Various Cities In China Research Articles

Item response theory analysis of the Chinese version compulsive shopping scale

Compulsive shopping, a behavioral disorder with significant personal and social repercussions, necessitates reliable assessment tools, especially within different cultural contexts. While several scales exist to measure compulsive buying behavior, there is a lack of validated instruments tailored to the Chinese population. This study aimed to examine the psychometric properties of the Chinese version of the Compulsive Shopping Scale (CSS) using Item Response Theory (IRT). A total of 637 young healthy participants (42.5 % males and 57.5 % females), with a mean age of 21.32 years (SD = 2.06), both undergraduate and postgraduate students, were recruited from various cities in China. Sixty-four participants were retested after a two-week interval to assess test-retest reliability. The results indicated that a one-dimensional factor structure was appropriate. The reliability analyses, including test-retest reliability, ω, α, and λ6 tests, demonstrated good internal consistency. The rating scale model analysis showed infit and outfit MNSQ values between 0.6 and 1.4, indicating a good fit. The item information curve and test information curve indicated a normal distribution of scores. Differential item functioning was observed in two items, suggesting potential gender-related differences. These findings indicate that the Chinese version of the CSS is a reliable and valid instrument for measuring compulsive shopping behaviors in Chinese populations.

Elucidating transport dynamics and regional division of PM2.5 and O3 in China using an advanced network model

Air pollution exhibits significant spatial spillover effects, complicating and challenging regional governance models. This study innovatively applied and optimized a statistics-based complex network method in atmospheric environmental field. The methodology was enhanced through improvements in edge weighting and threshold calculations, leading to the development of an advanced pollutant transport network model. This model integrates pollution, meteorological, and geographical data, thereby comprehensively revealing the dynamic characteristics of PM2.5 and O3 transport among various cities in China. Research findings indicated that, throughout the year, the O3 transport network surpassed the PM2.5 network in edge count, average degree, and average weighted degree, showcasing a higher network density, broader city connections, and greater transmission strength. Particularly during the warm period, these characteristics of the O3 network were more pronounced, showcasing significant transport potential. Furthermore, the model successfully identified key influential cities in different periods; it also provided detailed descriptions of the interprovincial spillover flux and pathways of PM2.5 and O3 across various time scales. It pinpointed major pollution spillover and receiving provinces, with primary spillover pathways concentrated in crucial areas such as the Beijing-Tianjin-Hebei (BTH) region and its surrounding areas, the Yangtze River Delta, and the Fen-Wei Plain. Building on this, the model divided the O3, PM2.5, and synergistic pollution transmission regions in China into 6, 7, and 8 zones, respectively, based on network weights and the Girvan Newman (GN) algorithm. Such division offers novel perspectives and strategies for regional joint prevention and control. The validity of the model was further corroborated by source analysis results from the WRF-CAMx model in the BTH area. Overall, this research provides valuable insights for local and regional atmospheric pollution control strategies. Additionally, it offers a robust analytical tool for research in the field of atmospheric pollution.

How Urban Greening Policy Affects Urban Ecological Resilience: Quasi-Natural Experimental Evidence from Three Megacity Clusters in China

This study examines how urban greening policies affect urban ecological resilience through a quasi-natural experimental analysis of various cities in China. Leveraging the country's large-scale promotion of forest city development, we assess the effectiveness of these policies using differences-in-differences modeling across multiple time periods. The results affirm the positive impact of urban greening on resilience, as designated forest cities demonstrated enhanced resilience levels compared to control cities. Notable disparities were also found among the three major Chinese urban agglomerations - the Yangtze River Delta, Pearl River Delta, and Beijing-Tianjin-Hebei regions - in terms of policy effects. While short-term resilience increased under central government oversight, long-term gains relied more on intercity cooperation within agglomerations. It highlights the limitations inherent within China's "experiment under hierarchy" paradigm but also benefits from regional integration. This study contributes novel insights regarding the dynamic relationship between governance structures and urban ecosystem resilience under authoritarian contexts. Innovatively, we explore how intercity cooperation among urban agglomerations affects the long-term effectiveness of urban ecological governance, thereby contributing to a deeper understanding of the complexities involved in fostering resilient urban ecosystems under such governance models.

