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In order to solve the poor heat dissipation in the outdoor mobile communication base station, especially in summer, high temperature alarm phenomenon occurs frequently, affecting the normal operation of building base band unite, this paper designs an energy-saving and efficient integrated thermal management system, which has achieved good results by applying the combined operation of heat pipe cooling and air conditioning system using the outdoor temperature switching mode. A mobile communication base station in Zhengzhou City was chosen for a pilot application. The measured results showed that the system ran stably, the temperature inside the cabinet was controlled between 12 °C and 39 °C with no high temperature alarm, the compressor running time was significantly reduced, the power consumption of the air conditioner was significantly reduced, and the annual power saving rate was as high as 58.63%. [ABSTRACT FROM AUTHOR]

In view of the prominent and intractable problems of frequent high temperature alarms of the communication equipment and high energy consumption of air conditioners in Zhengzhou communication outdoor cabinets, a temperature control system with heat pipe as the main part and air conditioner as the auxiliary part is proposed in this paper. A prototype is developed and its applications are discussed. The annual field test shows the system works well, and it has a remarkable energy saving efficiency. [ABSTRACT FROM AUTHOR]

Aimin Liu1,21Department of Dermatology, Henan University of Chinese Medicine, Zhengzhou, Henan, People's Republic of China; 2Department of Dermatology, Henan Province Hospital of Traditional Chinese Medicine, The Second Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, Henan, People's Republic of ChinaCorrespondence: Aimin Liu, Department of Dermatology, Henan Province Hospital of Traditional Chinese Medicine, The Second Affiliated Hospital of Henan University of Chinese Medicine, No, 6, Dongfeng Road, Jinshui District, Zhengzhou city, Henan Province, 450053, People's Republic of China, Tel +86 13592603226, Fax +86-371-60973329, Email [email protected] Background: Generalised pustular psoriasis (GPP) is a chronic inflammatory skin disease. We aimed to visualize the research hotspots and trends of GPP using bibliometric analysis to enhance our comprehension of the future advancements in both basic science and clinical research.Methods: Relevant publications from July 2003 to July 2023 were obtained from the Web of Science Core Collection on July 12, 2023. The analysis of countries, institutions, authors, references, and keywords associated with this subject was conducted through the utilisation of CiteSpace 6.2.R4, VOSviewer 1.6.18, and Microsoft Excel 2019.Results: A total of 578 papers were analyzed, authored by 2758 researchers from 191 countries/regions and 1868 institutions, published in 174 academic journals. There was an overall upward trajectory in the volume of annual publications, accompanied by a gradual intensification of research interest in GPP. The United States, UDICE-French Research Universities, and Akiyama M of Nagoya University were the most productive and influential country, institution, and author, respectively. The Journal of Dermatology ranked first with the highest publications, and the Journal of the American Academy of Dermatology received the most citations. High-frequency keywords included "generalized pustular psoriasis", "psoriasis, interleukin-36", "plaque psoriasis", "skin-disease", and "antagonist deficiency". Recent research focuses have included "safety", "secukinumab", "spesolimab", "ap1s3 mutations", and "interleukin-36". Burst detection analysis of keywords showed that "moderate", "ixekizumab treatment", "mutations", "efficacy", and "safety" are current research frontiers in this field.Conclusion: This bibliometric analysis delineated the landmark publications in GPP that have defined current research hotspots and development trends, notably the applications, efficacy, and safety of biological agents. Future research endeavors are warranted to explore other biological therapeutic options for both acute GPP and the long-term management of chronic GPP. [ABSTRACT FROM AUTHOR]

On 20 July 2021, an extreme rainstorm battered Zhengzhou in China's Henan Province, killing 302 people, including 14 individuals who drowned in a subway tunnel and 6 who drowned in a road tunnel. As the global climate warms, extreme weather events similar to the Zhengzhou flood will become more frequent, with increasingly catastrophic consequences for society. Taking a case study-based approach by focusing on the record-breaking Zhengzhou flood, this paper examines the governance capacity of inland cities in North China for managing extreme precipitation and flooding events from the perspective of the flood risk management process. Based on in-depth case analysis, our paper hypothesizes that inland cities in North China still have low risk perceptions of extreme weather events, which was manifested in insufficient pre-disaster preparation and prevention, poor risk communication, and slow emergency response. Accordingly, it is recommended that inland cities update their risk perceptions of extreme rainfall and flooding events, which are no longer low-probability, high-impact "black swans", but turning into high-probability, high-impact "gray rhinos." In particular, cities must make sufficient preparation for extreme weather events by revising contingency plans and strengthening their implementation, improving risk communication of meteorological warnings, and synchronizing emergency response with meteorological warnings. [ABSTRACT FROM AUTHOR]

Urban water management is confronted with more frequent, more extreme weather events. This paper introduces the Three-Points Approach (3PA) into Sponge City concept, to create a novel framework aimed at guiding water management interventions across local, urban, regional, and river basin scales. The 3PA integrates three domains--Day-to-day, Design, and Extreme--offering a nuanced strategy for flood and drought risk mitigation, also for extreme events. Notably, the 3PA emphasizes the fusion of blue-green infrastructure (BGI) with conventional gray approaches to enhance both multifunctionality and resilience in extreme weather conditions. The study identifies critical issues of implementing this Three-Points Sponge Policy (3PSP) approach, including spatial and temporal scales, transitioning from gray to blue-green infrastructure, asset management, data handling, and effective communication. Interventions spanning various spatial scales and addressing flood protection, drought resilience, and water quality are explored in a first and indicative application in Zhengzhou. The case study distills key design principles, highlighting the imperative of never shifting problems, embracing ecosystem-based adaptation, seeking synergy between interventions, and incorporating adaptability into designs. The 3PSP approach emerges as a holistic framework that considers both risks and benefits, contributing valuable insights to the discourse on integrating urban and river basin water management, improving our ways of dealing with extreme weather events while maximizing the day-to-day benefits of our interventions. [ABSTRACT FROM AUTHOR]

[Objective] Soil organic carbon (SOC) is not only an indicator of soil health but also plays a crucial role in feedback interaction between global warming and carbon stock in terrestrial ecosystems. Its dynamics is modulated by a multitude of interactive abiotic and biotic factors. In this paper, we analyze the spatial distribution of SOC in the plough layer and its correlation with soil texture and other geochemical properties in the region of Zhengzhou in Henan province. [Method] Soil samples were taken from a grid network in the region. SOC, bulk density, soil texture and other geochemical properties in each soil sample were measured. The correlation between SOC and soil nutrients, including nitrogen, phosphorus, potassium and micronutrients in the soil, was analyzed using the GeoChemStudio software. [Result] The calcareous skeletol soil in the region has the highest SOC, reaching 2.307%. The SOC content varied from 0.1%-11.6% across the region, and was normally distributed with a mean of 1.134%. The SOC was positively correlated with N, P2O5, Fe, Mn, Zn, Cu, Mo and B, and their associated correlation coefficients were 0.804 5, 0.223 0, 0.156 3, 0.119 1, 0.223 8, 0.263 4, 0.162 8 and 0.191 1, respectively. Negative correlations were found between SOC and K2O and pH, and their associated correlation coefficients were -0.088 8 and -0.195 7, respectively. The average SOC content in the plough layer in the region was 1.09%. Spatially, SOC was rich in Xinmi, Dengfeng and Gongyi in the southwest of the region. In terms of soil texture, SOC is higher in skeletol soil and calcareous cinnamon soil than in other soils. SOC stored in the topsoil in the whole region was 1 012.87x104 t, with 523.13x104 t stored in the cinnamon soils and calcareous cinnamon soils, accounting for 51.64% of the total topsoil SOC in the region. [ABSTRACT FROM AUTHOR]

