fields. In this paper, the gradient boosting tree algorithm is used to perform deep learning on the monitored video to convert the monitored production status into visual data. In this paper, XGBoost is used as the research method of extreme gradient enhanced tree computing. Based on GBDT, parallel processing is used, and it has high scalability. According to the previous description, boosting, as an efficient algorithm of integrated learning, can adjust the weight of the learning machine according to its performance in the training process, realize the enhancement of weak learning machine, and improve the accuracy of classification. The process is as follows: (1) all training sets are given the same weight; (2) after After the iteration, all the classifiers are obtained. From the above steps, it can be seen the classification error samples, whose weight will become higher, in order to optimize the next iteration effect. Finally, the sample is obtained by voting classification results. It is proved by experiments that the loss function of boosting is in exponential form, and the gradient lifting decision tree is to make the loss function drop along the gradient direction in the iteration.So as to improve the classification accuracy, XGBoost is the optimal implementation of the algorithm. XGBoost model integrates multiple classification regression cart tree models, which are constructed according to different characteristics, and the value of the leaf node of the tree represents the importance of the characteristics. The expression of XGBoost model can be given:K in the expression refers to the number of cart tree models, yi refers to the predicted value of a single tree, xi refers to the ith input sample, and F refers to the total set of all cart trees with probability in training. XGBoost algorithm does not need to give all the sets of trees but uses gradient lifting method to add a new tree model each time and constantly improves the previous results.Five indicators will be selected, including total industrial output value, number of enterprises, main business income, average number of employees, and production capacity of main products. Among them, the total industrial output value is expressed in the form of currency. The total value of the final products or labor services provided by an enterprise in a certain period of time reflects the total scale and level of production in a certain period of time. The production capacity of main products refers to the core design and manufacturing, application equipment manufacturing, software development and application, system integration, and network operation. The annual production capacity of the five links, such as information service, can be expressed in terms of output value.Five indicators will be selected, including total profit and tax, industrial added value rate, product sales rate, total asset contribution rate, and total labor productivity. Among them, the total profit and tax is an indicator that counts the total profit and tax of the enterprise, which reflects the total profit realized by the enterprise in the quantitative indicator that undertakes the obligation to the region; the industrial added value rate refers to the proportion of industrial added value in the total industrial output value in a certain period of time, reflects the economic indicator that reduces the intermediate consumption, and is also the Internet of Things industry core indicators of development; product sales rate refers to the ratio of sales output value in the reporting period to total industrial output value in the same period, which reflects the extent to which industrial products have been sold and is an important indicator to analyze the balance of production and demand in the Internet of Things industry; total asset contribution rate reflects the relative indicators of the output of total assets of enterprises, reflects the profitability of all assets of enterprises, and evaluates industrial benefit core indicators. The total labor productivity is the comprehensive performance of the production technology level, management level, technical proficiency, and labor enthusiasm of the enterprise, and it is also an important index to assess the industrial efficiency.Five indicators will be selected, including R&D expenditure, number of Internet of Things standards, number of patent applications, number of important research results, and sales revenue of new products. Among them, R&D expenditure refers to all kinds of direct and indirect expenses incurred by enterprises in the research and development process of products, technologies, materials, processes, and standards; the number of important research results refers to the number of key technologies that are conquered and recognized by the state in the fields of perception, transmission, processing, application, and other technologies; the new products refer to the research results that are obtained through technological innovation. The product has a breakthrough in one aspect or obvious improvement compared with the original product, thus significantly improving the product performance or expanding the use function, which has a certain part in boosting the economic efficiency of the product and is conducive to the sustainable development of the city's industry.Five indicators will be selected, including the number of application projects, the number of public service platforms, the number of industrial clusters, the number of key enterprises, and the number of international cooperation. Among them, nonstandard application projects, public