An analysis and investigation of the factors affecting the air quality index in various cities in China

With the rapid progress of society, air pollution has gradually become the focus of people's concern, the impact of air pollution is very many factors, including but not limited to natural factors, human factors, geographic factors, etc., this paper is mainly from the natural factors and human factors, to explore its impact on air quality in the past five years, this paper first from the data itself, summarizes the distribution characteristics of the air quality in different regions of China, and then from the temperature and humidity throughout the year, to quantify its impact, and then with the help of time-series methods, to explore the air pollution indicators in the case of de-seasonalization of the air pollution indicators. This paper firstly summarizes the distribution characteristics of air quality in different regions of China from the data itself, then quantifies the impact of temperature and humidity throughout the year, and then explores whether the air pollution indicators satisfy the smooth distribution under the situation of de-seasonalization with the help of time series correlation method. The paper then compares the effects of several anthropogenic factors on the air through the gray correlation method. Finally, the influence of each factor in different parts of the country is summarized to provide reference for future studies.

Spatiotemporal Patterns in the Urban Heat Island Effect of Several Contemporary and Historical Chinese “Stove Cities”

Various cities in China have been identified as “stove cities” either in contemporary or historical times, exposing residents to extremely high temperatures. Existing studies on the heat island effect in stove cities are not representative nationwide. The outdated nature of these studies also significantly diminishes the relevance of their findings. Thus, reassessing the urban heat island (UHI) effect of stove cities is necessary in the context of global climate change and urbanization. This study focuses on seven symbolic and geographically distributed stove cities in China, including Nanjing, Chongqing, Wuhan, Fuzhou, Beijing, Xi’an, and Turpan. Using land surface temperature (LST) data, this study investigates the summer heat island effect from 2013 to 2023 and analyzes changes in the spatial distribution of the heat island effect. This paper utilizes impervious surface data and urban clustering algorithms to define urban and suburban areas. It then examines the evolution and spatial distribution of surface urban heat island intensity (SUHII) over time. Incorporating urbanization variables like population density and urban area, the study analyzes the main factors affecting the heat island effect from 2013 to 2018. We find that all cities continuously expand, with the annual average heat island effect intensifying over the years. With the exception of Beijing, the summer heat island or cool island effects in the remaining six cities show an overall intensification trend. From 2013 to 2018, SUHII has been primarily related to urban expansion and planning layout, with minimal impact from factors such as population density.

The Assessment of Fatty Acid Composition in Deep-Fried Dough Sticks across Five Cities in China in 2020

Objective: To analyze and compare the concentrations and dietary intake of different fatty acids (FAs) in deep-fried dough sticks (Chinese fried bread) across various cities in China. Method: Sixty-one deep-fried dough stick samples were collected from five cities (Beijing, Shijiazhuang, Guangzhou, Chongqing, and Hangzhou), and the contents of FA monomers were determined using gas chromatography. Moreover, the dietary FA intake was estimated. Results: The mean FA concentration was 18.83 g/100 g (maximum, 41.59 g/100 g; minimum, 4.88 g/100 g). Polyunsaturated FAs (PUFAs) accounted for the highest proportion of the total FAs at 41.7% (7.86 g/100 g), followed by monounsaturated FAs (MUFAs) at 30.77% (5.79 g/100 g), saturated FAs (SFAs) at 26.27% (4.95 g/100 g), and trans-FAs (TFAs) at 1.18% (0.22 g/100 g). The Guangzhou deep-fried dough stick samples had a significantly different FA composition than those from the other cities, presenting with the highest concentration of SFAs (8.64 ± 4.74 g/100 g) and lowest concentration of PUFAs (5.01 ± 3.41 g/100 g). Beijing had the highest intake of PUFAs and MUFAs, whereas Guangzhou had the highest intake of SFAs. Conclusion: The contents and intake of saturated and unsaturated FAs in deep-fried dough sticks varied across the five cities in China. These results are useful for comparing the nutritional characteristics of deep-fried dough sticks in the different cities of China, thereby promoting further research on the relationship between deep-fried dough stick consumption and human health.

Does urban air pollution have an impact on public health? Empirical evidence from 288 prefecture-level cities in China

The impact of air pollution on public health is a popular topic among socio-economists and environmental researchers everywhere. Although much research has been conducted on it, the connection between air pollution and public health at the urban scale in China is still not well understood. This study employs a spatial econometric model using panel data from 288 Chinese cities from 2000 to 2021 to explore the spatial impact of air pollution on public health and to investigate regional heterogeneity across regions. The findings indicate that there is a significant spatial correlation between the level of public health and the level of air pollution in various cities in China, and air pollution has spillover effects between these cities; air pollution, as well as GDP per capita, industrial structure, green space per capita, population density, and number of physicians per 10,000 people, all have positive or negative effects on public health; in the eastern, central and western regions, air pollution and the impact of control variables on population mortality are different, from a regional perspective, the impact of air pollution on public health varies significantly from region to region. This study enriches the research on air pollution and public health, and the conclusions obtained have strong practical significance for improving urban air pollution and ensuring residents' health.