This study proposes a two-dimensional analytical framework based on urban spatial form and spatial service perspectives, utilizing data on buildings and points of interest (POIs). It integrates fishnet analysis, kernel density analysis, the categorization of POI functionalities, and mixture calculations to enhance our understanding of urban spatial form and function. Taking the main urban area of Zhengzhou as an example, this study identifies image elements that can describe urban spatial characteristics through the results of two-dimensional analysis and enriches the city image in the form of a portrait. The experimental findings demonstrate that the elements of the annular layer, functional landmarks, ring line boundaries, and special districts can fully convey the spatial picture of Zhengzhou City. The performance of the four types of image elements has a high degree of matching with the content of the urban spatial planning of Zhengzhou City, which can effectively identify the urban multi-center structure and development pattern. This paper explores and tests the development status of the city from a new perspective, which can provide an effective reference for the future planning and sustainable development of the city. [ABSTRACT FROM AUTHOR]

The transit signal priority leads to the delay of private vehicles in the priority and non-priority phases. To address this problem, a bi-level programming model is proposed based on the dynamic cycle and arrival rate of private vehicles under connected environment. The upper model is built by a delay triangle, with the maximum delay reduction of private vehicles between the decreased delay and increased delay in the experimental period. The lower model is constructed based on the Stackelberg model of game theory, and the objective is to obtain the dynamic cycle. A genetic algorithm (GA) is implemented to solve the proposed model. Based on SUMO, a case study of a self-driving bus in the city of Zhengzhou is conducted to demonstrate the effectiveness of the proposed model. The results from GA and SUMO are consistent, which verifies the effectiveness of the proposed model. The delay of the private vehicles with dynamic signal priority declines by 21.32% on average compared to that without priority. Compared with active signal priority, it declines by 22.63% on average. The proposed method is compared with the method proposed by other papers, and the delay per private vehicle is small. The effectiveness of the proposed method is further illustrated. The proposed methodology is helpful for improving the operation efficiency of intersections with minimum delay. [ABSTRACT FROM AUTHOR]

With the continuous expansion of urban scale in China, the increase of passenger flow has brought great pressure to the urban public transport system. An accurate and timely prediction of the short-term passenger flow at each metro station is extremely important for the metro intelligent control system to make a timely decision. In this paper, based on the measured passenger flow data of Zijingshan station of Zhengzhou Metro Line 1, an improved whale optimization algorithm is proposed to predict the passenger flow on different time scales. The results show that the method has higher accuracy than the traditional least squares support vector machines algorithm. The paper opens a new window for nowcasting warning in the rush hour and long-period optimization of the public transport. [ABSTRACT FROM AUTHOR]

Based on urban flood hydrology processes and hydrodynamic principles, the stormwater management model (SWMM) was improved upon. The coupling and implementation methods of the SWMM and two-dimensional hydrodynamic model are proposed. The improved SWMM was coupled with the hydrodynamic model both from the vertical and horizontal directions. The hydrology and hydrodynamic coupling model (HHDCM) was constructed and verified by using extreme rainstorm data. Taking July.20 extreme rainstorms (from July 17 to July 20, 2021, i.e., July.20 extreme rainstorm) in Zhengzhou city, Henan Province, China, as an example and using the HHDCM model, the flood disaster caused by July.20 extreme rainstorm was simulated. Based on the simulation results, an inundation distribution map was drawn for the urban area. A comparison between the simulated and measured results reveals that the maximum relative error in the simulated results is 12.5%. Therefore, the HHDCM model proposed in this paper has desirable accuracy and reliability for simulating extreme urban rainstorms and flood disasters. [ABSTRACT FROM AUTHOR]

The frequent occurrence of urban flood disasters is a major and persistent problem threatening the safety of cities in China and elsewhere in the world. As this issue is so pervasive, exploring new methods for more effective risk prevention and urban flood disaster control is now being prioritized. Taking the case of the city of Zhengzhou as an example, this paper proposes using geological, hydrogeological, ecological, and environmental conditions together with appropriate engineering designs to address the problem of urban flooding. The strategy includes integrating urban sponge–hydrogeological conditions, ecological engineering, and the construction of deep underground water storage facilities. Field investigations, data collection and analysis, in situ observations, testing, and laboratory experiments, are analyzed to explain the formation mechanism and means to mitigate flood disasters in Zhengzhou. Our results suggest that the appropriate use of geological, ecological, and hydrogeological aspects, combined with effective engineering practices, can significantly improve the city's flood control capacity. These measures can solve the problem of the "once-in-a-millennium" occurrence of torrential rain disasters such as the "720" torrential rainstorm that has affected the city of Zhengzhou. [ABSTRACT FROM AUTHOR]

Point cloud registration is of great significance to the reconstruction of high‐precision 3D city models. There are some challenges when aligning aerial and close‐range photogrammetric point clouds, such as huge view differences caused by the different sights of the sensors, massive noisy points due to the error in dense matching, and scale uncertainty since there are no control points for absolute orientation. To achieve complementary advantages of aerial and close‐range point clouds, in this paper, a robust cross‐source point clouds registration method is proposed using image visual context features and scale consistency. First, a cross‐view image matching method based on image visual context features is proposed to obtain corresponding points. Second, to overcome the challenges of noisy points and scale differences, an outlier filtering method is designed based on scale consistency. Finally, the dual quaternions model considering the scale factor is introduced to solve the spatial transformation model. To analyze the feasibility of this method qualitatively and quantitatively, experiments are conducted using the public scene dataset of Dortmund, Germany, and the scene dataset of Zhengzhou City, China. Three kinds of cross‐source point clouds registration experiments are conducted in this paper, including aerial and close‐range point clouds registration in Dortmund, and aerial and ground point clouds registrations in both Dortmund and Zhengzhou. The chamfer distances of the three sets of experiments are 4.48 m, 5.97 m and 4.78 m, respectively. The ablation study shows that the outlier filtering method and the dual quaternions model improve the accuracy by at least 14% and 25%, respectively. The experiments demonstrate that the method accomplishes the cross‐source point clouds registration in large‐scale scenes accurately and efficiently, providing a solid foundation for subsequent fine 3D reconstruction. [ABSTRACT FROM AUTHOR]