service platforms, industrial clusters, and backbone enterprises are all general, standard, independent and controllable application platforms, Internet of Things public service platforms, Internet of Things industrial clusters, and backbone enterprises recognized by the state; international cooperation refers to the establishment of R&D institutions in China and joint R&D and establishment abroad by overseas enterprises and scientific research institutions R&D institutions; this index helps to enhance the international competitiveness of Wuxi Internet of Things industry.In the experiment of this paper, firstly, the industrial equipment is screened, and the appropriate type of factory equipment is selected, and then, the Internet of Things technology is used to arrange the intelligent monitoring equipment in the factory park. Finally, the intelligent monitoring system is tested.24 V industrial switching power supply, PLC, temperature and humidity meter, electric energy meter, temperature control meter, pulse generator, Modbus gateway, wire, and other materials are shown in Assemble the unit data acquisition module, input the PLC's own program, set the slave station address and communication parameters  for each instrument connected to 485 bus, check the circuit and power supply safety, and prepare for the subsequent test. As a comprehensive data acquisition and processing module, PLC is an important test object. Firstly, the signal acquisition function and serial communication function of PLC will be tested, and all kinds of instruments will be connected to the corresponding interfaces of PLC , and then, PLC will be connected through 485 to USB data line direct serial communication with the testing machine computer and data reading and displayed through Modbus poll debugging software. Finally, the test function interface is written through the configuration software, and the data table is read and displayed. The data acquisition and monitoring experiment of the monitoring meter have been completed successfully. The test methods of the temperature inspection instrument, the electric energy meter, and the pulse signal generator are consistent with the above process. After the server and configuration software of the machine room are built, the monitoring screen is projected to the central screen through the remote desktop, so as to realize the production in the workshop site and facilitate the timely supervision and control of the production management personnel.With the widespread use of the Internet, the structural transformation and development of high-end manufacturing industry also need to be improved. Industrial production began to face a series of diversified challenges; the traditional production technology and information management have been unable to meet its development needs. What changed was the birth of diversified integration of the industry, “smart factory,” “smart manufacturing,” and other concepts came out. In this field, centering on intelligent manufacturing, it integrates many technologies such as industrial automation, intelligent logistics, industrial big data platform, and industrial Internet of Things, making manufacturing gradually replaces new blood. Among them, data visualization is very important. Due to the high integration of industrialization and information technology, information technology provides a variety of ways for data collection, such as bar code, two-dimensional code, RFID, industrial sensors, automatic control system, and other technologies that have been fully applied. Through the combination of RF technology and industrial sensors, the data acquisition system covering the whole production system equipment can be realized. At the same time, it is hard to manage a lot of production data only by manpower. Therefore, it is very important to realize data visualization, data centralization, and intelligent control. The intelligent system planning and design of the smart park should take the construction of green buildings and the park as the goal, to achieve functional practicality, timely technology, safety and efficiency, standardized operation, and economic rationality. The intelligent construction planning and design of the park shall be carried out in strict accordance with the building function, building equipment management, building environment management, etc., and the concept of the intelligent park. The planning and design of intelligent monitoring system engineering can know the production status and change the production mode at any time. The intelligent system planning and design of the intelligent park is based on the building and its landscape as the platform, based on the integrated application of various intelligent information, integrating architecture, system, application, management, and optimization, with the integrated intelligent ability of perception, transmission, memory, reasoning, judgment, and decision-making, and providing the park people with a safe, efficient, convenient, and sustainable development function ring environment.Motor parameter acquisition subsystem is the basic measurement unit of the whole motor monitoring system, which is mainly composed of STM32 controller, temperature sensor, voltage, current, vibration sensor, hall speed sensor, LoRa wireless data transmission module, and TFT display interface. Complete the real-time and accurate measurement of the field motor parameters, and transmit the data to the relay data transmission subsystem through the LoRa wireless module, so as to realize the concentration of multiple motor operation parameters. As shown in The relay data transmission subsystem is the intermediate node of the whole motor condition monitoring system to realize the remote transmission and monitoring of motor data. It is mainly composed of STM32 controller, LoRa wireless data receiving module, and Nb IOT wireless Internet of Things module. Through LoRa wireless module, the wireless local area network function of multiple parameter acquisition subsystems on site is completed, and the data of multiple motor equipment on site is centralized. Then, through the Nb IOT module, the field motor parameters are uploaded to the open platform of the telecom IOT in order to awake the remote networking and data access operation of the field motor data.Data storage monitoring service platform is the data storage and remote monitoring interface of the whole motor condition monitoring system. Using the API provided by the open platform of the Internet of Things, the data interaction between the IOT North host computer and the open platform of the Internet of Things is realized, the motor parameters of the front-end parameter collection and transmission unit are acquired, and the acquired parameters are stored in the corresponding data table items of MySQL database. Then, through the remote browser access Tomcat web server, the data in MySQL database is displayed in the remote access end, to achieve the monitoring of the running state of the field motor. As shown in In the parameter setting of quality prediction model based on XGBoost algorithm, some parameters are set as follows, as shown in The unit data acquisition module equipped with each equipment has basically completed the equipment status data acquisition required by production, completed the communication between the lower sensor and the upper computer through reasonable networking, and successfully implemented the real-time monitoring function through the configuration software. In the real-time data acquisition, there is a slight delay deviation between the actual data of the equipment and the acquisition display data, which has no impact on the product production control within the acceptable range. But it also needs to be improved later. So far, the whole data acquisition and monitoring system have been built, and the equipment number, corresponding IP address, and slave station address are recorded in the upper computer software for later query and management. Configuration software has played its due role. It not only collects and transmits the data of the sensors of the lower equipment but also successfully completes the real-time monitoring of the configuration and provides a variety of monitoring management methods such as trend chart and report form, which provides a good foundation for the subsequent improvement and optimization. In conclusion, XGBoost algorithm has a good performance in quality prediction-oriented classification. In the production process, the prediction model can be used to complete the batch of products according to the existing process parameter settings before they are put into production; the prediction of good product rate has a more comprehensive understanding and control of production and processing, as show in As a complex system engineering, the Internet of Things has cross integration with many technologies, such as radio frequency identification, network communication, integrated circuit, computer software and hardware, and system integration. In this technology chain, the backwardness of any link will affect the development of Internet of Things and industry.Worldwide, Philips, French semiconductor, and Texas Instruments basically monopolize the RFID chip market; Intel, Honeywell, Foxboro, and other enterprises have absolute advantages in the sensor market; IBM, Microsoft, Sybase, Oracle, and other international giants seize the leading position in middleware, Internet of Things system integration, and overall solution market; The core technology of information module and intelligent control equipment is also basically in the hands of European and American multinational companies. As far as China's current situation is concerned, due to the limitation of domestic IC design level, there is a lack of independent intellectual property rights in key core technology areas, which restricts the further development. China has successfully cultivated a number of industry leading enterprises in this field, but in sensor manufacturing, Internet of Things system integration application, public service, and other fields, there is a lack of leading enterprises to control high-end products or core technologies, especially those chain leading enterprises that determine technical standards, master the right to formulate technical standards, and can lead the direction of technological innovation and evolution, which have not yet formed. Effective business model and industrial division system lead to the low output value of the core industry.Technological innovation and industrial development have the relationship of mutual influence and promotion. At the same time, the development of industry also needs the combination of industrial model matching with relevant technological innovation. With the increasingly extensive application of the technology and the continuous maturity of common markets, the state needs to guide the industry of Internet of Things from support to independence, promote the connotative development of China's Internet of Things industry, achieve technological innovation and surmount in key technologies, and promote the development of new urbanization with greater advantages.