As the scale of underground rail transit construction in urban areas continues to expand, the tunnel construction environment has become progressively more complex. In recent years, an emerging artificial intelligence (AI) method in the civil engineering field, called the Random Forest (RF) method, has been widely used. In the construction of Zhengzhou Metro Line 7, the RF method was used to predict and control the vertical displacement of the bridge pier pile foundation. Such displacement can indicate the deformation of the structure, particularly under long-term utilization and strenuous circumstances that could sink or lift the pier body. Moreover, the vertical displacement of the bridge pier can affect the stiffness and bearing capacity of the bridge, thus impacting driving safety and the bridge's service life. Therefore, the vertical displacement of bridge piers has become the main prediction and control indicator for research. In the Zhengzhou Metro Line 7 tunnel, the tunnel continuously passes through 78 bridge pier foundations, among which the pile foundations of 4 key bridge piers are less than 0.5 times the tunnel diameter with a clear distance planned for the tunnel. However, limitations such as surface traffic and environmental conditions prevent the reinforcement of the bridge pier foundation in advance. Therefore, determining and setting sensible shield construction parameters is crucial to effectively controlling the vertical displacement of these essential bridge piers. This project can serve as a model for future endeavors. The study combines Random Forest with Particle Swarm Optimization Algorithm (PSO) to upgrade the technology of shield tunneling through Pier 2, introduces the Bayesian principle for statistical analysis, and optimizes various main construction variables. Random Forest is an ensemble learning method based on decision trees, which has high flexibility and predictive performance. It can automatically filter out important features from a large number of input features, thereby establishing an effective prediction model. The primary research objective is to enhance tunnel construction by accurately predicting and controlling the vertical displacement of pier foundations. To achieve this objective, the study utilizes the PSO to optimize the parameters and structure of the RF model. By doing this, the model's ability to predict the pier's vertical displacement accuracy can be improved. By combining these two methods, the accuracy of the prediction model and the optimization effect of construction parameters can be improved. In addition, the reliability of the model is further improved by using the Bayesian principle for statistical analysis. The paper compares and evaluates the engineering data objectively, presenting the evaluation index and feature selection method. This approach is innovative and purposeful, aiming to enhance the predictive ability, construction efficiency, and quality. This method can provide support for decision-making and optimization of engineering projects and promote sustainable development of the project. After the construction was completed, the model was established, and the results were predicted. The actual engineering measurement data of Pier Two was taken for comparison with it. Two parameters, Root-Mean-Square Error (RMSE) and Linear Curvature (R² ), were introduced to evaluate the prediction results, and the results were subjected to Correlation-based Feature Selection (CFS). The test sets for the downstream and the upstream tunnel were extracted, in which R² for the three extracted comparisons of the downstream were 0.83, 0.82, and 0.89, respectively, while R² for the upstream was 0.88, 0.86, and 0.86, respectively. From this, it can be seen that the optimized model has good predictive performance. In the construction process of other projects, the model can be used to predict the vertical displacement of bridge piers, which has real-time performance in preventing accidents. [ABSTRACT FROM AUTHOR]

Despite significant improvements in air quality during and after COVID-19 restrictions, haze continued to occur in Zhengzhou afterwards. This paper compares ionic compositions and sources of PM2.5 before (2019), during (2020), and after (2021) the restrictions to explore the reasons for the haze. The average concentration of PM2.5 decreased by 28.5% in 2020 and 27.9% in 2021, respectively, from 102.49 μg m−3 in 2019. The concentration of secondary inorganic aerosols (SIAs) was 51.87 μg m−3 in 2019, which decreased by 3.1% in 2020 and 12.8% in 2021. In contrast, the contributions of SIAs to PM2.5 increased from 50.61% (2019) to 68.6% (2020) and 61.2% (2021). SIAs contributed significantly to PM2.5 levels in 2020–2021. Despite a 22~62% decline in NOx levels in 2020–2021, the increased O3 caused a similar NO3− concentration (20.69~23.00 μg m−3) in 2020–2021 to that (22.93 μg m−3) in 2019, hindering PM2.5 reduction in Zhengzhou. Six PM2.5 sources, including secondary inorganic aerosols, industrial emissions, coal combustion, biomass burning, soil dust, and traffic emissions, were identified by the positive matrix factorization model in 2019–2021. Compared to 2019, the reduction in PM2.5 from the secondary aerosol source in 2020 and 2021 was small, and the contribution of secondary aerosol to PM2.5 increased by 13.32% in 2020 and 12.94% in 2021. In comparison, the primary emissions, including biomass burning, traffic, and dust, were reduced by 29.71% in 2020 and 27.7% in 2021. The results indicated that the secondary production did not significantly contribute to the PM2.5 decrease during and after the COVID-19 restrictions. Therefore, it is essential to understand the formation of secondary aerosols under high O3 and low precursor gases to mitigate air pollution in the future. [ABSTRACT FROM AUTHOR]

On the basis of analyzing the problems concerning hotel accommodation recommendation (HAR), this paper constructs a tourism HAR algorithm based on the CS-IDIANA clustering model (cellular space-improved divisive analysis). The algorithm integrates the cellular space model with DIANA, and takes the tourist attractions and the travel route costs as the research background and constraint conditions. Considering the feature attributes and spatial attributes of the tourist attractions, the tourist attraction recommendation algorithm based on the CS-IDIANA clustering model is established, then the HAR algorithm based on the spatial accessibility and route cost is constructed, with the constraints of the spatial accessibility field strength (SAFS) between the hotels and attractions and the travel route costs between the hotels and attractions. The experiment selects the tourism city Zhengzhou as the research object, and the experimental results are analyzed in four dimensions: the clustering results, the recommendation field strength of the tourist attractions, the hotel SAFS and the HAR results. The experiment proves that the proposed algorithm can find the best matched tourist attractions for tourists and the hotels with the lowest tour route cost based on the constraint conditions. Compared to the suboptimal hotels, the route costs are reduced by 5.67% and 9.63%, respectively. Compared to the hotel with the highest route cost, it reduces the travel costs by 29.23%. Compared with the two commonly used recommendation methods, the UCFR (user-based collaborative filtering recommendation) and ICFR (item-based collaborative filtering recommendation), the proposed CSIDR (CS-IDIANA recommendation) has a higher accuracy and recall rate. [ABSTRACT FROM AUTHOR]

Reasonable districting plays an important role in the patrolling process. In this paper, workload attributes are considered, and a mixed integer programming model is developed to solve the street patrol districting problem (SPDP). The improved spectral clustering algorithm named spectral clustering algorithm based on the road network (SCRn) and simulated annealing algorithm (SA) are combined. This results in a hybrid algorithm called SCRn-SA. The SCRn-SA algorithm is tested on small examples and real instances in Zhengzhou, China. The experimental results show that the proposed algorithm is effective for solving SPDP. It has better performance when compared to other advanced algorithms. [ABSTRACT FROM AUTHOR]

High-quality urban land-use maps are essential for grasping the dynamics and scale of urban land use, predicting future environmental trends and changes, and allocating national land resources. This paper proposes a multisample "voting mechanism" based on multisource data and random forests to achieve fine mapping of urban land use. First, Zhengzhou City was selected as the study area. Based on full integration of multisource features, random forests were used to perform the preliminary classification of multiple samples. Finally, the preliminary classification results were filtered according to the "voting mechanism" to achieve high-precision urban land-use classification mapping. The results showed that the overall classification accuracy of Level I features increased by 5.66% and 14.32% and that the overall classification accuracy of Level II features increased by 9.02% and 12.46%, respectively, compared with the classification results of other strategies. Therefore, this method can significantly reduce the influence of mixed distribution of land types and improve the accuracy of urban land-use classification at a fine scale. [ABSTRACT FROM AUTHOR]