At present, collaborative industrial parks (CIPs) in the Yangtze River Delta Region (YRDR) have become an important spatial strategy for coordinating regional development. However, existing studies tend to focus on individualized micro-studies, ignoring the regional-scale production space reconstruction by the geographical expansion of CIPs. Based on this, this study takes the YRDR, where the development of CIPs is relatively mature, as an example and systematically analyzes their geographic expansion process and driving mechanism. The results found that CIPs in the YRDR have gone through three stages: the exploration period of CIP construction under the guidance of assistance policies; the blowout development period of CIPs under the demonstration effect; and the complete cluster formation period of CIPs. Regional central cities, such as Suzhou, Hangzhou, Nanjing, and underdeveloped cities, such as Tongling and Xuancheng, are core nodes, with Shanghai–Nantong; Shanghai–Anqing; Nanjing–Huainan; Wuxi–Xuzhou; Suzhou–Suqian; and Jiaxing–Lishui being important elements in the flow channel. The CIP network is basically formed. During this period, the degree of all nodes increased to 134, the network connection rate increased to 2.26, and the network complexity was more significant. Furthermore, CIPs are essentially a form of capital re-territorialization and space restoration organized and coordinated by the government . In the meantime, the market and the social environment, such as residents’ living standards, urban development foundation, urban transportation, and urban investment, also have an important impact on the geographic expansion of CIPs. In the regression results, the coefficients of popu, finance, labor, and passenger are significantly negative, but the coefficients of wage, gdp, freight, and govrd are significantly positive. From the agricultural economy to the later stage of industrialization, the economy and society have basically been organized around cities . HoweverIn the past, scholars discussed the spatial structure of economic and social connections between cities based on the flow of people, traffic, information, and capital ,8. The cWith the development of CIPs in the YRDR, significant changes are taking place in the economic production links between cities. What changes have taken place in economic production linkages under the background of the expansion of CIPs in different places? How is their formation mechanism different from traditional element flow? It is an important direction for this paper to expand existing literature theory. As one of the typical representative regions of regional integrated development in China, the development of CIPs in the YRDR has experienced nearly 20 years. It has transformed from an exploration period to a gradual maturity period, which provides a good case support for us to carry out related research. Therefore, in order to clarify the heterogeneity of its connection with traditional factors for the reconstruction of economic production relations, this study takes the geographical expansion of CIPs in the YRDR as an example, and systematically analyzes the spatiotemporal evolution pattern of its geographical expansion based on complex network methods. At the same time, based on the two-way fixed effects measurement model, the mechanism of its geographical expansion is systematically discussed.“Enclave Economy” first reflects the phenomenon that a foreign-oriented or high-tech industry is dominated by international capital rather than embedded in the local economy ,6, whichLater, with the innovation of the interactive cooperation model between domestic cities, it is given new connotations, and the research scale begins to focus on regions or cities, which mainly reflects the cross-administrative boundary cooperation model between different cities or regions ,16. On tCurrent research mainly focuses on the economic performance , operatiAs for the dynamic mechanism of CIPs , currentThe driving force of the market is the attractiveness of economic benefits brought about by the allocation of resources on a larger scale, and the effective flow of elements is gathered together to achieve the complementation and effective allocation of resources . Some stIn addition, some studies also found that the public, non-governmental organizations (NGOs), social business groups, and other social entities play an important role in the development of CIPs. The cooperative partnership established by cooperative entities based on social factors, such as mutual trust, respect, and social network connections, plays an important role in promoting the transfer of knowledge in the process of cooperation . NGO intOn the whole, current research mostly focuses on individualized micro-research, the scale is mainly concentrated in a city or even a CIP itself, and there is a lack of more detailed research on the changes and trends of macro-structure. In particular, it ignores the analysis of the restructuring of regional-scale production space by the geographical expansion of CIP. At the same time, current research on the driving mechanism of CIPs mainly focuses on government behaviors, and less attention is paid to the influence of the market and social environment. Based on this, the study takes the YRDR as example; conducts a systematic analysis of the spatial production process and organizational model evolution of CIPs; and adopts a combination of qualitative and quantitative methods to systematically summarize the impact of government