The metro network plays a vital role in the urban transportation system. However, the metro network is easily damaged by humans and natural disturbances. This can cause serious economic damage, such as the suspension of metro station operations and line disruptions. Therefore, we conducted this study in order to minimize the loss caused by the damage to the metro network and improve the performance of the network after recovery. Based on the cascading failures of metro networks, this paper proposes a recovery model for metro networks considering the value of time. Then, considering the time value, a new node importance measure is proposed using the determination of maintenance priorities. The maintenance priorities of nodes with different importance values are investigated to minimize network losses. Lastly, the applicability of the method is verified by a metro network in Zhengzhou city. [ABSTRACT FROM AUTHOR]

Transit Signal Priority (TSP) is a system designed to grant right-of-way to buses, yet it can lead to delays for private vehicles. With the rapid advancement of network technology, self-driving buses have the capability to efficiently acquire road information and optimize the coordination between vehicle arrival and signal timing. However, the complexity of arterial intersections poses challenges for conventional algorithms and models in adapting to real-time signal priority. In this paper, a novel real-time signal-priority optimization method is proposed for self-driving buses based on the CACC model and the powerful deep Q-network (DQN) algorithm. The proposed method leverages the DQN algorithm to facilitate rapid data collection, analysis, and feedback in self-driving scenarios. Based on the arrival states of both the bus and private vehicles, appropriate actions are chosen to adjust the current-phase green time or switch to the next phase while calculating the duration of the green light. In order to optimize traffic balance, the reward function incorporates an equalization reward term. Through simulation analysis using the SUMO framework with self-driving buses in Zhengzhou, the results demonstrate that the DQN-controlled self-driving TSP optimization method reduces intersection delay by 27.77% and 30.55% compared to scenarios without TSP and with traditional active transit signal priority (ATSP), respectively. Furthermore, the queue length is reduced by 33.41% and 38.21% compared to scenarios without TSP and with traditional ATSP, respectively. These findings highlight the superior control effectiveness of the proposed method, particularly during peak hours and in high-traffic volume scenarios. [ABSTRACT FROM AUTHOR]

Green and high-efficiency water resource utilization patterns hold paramount importance in promoting sustainable economic and social development, as well as in attaining the goal of carbon neutrality. Most research on water utilization efficiency have taken a general perspective to quantify it, neglecting independent relationships and green effects among water use sectors. This study proposed an integrated measurement model of green water resource utilization efficiency (GWRUE), combined with the carbon dioxide emission equivalent analysis method of water resource behaviors, and constructed an input–output indicator system of GWRUE from four dimensions: domestic, industrial, agricultural, and ecological water. The aim is to achieve the measurement of GWRUE towards carbon neutrality. In this paper, 18 cities in Henan Province were used as instances to carry out the study. The results show that (1) The CO2 emission equivalent from multiple water use sectors in Henan Province showed a tendency of fluctuating reduction during the study period, from a peak of 21,090,100 tons in 2012 to a low of 12,351,900 tons in 2021, with large spatial variations, and the CO2 emission effect existed in most cities, with Zhengzhou being the highest. (2) The GWRUE of domestic, industrial, and agricultural water in Henan Province and 18 cities exhibited an overall upward trend, while that of ecological water presented a downward trend and was at the lowest level among the four sectors. (3) Consolidated GWRUE in Henan Province tended to decrease and then increase; its value was 0.512 in 2011, 0.448 in 2017, and 0.586 in 2021, and most of its cities were at a Medium level. The findings of this study can serve as a theoretical and practical basis for improving the level of green and efficient utilization of water resources, as well as offer references for relevant water use sectors to formulate CO2 emission reduction policies. [ABSTRACT FROM AUTHOR]

Electric Taxis (ETs) are the most favored alternatives to Gasoline Taxis (GTs) in cities that aim to reduce environmental pollution. How to develop a reasonable scale on which GTs are substituted by ETs remains a challenge to governments due to the dynamics and complexity of the taxi system. To address this challenge, this paper develops a discrete-event-based simulation framework to simulate participants in the system and estimate the results under different substitution scales, which are helpful to understanding the status changing law of entities under different substitution scales, such as the operating indices of ETs, the unsatisfied travel requirements of passengers, and the usage state of charging facilities. The framework abstracts the behavioral process of ETs into three elements, namely, entity, behavior, and event. The entities are constructed from the information derived from the trajectory data. The behaviors are defined by rules following behavioral logic under anxiety psychology, which is caused by the limited range of ETs. The events are triggered based on rules from reality. With the help of this framework, a multi-objective optimization model is developed to obtain the optimal substitution scale of GTs in the case study area of Zhengzhou City. Overall, the approach could provide a practical tool to address this challenge, which could support further studies of the effect of ETs on urban taxis. [ABSTRACT FROM AUTHOR]

The rapid urbanization and population growth in China have brought the issues of social equity and justice to the forefront. The supply and layout of public service facilities play a crucial role in determining the residents' quality of life and have become a significant factor triggering social equity and justice concerns. This study took Zhengzhou's urban core as an example. From the perspectives of regional equality, spatial equity, and social justice, the service area analysis and Gaussian two-step floating catchment area method were used to analyze the public service facilities' layout situation and the equity and justice issue and to discuss the causes of the current situation. The study found that the social equity and justice of public facilities in Zhengzhou's urban core were more prominent. The accessibility of public facilities inside and outside the 3rd ring road of the urban core exhibited marked differences, indicating a need for improvement in regional equality and spatial equity. Vulnerable groups lacked special care and public facilities lacked justice. Combined with the development process of urbanization in Zhengzhou, this paper argued that this was closely related to the government's public policies. [ABSTRACT FROM AUTHOR]

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In view of the problems in traditional geological modeling methods, such as the insufficient utilization of geological survey data, the inaccurate expression of a stratigraphic model, and the large amount of model data, a 3D geological model cannot be smoothly loaded and rendered on the web end. In this paper, a 3D geological implicit modeling method of regular voxel splitting based on hierarchical interpolation data is proposed. This method first uses the boreholes and geological section data from a geological survey for data conversion and fusion, compares the applicability of different interpolation algorithms through cross-validation research, and uses the best fitting algorithm to interpolate and encrypt discrete points in the formation. Then, it constructs the regular voxels, designs five different regular voxel split types, and divides the voxels. In addition, the data structure design of the voxel split model is implemented, and the irregular voxel metadata structure is analyzed and displayed through Three.js. Using this method, based on the survey data of an area in Zhengzhou, the global workflow from data processing to model construction and visualization is demonstrated. The experimental results show that the model can integrate multisource hierarchical interpolation data; express different stratum structures accurately and smoothly, and can realize the rendering, spatial query and analysis of the internal information of a geological body in a browser. [ABSTRACT FROM AUTHOR]

In order to study and forecast extreme weather, a comprehensive and systematic analysis of the spatial and temporal relationship between Precipitable Water Vapor (PWV), predicted by Numerical Weather Predication (NWP) data, and precipitation, is necessary. The goal of this paper was to study the temporal and spatial relationship between PWV and precipitation during the so-called 'July 20' (18–21 July 2021) heavy rainstorm in Zhengzhou. Firstly, the PWV data provided by 120 radiosonde stations uniformly distributed throughout the world, and two IGS stations in China, in 2020, was used to evaluate the accuracy of PWV estimation by ERA5 and MERRA-2 data, and the factors affecting the accuracy of NWP PWV were explored. Secondly, ERA5 PWV and the precipitation data of six meteorological stations were used to qualitatively analyze the relationship between PWV and precipitation during the 'July 20' heavy rainstorm in Zhengzhou. Finally, a quantitative study was conducted by an eigenvalue matching method. The main experimental results were as follows. Compared with MERRA-2 PWV, the accuracy of ERA5 PWV was slightly higher. Latitude, altitude and season were the influencing factors of the NWP PWV estimation accuracy. The change trend of ERA5 PWV was consistent with both 24 h cumulative precipitation and surface precipitation during the 'July 20' heavy rainstorm in Zhengzhou. The average optimal matching degree and optimal matching time between NWP PWV and surface precipitation during the 'July 20' heavy rainstorm in Zhengzhou was 56.6% and 3.68 h, respectively. The maximum optimal matching degree was 80.3%. The spatial–temporal relationship between NWP PWV and surface precipitation was strong. [ABSTRACT FROM AUTHOR]

Partial cable-stayed bridges have the advantages of high rigidity, good economy and convenient construction. In recent years, they have been widely used in high-speed railway, but most of them are two-tower structures. In this paper, based on the main bridge of Ji'nan Yellow River Bridge on Zhengzhou-Ji'nan Railway, the structural system, side-to-middle span ratio and key parameters of beam-tower-cable are analyzed and studied for the long-span, five-tower, four-span and large-span partial cable-stayed bridge on high-speed railway. Through comprehensive comparison and study, the structure system of tower pier consolidation is selected for the Yellow River Bridge, which has the advantages of partial release of temperature force, bridge stiffness and track surface irregularity index to meet the requirements of ballastless track on high-speed railway. Vibration-reducing and isolation measures can be adopted for beam section, effectively reducing seismic force and improving overall economy of bridge. The main bridge uses a smaller ratio of mid-span at the edge to meet the requirement of no auxiliary span for flood control, and can effectively reduce the corner at the end of the beam, avoiding the increase of the investment of the whole bridge due to the use of large girder height. When the height of the tower is 38 m, the increase of the height of the tower can significantly reduce the internal force of the beam, but the deformation under temperature load will increase accordingly. Therefore, the selection of the height of the tower should take into account the structural forces and the requirements of track irregularity. AT - 61 cable is used. Increasing cable size has little effect on bridge rigidity, but it can significantly reduce beam bending moment, but increase beam irregularity and residual creep deformation. [ABSTRACT FROM AUTHOR]

As a key factor in the flood damage assessment process, the damage ratio is defined as the ratio of the potential damage value to the total risk assets at a certain inundation depth. Spatial variability of flood‐bearing elements caused spatial heterogeneity, local correlation and neighborhood non‐stationarity to the damage ratio. Thus, it is challenging to scientifically and rationally measure the damage ratio. In this study, a modeling framework of stochastic flood damage assessment functions was established to measure triple uncertainties. First, based on the maximum likelihood estimation method, migration data of the flood damage ratio were constructed as the beta distribution by heterogeneous multi‐attribute analogy. Then, the Markov chain Monte Carlo method, combined with a variant sliding window method, is used for sampling to generate spatially distributed samples. In addition, three risk factors were integrated grid by grid to assess flood damage. By taking the Jinshui District of Zhengzhou City in China as an example, economic losses during the 1%, 2%, 5% and 10% annual exceedance probability (AEP) floods were assessed, respectively. The results show that the economic losses showed a significant increasing trend with AEP. The optimal domain scales for industrial, commercial, residential and public service land uses were 19, 14, 25 and 32 m, respectively, and also varied with different AEP floods. The model was effectively verified by simulating and comparing historical data of the "7·20" flood event in Zhengzhou, China. This study aims to provide feasible ideas for uncertainty research of damage assessment methods. Plain Language Summary: The damage ratio serves as the link between flood hydrological elements and damages and has an indispensable role in quantifying flood risks. However, the spatial variability of flood‐bearing elements leads to three kinds of spatial uncertainties in damage ratios: spatial heterogeneity, local correlation and neighborhood non‐stationarity. Thus, in this paper, a stochastic flood damage assessment model considering multiple uncertainties was proposed and it is found that optimal domain scales were inconsistent for different annual exceedance probability flood events and different land uses. The model was effectively verified by simulating and comparing historical data of the "7·20" flood event in Zhengzhou, China. Key Points: Accurately quantifying flood damage ratios is a challenge due to the link between flood hydrological elements and lossesSpatial variability of flood‐bearing components caused triple spatial uncertainties to damage ratiosDifferent land uses and flood events with different annual exceedance probabilities exhibited inconsistent optimal domain scales [ABSTRACT FROM AUTHOR]

The premise of the large-scale operation of electric buses corresponds to efficient charging service guarantees. Recent research on charging stations mainly aims to obtain the construction location and construction sequence through optimization methods or decision-making methods. This research has considered the aspects of geography, charging efficiency, economic efficiency, and emergency response capacity. The increase of charging stations will lead to competition among charging stations, unbalanced use of charging facilities, and unnecessary loss of electricity to the power grid. In fact, few studies pay attention to the actual operation of existing charging stations. Therefore, it is necessary to establish a scientific, comprehensive, and efficient charging services evaluation framework to support the actual operation of charging stations. Based on the analytic hierarchy process (AHP), this paper designs a multi-level indicator evaluation framework, which includes 6 first-level indicators and 20 s-level indicators. The first-level indicators are cutting peak and filling valley (A1), location and scale (A2), intelligent technology (A3), equipment efficiency (A4), operating income (A5), and reliability (A6). Through the questionnaire survey of ten experts in related fields, we understood the importance and attention of these indicators. The results show that the weights of indicators of location and scale index (A2) and reliability (A6) are high, which are 0.2875 and 0.2957, respectively. The least concerned indicator is equipment utilization efficiency (A4), at a weight of 0.0531. According to the actual data of charging stations in Zhengzhou, China, the comprehensive competitiveness of several charging stations is evaluated by the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS). The result shows that station 1 has the highest comprehensive competitiveness, followed by station 2 and station 7. The evaluation framework proposed in this paper comprehensively considers a variety of factors. The combination of AHP and TOPSIS can reduce the uncertainty in experts' evaluation of the service of the charging station. [ABSTRACT FROM AUTHOR]