behaviors, the market, and the social environment on CIPs, which can provide a theoretical reference for cross-urban regional organization of economic activities in the new era.i represents the individual city; t represents the year; K represents the degree value of the dependent variable node ; X represents the driving factor variable; city is the unobservable individual fixed effect of a city; year is the time fixed effect; and ɛ is the random disturbance term. With reference to previous research literature .Centrality: In recent years, in order to fully evaluate the status and role of nodes in the network, scholars have mainly analyzed the degree centrality, adjacency centrality, and betweenness centrality .Degree centrality: Degree reflects the connection between a node and other nodes. Degree centrality is the most direct measure to describe the centrality of nodes. The greater the degree value of nodes, the higher the degree centrality of these nodes and the greater the importance of these nodes in the network . The speThis study takes the Yangtze River Delta Region as the research area . AccordiTaking into account that relevant data on CIPs have not been systematically counted, the research process mainly uses policy documents and the literature to sort out the data, while taking into account the information extracted from news materials and reports to obtain relevant data. Secondly, part of the data is obtained in conjunction with the statistical yearbooks of the development zones of various provinces and cities. These statistics found that after 2010, CIPs in the Yangtze River Delta entered a period of blowout development. At present, according to incomplete statistics , the numAs for the data in Overall, the geographical expansion of CIPs in the YRDR can be roughly divided into three stages: the exploration period of CIPs; the “blowout” development period of CIPs; and the complete cluster formation period of CIPs. In different stages, there are obvious differences in the spatial organization mode of CIPs.The establishment of a Jiangyin–Jingjiang CIP in 2003 opened the prelude to CIPs in the YRDR. In 2006, in order to solve the backward economic development in the northern part of Jiangsu, the Jiangsu Provincial Government issued the “North-South Linkage” policy, which has further explored the institutional design of CIPs under the leadership of the government ,45. UndeAt this stage, CIPs basically present a one-way connection, and under the influence of assistance policies, CIPs are basically set up in underdeveloped cities a. In ordFrom the characteristics of the complex network at this stage, there are 11 nodes with a degree of one, accounting for 68.75%. From the perspective of degree centrality, Shanghai has the highest degree value (5) and has the most connections with other nodes in the network, showing high centrality (0.33). This is followed by Lianyungang, Yancheng, Wuxi, and Nanjing , with the degree centrality being all 0.13. In terms of the connection rate and network density values, both are zero, indicating that the interaction and interdependence between these node cities are relatively limited, and the network structure is relatively simple at this time.Inspired by the CIPs in Jiangsu, Zhejiang carried out the construction of the “Mountain-Sea cooperation” CIPs, and Anhui carried out the “Southern and Northern cooperation” CIPs. Zhejiang issued the “Several Opinions on the Implementation of a New Round of Mountain-Sea CIP Projects” in 2009 , encouraAt this stage, the scale of CIPs had rapidly expanded and had expanded to Zhejiang and Anhui provinces a. The nuFrom the characteristics of the complex network at this stage, the degree value of all nodes has increased from 24 to 83, an increase of 245%. At the same time, node cities have begun to show a multi-directional development pattern. Among them, there are 13 node cities with a degree value of more than three, accounting for 40.6%. Especially for Shanghai, Suzhou, Wuxi, Nanjing, which have relatively good economic foundations, with degrees of 8, 7, 6, and 4, respectively. These node cities also show high centrality in the network of CIP, with high agglomeration coefficient and node centrality, which makes the hub-and-spoke network structure characteristics outstanding during this period. At the same time, during this period, the network connection rate has increased from 0.85 to 1.59, and the network complexity has increased significantly. The network density has dropped from 0.20 to 0.17, and the overall tightness of the network has dropped. From the distribution of CIP in various provinces, the scale of CIPs in Jiangsu Province continues to expand, especially between Nanjing and Huai’an, between Changzhou and Yancheng, and between Lianyungang and Zhenjiang, and the number of CIP (three or more) has increased significantly. In Anhui Province and Zhejiang Province, CIPs have begun to appear sporadically, but the number of CIPs between urban nodes is basically one; the network connection rate and network density are low, and the network structure is relatively simple. As far as Shanghai is concerned, Shanghai has started cross-provincial CIPs, with Nantong, Yancheng, and Suzhou in Jiangsu Province; Xuancheng and Ma’anshan in Anhui Province; and Jiaxing in Zhejiang Province. However, during this period, CIPs in the YRDR are basically within the province and the newly built CIPs are mainly concentrated in Jiangsu and Anhui provinces, while the number of newly built CIPs in Zhejiang is still relatively