The geographical locations of smart devices can help in providing authentication information between multimedia content providers and users in 5G networks. The IP geolocation methods can help in estimating the geographical location of these smart devices. The two key assumptions of existing IP geolocation methods are as follows: (1) the smallest relative delay comes from the nearest host; (2) the distance between hosts which share the closest common routers is smaller than others. However, the two assumptions are not always true in weakly connected networks, which may affect accuracy. We propose a novel street-level IP geolocation algorithm (Corr-SLG), which is based on the delay-distance correlation and multilayered common routers. The first key idea of Corr-SLG is to divide landmarks into different groups based on relative-delay-distance correlation. Different from previous methods, Corr-SLG geolocates the host based on the largest relative delay for the strongly negatively correlated groups. The second key idea is to introduce the landmarks which share multilayered common routers into the geolocation process, instead of only relying on the closest common routers. Besides, to increase the number of landmarks, a new street-level landmark collection method called WiFi landmark is also presented in this paper. The experiments in one province capital city of China, Zhengzhou, show that Corr-SLG can improve the geolocation accuracy remarkably in a real-world network. [ABSTRACT FROM AUTHOR]

Regional land-use change is the leading cause of ecosystem carbon stock change; it is essential to investigate the response of LUCC to carbon stock to achieve the strategic goal of "double carbon" in a region. This paper proposes a residual network algorithm, the Residual Multi-module Fusion Network (R-MFNet), to address the problems of blurred feature boundary information, low classification accuracy, and high noise, which are often encountered in traditional classification methods. The network algorithm uses an R-ASPP module to expand the receptive field of the feature map to extract sufficient and multi-scale target features; it uses the attention mechanism to assign weights to the multi-scale information of each channel and space. It can fully preserve the remote sensing image features extracted by the convolutional layer through the residual connection. Using this classification network method, the classification of three Landsat-TM/OLI images of Zhengzhou City (the capital of Henan Province) from 2001 to 2020 was realized (the years that the three images were taken are 2001, 2009, and 2020). Compared with SVM, 2D-CNN, and deep residual networks (ResNet), the overall accuracy of the test dataset is increased by 10.07%, 3.96%, and 1.33%, respectively. The classification achieved using this method is closer to the real land surface, and its accuracy is higher than that of the finished product data obtained using the traditional classification method, providing high-precision land-use classification data for the subsequent carbon storage estimation research. Based on the land-use classification data and the carbon density data corrected by meteorological data (temperature and precipitation data), the InVEST model is used to analyze the land-use change and its impact on carbon storage in the region. The results showed that, from 2001 to 2020, the carbon stock in the study area showed a downward trend, with a total decrease of 1.48 × 10 7 t. Over the course of this 19-year period, the farmland area in Zhengzhou decreased by 1101.72 km 2 , and the built land area increased sharply by 936.16 km 2 . The area of land transfer accounted for 29.26% of the total area of Zhengzhou City from 2001 to 2009, and 31.20% from 2009 to 2020. The conversion of farmland to built land is the primary type of land transfer and the most important reason for decreasing carbon stock. The research results can provide support, in the form of scientific data, for land-use management decisions and carbon storage function protections in Zhengzhou and other cities around the world undergoing rapid urbanization. [ABSTRACT FROM AUTHOR]

Urban road networks have promoted high-quality travel for residents by increasing connectivity and intelligence. But road congestion has not been effectively alleviated, causing a loss of time and energy. At present, the recovery of urban road networks mainly considers removing the failed edges. Considering the recovery cost and time, it is important to take active maintenance behavior to restore these networks. One of the key problems is dispatching traffic workers reasonably to achieve timely maintenance. In this paper, a flow-distribution-based process and execution (FD-PE) model is established for solving congestion. The maintenance centers (MC) study the reasons for and spread of congestion by edge flow. Based on the genetic algorithm (GA), two models of maintenance for urban road networks are developed, which include a single MC-centered dispatching plan and the co-scheduling of MCs. Both models aim at minimizing recovery time and allocating maintenance resources. The road network in Zhengzhou is borrowed as a case to explain the feasibility of the proposed models. The results show that on the premise of dividing network regions, it is reasonable to take a single MC to recover congestion. Compared with a single MC, the co-scheduling of MCs may save more time. [ABSTRACT FROM AUTHOR]

Since the reform and opening up, the prosperity of culture has always been the strong desire of the party and the country, and repeatedly put forward the goal of improving the public cultural service system (PCSS), requiring priority development of infrastructure construction related to the vital cultural interests of the people. Urban cultural facilities (UCF) are an important material basis in the cultural service system. The essential assurance for achieving the goal of developing a PCSS that covers the entire community is to improve the layout of cultural facilities (CF) and to allocate CF in a scientific and reasonable manner. This research examines the geographical layout characteristics of CF in Xiamen using POI data from libraries, art galleries, and museums crawled by Baidu API and spatial statistical tools such as ArcGIS. Taking the interest points of cultural promote serving residents as research objects, the advancement of spatial pattern of CF in Zhengzhou in 2007 and 2017 was quantitatively analyzed by using standard deviation ellipse and kernel density analysis. The paper compares and analyzes the location distribution characteristics of museums, libraries, cultural centers, art galleries and theaters from two aspects of macro spatial form and microgathering center. Residents' behavioral characteristics are introduced to examine the influence on the spatial form of CF, and appropriate suggestions are made for the planning and development of CF in Zhengzhou, based on large-scale field survey data and geographical detectors. This article, on the analysis of the state and international public facilities location layout on the basis of optimization study, starting from the present circumstances of urban public sports facilities layout, puts forward the geographic information system (GIS) technology and local approximation (LA) model is introduced into urban public sports service facility location, using DNSCAN network analysis function of urban public sports facilities in site selection and layout optimization, Provide a new method for site selection of sports facilities. And the actual case analysis, in order to provide a reference for the future location layout of public service facilities. Zhengzhou cultural resources through the establishment of GIS database, investigation, cultural needs, put forward the planning should not only include public CF, CF planning should also include the cultural heritage, cultural creative industry, and put forward the development strategy of the construction of the overall urban culture network, realize the cultural space planning and career planning, the fusion of the culture industry planning. [ABSTRACT FROM AUTHOR]

Exploring urban land use change is a classical problem in urban geography. Taking Zhengzhou as an example, this paper analyzes the spatial and temporal characteristics and driving factors of urban land use change, and simulates the spatial pattern of urban land use in the future. The results of the study show that the land use types in Zhengzhou city were mainly farmland and construction land, the area of forestland, grassland, water area, and unused land was smaller, and the main land use change was the transformation of farmland into construction land. The accuracy check of the simulated land use type data in 2020 showed that the kappa coefficient reached 0.9445, which met the accuracy requirement. Then, according to the predicted land use data in 2025, it was found that the area of grassland, construction land, and water area may have decreased, and the area of farmland, forestland and unused land may have increased. Based on the driving force analysis of land use changes, its prediction results can provide an important reference basis for the formulation and planning of policies related to urban construction. [ABSTRACT FROM AUTHOR]

High energy consumption is an increasingly serious problem for air conditioners in mobile communication base stations, and a composite system of the air conditioning and the heat pipe is proposed to solve the problem. The experimental data obtained in Zhengzhou City elucidated the high efficiency in energy saving. The system offers a new opportunity for wide applications in outdoor communication cabinets. [ABSTRACT FROM AUTHOR]

As new urbanization constantly develops, the county economy plays a vital role between country and city, and high economic resilience is necessary to support and safeguard for smooth functioning of the county development. The paper constructs the index system of county economic resilience in Henan Province from three dimensions: risk resistance ability, self-stability, and sustainable development ability, and to empirically analyze the economic resilience of 104 counties and cities in the province from 2013 to 2020 using the entropy weight-normal cloud model. The results show that Henan counties' economic resilience increases slowly over time and decreases spatially from the center to the surrounding region, with Zhengzhou as the main center and Luoyang and Sanmenxia as the subcenter; risk resistance ability and self-stabilization are more influential than the sustainable development ability; the key indicators affecting economic resilience are GDP per capita, retail sales of social consumer goods per capita, financial self-sufficiency rate, education expenditure per capita, and population mobility. Therefore, the counties in Henan should find the right positioning to improve economic resilience; central cities such as Zhengzhou and Luoyang should play their strong functions, while strengthening support for peripheral counties. [ABSTRACT FROM AUTHOR]

As an important component of bike-sharing (BS) users, the travel behavior of college students and office workers is important to the promotion of BS within Chinese cities. To explore the influencing factors for the behavioral intentions of BS, this paper makes a different analysis between the two groups. Based on the theory of planned behavior, and using environmental awareness as an extended variable, a BS travel intention model was developed. A total of 676 valid questionnaires were collected and analyzed from college students and office workers in Zhengzhou. The results indicate that attitude, subjective norms, perceived behavior control, and environmental awareness have a positive impact on the behavioral intentions of BS. However, the influence degree of each variable is different between the two groups. Perceived behavior control, including travel time, travel cost, and cycling difficulty, has the greatest impact on BS behavioral intention for college students. Meanwhile, subjective norms, including policy and media publicity, has the most significant impact on BS behavioral intention for office workers. The impact of environmental awareness on college students' use of BS is higher than that of office workers. We also found that undergraduates use BS more frequently than postgraduates. The findings provide the clear influence factors on behavioral intentions of BS between college students and office workers, that can help policy optimization in terms of bike-sharing systems, giving some suggestion for an approach devoted to deepen the individual-context interactions. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Irrigation & Drainage is the property of Journal of Irrigation & Drainage Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Small curved metro shield tunnels located in fine sand layers are sensitive to the response of horizontal and vertical cyclic loads from train operations, especially for centrifugal horizontal loads. The majority of Zhengzhou's strata are dominated by this geological composition. Therefore, the dynamic response of the fine sand layer under the train vibration load will lead to the settlement of the sand layer, which brings great hidden danger to the train operation. Long-term pore water monitoring was carried out in this paper, and the use of MIDAS-GTS (Multi-candidate Iterative Design with Adaptive Selection) finite element calculation platform to establish the metro ballast-lining-soil coupling dynamic model for mutual verification. The variation patterns of pore water pressure and super pore water pressure during train operation and the vibration response pattern of the soil layer around the tunnel were investigated. The results suggest that: (1) The pore and excess pore water pressures generated at the start of vibration are not easily dissipated and transferred, making them larger in the early stages of train operation. In contrast, the fine-grained powdered sandy soil has a small amount of clay particles, giving strength and cohesion to the soil layer. Vibrating hole pressure and excess pore water pressure stabilize with the train at a later stage; (2) The low probability of liquefaction in the silt layer surrounding the tunnel; (3) Under vibrating loads, areas of significant soil settlement are concentrated on the soil surface, on the upper side of the tunnel in the silty sand layer and at the bottom 3 m of the tunnel, however, its low variation in settlement has a low impact on the tunnel. [ABSTRACT FROM AUTHOR]

Copyright of Advances in Atmospheric Sciences is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Intensive land use (ILU) is a multi-objective optimization process that aims to simultaneously improve the economic, social, and ecological benefits, as well as the carrying capacity of the land, without increasing additional land, and evaluation of the ILU over long time series has a guiding significance for rational land use. To tackle inefficient extraction of information, subjective selection of dominant factor, and lack of prediction in previous evaluation studies, this paper proposes a novel framework for evaluation and analysis of ILU by, first, using Google Earth Engine (GEE) to extract cities' built-up land information, second, by constructing an index system that links economic, social and ecological aspects to evaluate the ILU degree, third, by applying Geodetector to identify the dominant factor on the ILU, finally, by using the S-curve to predict the degree. Based on the case study data from northern China's five fast-growing cities (i.e., Beijing, Tianjin, Shijiazhuang, Jinan, Zhengzhou), the findings show that the ILU degree for all cities has increased over the past 30 years, with the highest growth rate between 2000 and 2010. Beijing had the highest degree in 2018, followed by Tianjin, Zhengzhou, Jinan, and Shijiazhuang. In terms of the time dimension, the dominant factor for all cities shifted from the output-value proportion of secondary and tertiary industries in the early stage to the economic density in the late stage. In terms of the space dimension, the dominant factor varied from cities. It is worth noting that economic density was the dominant factor in the two high-level ILU cities, Beijing and Tianjin, indicating that economic strength is the main driver of the ILU. Moreover, cities with high-level ILU at the current stage will grow slowly in the ILU degree from 2020 to 2035, while Zhengzhou and Jinan, whose ILU has been in the midstream recently, will grow the most among the cities. [ABSTRACT FROM AUTHOR]

For the prediction of economic expenses involved in construction industry, cost estimation has become an important aspect of construction management for the prediction of economic expenses and successful completion of the construction work. Cost analysis is crucial and require expertise for accurate and comprehensive estimation. In order to effectively improve the accuracy of construction project cost, this paper establishes an estimation model based on gray BP neural network. It combines the MATLAB toolbox for program design, and learns and tests the input and output of training samples. This article determines the application of grey system theory to optimize the estimation model of Back Propagation (BP) neural network. The viability of the method established in this article, is tested by collecting the engineering cost data in Zhengzhou city and comparing between the standard BP neural network and the gray BP neural network methods. The results show that the average error of the gray system theory optimized BP neural network model designed in this paper is 2.33%. The gray BP neural network model studied in this paper can not only quickly estimate the project cost, but also has high accuracy rate. The outcomes obtained establishes a model with scientific and reasonable construction project cost estimation. [ABSTRACT FROM AUTHOR]

Near-zero carbon emission power (NZCEP) plants, consisting of gas-fired units; wind turbines; power-to-gas (P2G); and carbon capture, utilization and storage (CCUS) systems, have recently received a lot of attention due to their enormous benefits in reducing carbon emissions and increasing the consumption of renewable energy. However, a complex environment of interest and a combination of risks makes their development very slow. This paper establishes a risk analysis framework for NZCEP considering multi-stakeholder participation. Firstly, a synthetic risk factor system was constructed based on stakeholders' interests. Subsequently, interval type II trapezoidal fuzzy numbers were used and final weights were calculated from both subjective and objective aspects. Finally, we applied an acronym in Portuguese of the interactive and multi-criteria decision-making (TODIM) method to site selection to achieve a balance of interests of all stakeholders. In addition, a case study was conducted. The case result demonstrates that Zhengzhou in Henan Province is the best choice for a NZCEP power plant. A further finding is that government plays an important role in the development of NZCEP plants, with site selection results being the most sensitive to changes in the government's risk appetite. Moreover, human resources are an important factor in the siting of an NZCEP plant. [ABSTRACT FROM AUTHOR]