small.After 2015, the National Development and Reform Commission of China issued the “Guiding Opinions on Supporting the Development of “Enclave Economy”” . Under tAt this stage, the scale of CIPs continues to expand, and with the development of cross-provincial CIPs, the interconnection of elements between cities has basically been realized a. From tFrom the characteristics of the complex network at this stage, the number of nodes participating in CIPs has increased from 32 to 41, and the degree of all nodes has increased from 83 to 134. During this period, the network connection rate has increased from 1.59 to 2.26, the network complexity has become more significant, and the network has a loop structure. The network density has dropped from 0.17 to 0.16, indicating that, with the geographical expansion of CIPs, the overall network compactness has declined, and the overall network connection has become relatively sparse, which is closely related to the connection between some new nodes in Anhui and Zhejiang. From the perspective of the degree value of the network nodes, there are 11 nodes with a degree value of one in the network, accounting for 26.2%. There are 22 node cities with a degree value of more than three, accounting for 53.7%. The nodes with a degree value of more than five are Shanghai, Suzhou, Hefei, Xuancheng, Ningbo, Lishui, Chuzhou, Wuxi, and Nanjing. Among them, Shanghai, Suzhou, Hefei, Ningbo, Wuxi, and Nanjing are mainly flying-out places, while Xuancheng, Lishui, and Chuzhou are mainly flying-into places. From the perspective of agglomeration coefficient and centrality index, the formation of complete agglomeration further strengthens the network centrality characteristics of many nodes. On the one hand, some cities with high degree have formed a high network centrality, such as Shanghai, Hangzhou, Suzhou, and Nanjing. On the other hand, some cities with relatively backward development foundations are also closely connected with other nodes in the network, such as Tongling and Xuancheng, which also exhibit high network centrality characteristics.To sum up, with the development of cross-provincial CIPs, the complete cluster formation of the network has become more and more obvious, and it has become an important regional space carrier that carries the occurrence and development of economic activities in the YRDR. The spatial distribution of CIP plays an important role in promoting the process of industrial integration in the YRDR.Based on previous research, it is not difficult to find that the evolution of CIPs will not only be influenced by policy guidance, but will also be affected by the market, social, and other factors. It should be noted that in China, social organizations are relatively limited in guiding the construction of CIPs, so this paper does not discuss the social aspects.As a new institutional space, a CIP is fundamentally driven by the spatial movement of capital , and it In addition, the national spatial selectivity has played a significant role in promoting the development of cross-provincial CIPs . It is mIn order to reflect the robustness of the regression results regarding the driving mechanism, this paper conducts a stepwise regression test according to the four variable groups involved. The results demonstrate that the influence of different market factors on CIPs shows obvious heterogeneity . For theOn the whole, affected by the strong government intervention, the geographical expansion of CIPs has broken the cognitive category of traditional economic geography that the flow of factors follows geographical proximity and agglomeration to the megacities; the impact of some factors on the geographical expansion of CIPs presents an anti-marketization characterization. In the regression results, the coefficients of popu, finance, labor, and passenger are significantly negative, indicating that the higher the level of urban population agglomeration and financial development; the more the number of people; and the greater the passenger traffic, the lower the enthusiasm for participating in the construction of CIPs. This phenomenon is contrary to the laws of the market, which may have a lot to do with the development stage of most cities with a high level of economic foundation development in the YRDR. At present, most cities in the YRDR with high development level cannot meet their own development needs in terms of population absorption and financial services, etc. Under the influence of government support policies, they have to participate in the development of CIPs, which makes some factors appear to have anti-market characterization.At the same time, the coefficients of wage, gdp, freight, and govrd are significantly positive. It shows that the geographical expansion of CIPs is still positively affected by market factors, such as the level of local economic development, external production links, the level of scientific and technological development, and the income of residents. This analysis assumes that, with the market-oriented development of CIPs, the foundation of economic development, the connection with external production, the level of scientific and technological development, and the income of residents have become the key factors affecting the high-quality and sustainable development of CIPs, and they have also become an important manifestation of market participation in the construction of CIPs.In addition, the coefficient of house is positive but not significant; the coefficient of sec is negative but not significant; and the coefficient of hum is negative but not significant.In order to ensure the reliability of the regression results of the above-mentioned driving mechanism, this paper also conducts a series of robustness tests.① Stepwise regression. The stepwise regression results in ② Change the research sample. ③ Select some years. Model (4) in In recent years, the policies and practices of CIPs in Jiangsu, Anhui, Zhejiang, Shanghai, and other places have continued to innovate. CIPs have shown the characteristics of diversified types, multiple participants, and cross-regional cooperation. This article conducts empirical research on the evolution and driving mechanism of CIPs in the YRDR. The results demonstrate the following:From the perspective of the geographical expansion of CIPs, we found that, with the geographical expansion of CIPs, city nodes are gradually connected due to the co-construction relationship, and a networked organization model of CIPs has emerged. At present, the core nodes of regional central cities, such as Shanghai, Suzhou, Hangzhou and Nanjing, and underdeveloped cities, such as Tongling and Xuancheng, have been initially formed, with Shanghai–Nantong; Shanghai–Anqing; Nanjing–Huainan; Wuxi–Xuzhou; Suzhou–Suqian; Jiaxing–Lishui, and others being the important elements in the flow channel. The construction of CIPs under the assistance policy has boosted the central position of urban nodes in some underdeveloped regions to a certain extent, and will have a greater impact on the development of the edge cities of the YRDR.From the perspective of the driving mechanism of CIPs, on the one hand, CIPs are a form of the capital re-territorialization and space restoration coordinated and organized by the government . On the other hand, affected by the strong government intervention, the impact of some factors on the geographical expansion of CIPs present anti-market characterization, with the coefficients of popu, finance, labor, and passenger being significantly negative. However, market factors, such as the local economic development level, external production connection, scientific and technological development level, and residents’ income, still play a significant positive role in the geographical expansion of CIPs.In this context, we should give full play to the important role of CIPs in the cross-regional flow of factors, actively guiding developed cities and surrounding underdeveloped cities to carry out the construction of CIPs, guiding cross-regional exchanges and cooperation of factors, and promoting a new round of development of regional integration. Secondly, we should give full play to the dual factors of government and market in future urban and regional development. On the one hand, we should give full play to the government’s macro-control role in guiding the cross-regional flow and connection of elements, giving more development opportunities to marginal cities or underdeveloped areas, and promoting the rapid development of integration by creating policy space, such as CIPs in different places. On the other hand, we should also provide a good market environment for the cross-regional flow of factors, such as the construction of rapid transit system, supporting urban infrastructure, giving full play to the guiding role of the market, and removing the market barriers of cross-regional circulation of factors.This research systematically sorts out the process and driving factors of the geographical expansion of CIPs in the YRDR, which can provide a certain theoretical reference for the production interaction in the YRDR in the new period. On the one hand, in the past, scholars discussed the spatial structure of economic and social connections between cities based on the flow of people, traffic, information, and capital ,8, and tHowever, there are still many problems that need to be further analyzed and improved. On the one hand, this research lacks relatively micro-data, such as the industrial attributes of parks, and the analysis of the spatial impact of CIPs on the industrial structure of the YRDR is lacking. On the other hand, current parks have experienced nearly 20 years of development. How are their development status? What are the later issues that they are facing? Furthermore, this paper only analyzes the process and driving factors of the geographical expansion of CIPs, and there is no validation on whether CIPs play a mediating role in the cross-regional flow. All of these questions need to be analyzed through a field survey system.


Dear Editor,The skin can signal internal diseases such as visceral neoplasms. Any tumor has the potential to cause skin metastases, which can occur via lymphatic, hematogenous routes, contiguity or iatrogenic implantation. Subcutaneous nodules can have inflammatory, infectious or neoplastic etiologies. Skin metastases occur in 1% to 9% of malignancies, and about 10% affect the umbilical region.2Metastasis to the umbilical region has been described as Sister Mary-Joseph's nodule. It is a painless, palpable lump that varies in color from violaceous to reddish-brown and can resemble a vascular structure.A 45-year-old female patient presented with painless nodular lesions in the umbilical and periumbilical region for 6 months, associated with weight loss and abdominal pain. Clinically, she was pale, emaciated, showing a globular and ascitic abdomen, an abdominal mass in the pelvic region, and purplish-brown nodules with an ulceronecrotic surface and hardened consistency in the umbilicus and periumbilical region . The abdIt