Exploring protected area (PA) siting from a biodiversity perspective is critical in mitigating human impacts on ecosystems. This paper used the MaxEnt model to predict the geographic distribution patterns of wetland species in Zhengzhou and the environmental factors affecting species' habitat selection. Environmental variables were screened by correlation analysis to avoid affecting the prediction results due to overfitting of the model. The AUC value of the training set of the model ROC curve was above 0.8, and the prediction accuracy was high. The prediction results showed that the only nature reserve in Zhengzhou, Yellow River Wetland Nature Reserve, currently covers only 10.25% of the total area of the high suitability areas for plants and 17.54% of the high suitability habitat areas for waterfowl in the whole area of Zhengzhou. The potential suitability areas of wetland species outside the reserve can provide a basis for site selection for wetland conservation planning in Zhengzhou. It was found that the geographic distribution of wetland species in Zhengzhou is constrained by the distribution of water bodies, bioclimatic variables, land cover, and population density. [ABSTRACT FROM AUTHOR]

Underground commercial buildings have received increasing attention as an emerging place of consumption. However, previous studies on underground commercial buildings have mainly focused on the impact of a specific environment on comfort or energy consumption. Few studies have been conducted from the perspective of functional use. The purpose of this paper is to investigate, in terms of functional angles, the indoor thermal environment and air quality of an underground commercial building in Zhengzhou, China, and put forward an optimal control strategy of ventilation organization. The results showed that the relative humidity of the underground shopping mall was generally above 60%, and the average temperature of 29.1 °C led to a thermal comfort problem in the catering area in summer. Meanwhile, the concentration of CO2 exceeded the allowed figures during the peak of the customer flow rate, and PM2.5 concentration in the catering area also exceeded the standard, by 43.3% and 33.3%, respectively. Furthermore, to solve the indoor thermal environment and air quality problems found in the field measurements, this study assessed the air distribution by adopting three different air supply schemes for the catering area. Optimization results showed that compared with the ceiling supply, the side supply scheme kept the air temperature 0.4 °C cooler in summer and 0.5 °C warmer in winter. The temperature uniformity increased by 5.4% and 3.7%, and the velocity uniformity increased by 6.5% and 8.8%, respectively. This study can provide theoretical support for thermal environment construction and ventilation organization control of underground commercial buildings. [ABSTRACT FROM AUTHOR]

To address the two problems of unclear delineation of sub‐catchment and complicated and cumbersome parameter rate determination in the Storm Water Management Model (SWMM), this study proposes a rapid construction method of SWMM based on the principle of single urban functional area combined with K‐means clustering algorithm, The research area is the southern part of Jinshui District, Zhengzhou City. The Hydrological Response Unit (HRU) contains only a single urban functional area, divided by combining the natural and social attributes of the urban surface. Calibrated uncertain parameters from 76 papers were selected as samples, and the K‐means clustering algorithm was used to cluster and calculate the parameter values, to improve the SWMM model, selecting three typical rainfall runoff processes for validation application. The results show that simulated runoff is consistent with measured runoff trends, with the NSE and R2 value scores of the flow processes of the three floods above 0.86 and the, locations and numbers of flooded nodes are consistent with the actual research. This provides a new idea and technical support for the construction of urban flood models in flood prevention and mitigation. The relevant results can provide scientific decision‐making reference for urban flood forecasting and warning. [ABSTRACT FROM AUTHOR]

To overcome the limitations of long-term prediction of PM2.5 concentration, a multi-factor information flow causality analysis method is used to screen suitable meteorological and air pollutant-related factors and concatenate them with a PM2.5 sequence as the dataset. A modal decomposition algorithm is used as a module to be integrated into the autoformer (transformer improved with autocorrelation mechanism) model to improve it, and the modal autoformer (empirical modal decomposition combined with autoformer) is proposed. The constructed model decomposes the sequence into several components by using the modal decomposition module and uses the self-correlation mechanism and decomposition structure to decompose and extract features of different components at the time-feature level. Based on the matching method, the model is adjusted for different component features to improve the long-term prediction effect. The model is applied to three cities in Henan Province, Zhengzhou, Luoyang, and Zhumadian, as examples for experiments, and gated neural unit (GRU), informer, autoformer, and modal GRU (empirical modal decomposition combined with GRU model) are constructed for comparative verification. The results show that the modal autoformer can better cope with the complex characteristics of long-term prediction of the PM2.5 time series, has strong spatial adaptability and that its various indicators are optimal for the three cities, with R2 values being all above 0.96, where the highest is 0.987 in Zhengzhou; MAPE (Mean absolute percentage error) values all being less than 10, where the best is 7.602 in Zhumadian; and MAE (Mean absolute error) values all being less than 4. The prediction effect is stable enough, showing its feasibility and adaptability in long-term prediction. [ABSTRACT FROM AUTHOR]

Due to the insufficient number and uneven distribution of urban rainfall stations, research on urban flooding disasters is limited. With the development of big data research, many scholars have applied big data to natural disaster research. In this paper, we analyzed the reliability of unstructured data from the urban rainfall patterns studies using the measured rainfall data for Zhengzhou City. First, web crawler technology was used on Sina Weibo, one of China's largest social platforms, to obtain the unstructured data related to rainfall. The fuzzy recognition method was used to analyze the rain patterns of the measured rainfall data and the unstructured data, which verified the reliability of the unstructured data in the analysis of the urban rainfall patterns. Taking Zhengzhou City as an example, it was found that the matching degree of rain pattern recognition results was 45%, between the unstructured data and measured data. This showed that the application of the unstructured data in the analysis of the urban rainfall patterns has a certain degree of reliability. [ABSTRACT FROM AUTHOR]

To achieve the goals of carbon emission-peak and carbon neutrality, the energy conservation problem of subway air-conditioning system has become more and more prominent. Since the load of the subway equipment management room varies obviously with the start and stop of the equipment, the traditional air-conditioning system of constant air volume cannot change the air supply volume of the system, which would cause the waste of the cooling capacity. The air-conditioning system of variable air volume can be used to achieve the air supply on demand for different rooms at different times. This paper builds a simulation platform of the VAV air-conditioning system for a subway station in Zhengzhou and the platform is integrated with the load model of the subway equipment room to achieve on-demand air supply. The simulation platform is used to simulate the control characteristics and air volume characteristics of the VAV system. By adjusting the valve opening of the VAV-box terminal, the demanded air volume of the room is supplied on according to different load demands. The results show that the actual operating air volume basically matches the demand air volume and the deviation is less than 1%. The control effects of room temperature between the constant air volume system and the VAV system are compared. The room temperature with the constant air volume system is decreased to 34 °C, which is lower than the design temperature of 36 °. While, the room temperature with the VAV system can be precisely controlled at 36 °, and the waste of cooling capacity is avoided. [ABSTRACT FROM AUTHOR]