is essential to know the causes of umbilical nodules, since this cutaneous manifestation can represent an opportunity to make the diagnosis of the primary lesion. Some differential diagnoses are cutaneous endometriosis, pyogenic granuloma, melanoma, squamous cell/basal cell carcinoma, and umbilical hernia.Findings similar to those of the present case (CK7+ CK20-) correspond to primitive tumors that can be located in the breast, lung, thyroid, and gynecological tumors. Specific antibodies were used, excluding adenocarcinoma of other origins and indicating the ovary as the strongest possibility of the primary origin of the umbilical metastases. Finally, it is important to note that in the presence of umbilical nodules, the possibility of cutaneous metastases should be considered.None declared.Ivonne Dannesy Rodriguez Hernandez: Approval of the final version of the manuscript; design and planning of the study; drafting and editing of the manuscript; intellectual participation in the propaedeutic and/or therapeutic conduct of the studied cases; critical review of the literature; critical review of the manuscriptPatricia de Franco Marques Ferreira: Approval of the final version of the manuscript; design and planning of the study; drafting and editing of the manuscript; intellectual participation in the propaedeutic and/or therapeutic conduct of the studied cases; critical review of the literature; critical review of the manuscript.Paula Dadalti Granja: Approval of the final version of the manuscript; design and planning of the study; effective participation in research orientation; intellectual participation in the propaedeutic and/or therapeutic conduct of the studied cases; critical review of the literature; critical review of the manuscript.Mayra Carrijo Rochael: Approval of the final version of the manuscript; drafting and editing of the manuscript; effective participation in research orientation; intellectual participation in the propaedeutic and/or therapeutic conduct of the studied cases; critical review of the literature; critical review of the manuscript.None declared.


In the published article, there was an error in affiliation 3. Instead of Department of Psychology, Beijing Normal University, Beijing, China, it should be Institute of Early Childhood Education, Faculty of Education, Beijing Normal University, Beijing, China.The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Dear Editor,The auricle or pinna is a frequent target of malignant neoplasms. Half of the tumors are located in the helix, and many defects involve both skin and cartilage, making surgical reconstruction a challenge.in situ squamous cell carcinoma (SCC), measuring 13 mm in its largest diameter, submitted to Mohs micrographic surgery (MMS) and removed in the first stage. The second patient had an infiltrative basal cell carcinoma (BCC), measuring 8 mm in its largest diameter, removed in 2 stages, using MMC. Finally, the third case was a well-differentiated SCC, measuring 10 mm in its largest diameter, resected using the conventional technique  are easily reconstructed with wedge excision and primary closure, unlike larger defects, which require the use of grafts or flaps.Grafts require a preserved cartilaginous structure, with viable perichondrium or cartilage perforations to allow irrigation through the contralateral bed. In composite defects, the structural loss of the helix margin requires cartilage and skin for its repair, which can be performed using the following techniques: composite graft from the contralateral auricle; interpolated flaps using cartilage; chondrocutaneous flap.The chondrocutaneous flap was first described by Antia and Buch, in 1967. The principle of the procedure is to advance the skin and cartilage of the intact portion of the helix adjacent to the defect, based on a wide and secure retroauricular pedicle, with greater preservation of the vascularization of the posterior auricular artery.Therefore, Antia and Buch flap, despite having been described more than 50 years ago, maintains its role among the techniques of helix reconstruction, and its knowledge is important for dermatological surgeons. It is an effective and safe method, performed in a single step with the additional advantage of preserving local vascularization, reducing the risk of necrosis.None declared.Paula Hitomi Sakiyama: Approval of the final version of the manuscript; design and planning of the study; drafting and editing of the manuscript; collection, analysis, and interpretation of data; critical review of the literature; critical review of the manuscript.Thiago Augusto Ferrari: Approval of the final version of the manuscript; design and planning of the study; drafting and editing of the manuscript; collection, analysis, and interpretation of data; critical review of the literature; critical review of the manuscript.Raíssa Rigo Garbin: Approval of the final version of the manuscript; design and planning of the study; collection, analysis, and interpretation of data; effective participation in research orientation; intellectual participation in the propaedeutic and/or therapeutic conduct of studied cases; critical review of the literature; critical review of the manuscript.Roberto Gomes Tarlé: Approval of the final version of the manuscript; design and planning of the study; effective participation in research orientation; intellectual participation in the propaedeutic and/or therapeutic conduct of the studied cases; critical review of the literature; critical review of the manuscript.None declared.