A Study on the Marketing Factors of Convention and Exhibition Industry in Tai’an

Purpose - The exhibition industry is a strategic emerging service industry with great development potential in the new economic era, and its role in promoting the development of the national economy is also increasing.
 Design/Methodology/Approach - Construct a new indicator system, classify and analyze the influencing factors and their influencing mechanisms, construct a theoretical model of the influencing mechanisms, evaluate and correct the items measured by variables, and reveal the formation mechanism of the influencing factors.
 Findings - A new indicator system for influencing factors has been constructed, which is classified into core factors (exhibition enterprises and technological innovation), basic factors (resource endowment), and industrial environment factors (government support), revealing the formation mechanism of the impact of factors on the competitiveness of the urban exhibition industry.
 Research Implications - The exhibition industry is related to the material life of the people and their spiritual life. Studying the competitiveness and influencing factors of the urban exhibition industry is beneficial for alleviating the pressure brought by idle exhibition venues and related resources in various cities in China, sharing the responsibility of the Chinese government to continuously improve urban construction, meeting the growing material and cultural needs of the people, and promoting the sustainable development of the exhibition industry.

Dioxin emission modeling using feature selection and simplified DFR with residual error fitting for the grate-based MSWI process

Municipal solid waste incineration (MSWI) with grate technology is a widely applied waste-to-energy process in various cities in China. Meanwhile, dioxins (DXN) are emitted at the stack and are the critical environmental indicator for operation optimization control in the MSWI process. However, constructing a high-precision and fast emission model for DXN emission operation optimization control becomes an immediate difficulty. To address the above problem, this research utilizes a novel DXN emission measurement method using simplified deep forest regression (DFR) with residual error fitting (SDFR-ref). First, the high-dimensional process variables are optimally reduced following the mutual information and significance test. Then, a simplified DFR algorithm is established to infer or predict the nonlinearity between the selected process variables and the DXN emission concentration. Moreover, a gradient enhancement strategy in terms of residual error fitting with a step factor is designed to improve the measurement performance in the layer-by-layer learning process. Finally, an actual DXN dataset from 2009 to 2020 of the MSWI plant in Beijing is utilized to verify the SDFR-ref method. Comparison experiments demonstrate the superiority of the proposed method over other methods in terms of measurement accuracy and time consumption.

Comparison of machine learning and deep learning techniques for the prediction of air pollution: a case study from China

The adverse effect of air pollution has always been a problem for human health. The presence of a high level of air pollutants can cause severe illnesses such as emphysema, chronic obstructive pulmonary disease (COPD), or asthma. Air quality prediction helps us to undertake practical action plans for controlling air pollution. The Air Quality Index (AQI) reflects the degree of concentration of pollutants in a locality. The average AQI was calculated for the various cities in China to understand the annual trends. Furthermore, the air quality index has been predicted for ten major cities across China using five different deep learning techniques, namely, Recurrent Neural Network (RNN), Bidirectional Gated Recurrent unit (Bi-GRU), Bidirectional Long Short-Term Memory (BiLSTM), Convolutional Neural Network BiLSTM (CNN-BiLSTM), and Convolutional BiLSTM (Conv1D-BiLSTM). The performance of these models has been compared with a machine learning model, eXtreme Gradient Boosting (XGBoost) to discover the most efficient deep learning model. The results suggest that the machine learning model, XGBoost, outperforms the deep learning models. While Conv1D-BiLSTM and CNN-BiLSTM perform well among the deep learning models in the estimation of the air quality index (AQI), RNN and Bi-GRU are the least performing ones. Thus, both XGBoost and neural network models are capable of capturing the non-linearity present in the dataset with reliable accuracy.

Classification and determinants of high-speed rail stations using multi-source data: A case study in Jiangsu Province, China

High-speed rail (HSR) stations play a vital role in the HSR system. HSR stations not only facilitate the accessibility of interregional transportation but also stimulate population movements across various cities in China. HSR stations in different cities can vary greatly, and an efficient HSR system requires an in-depth understanding of the interrelations between the related influential factors and spatiotemporal passenger flow patterns of different HSR stations. This study adopts a new scheme for clustering HSR stations based on passengers' arrival and departure time series using mobile phone data in Jiangsu, China. To this end, 71 HSR stations are clustered into 3 classes and the spatiotemporal characteristics of passenger flow at different stations are compared. Finally, a geographically weighted multinomial logit model (GWMNL) is built to explore the influence of the built environment, socioeconomic indicators, and HSR station attributes on the classification results of HSR stations related to the time-varying characteristics of passenger flow. The model results show that the number of entertainment POIs, population, population density, area, GDP and building area are significantly associated with the classification results of HSR stations. Additionally, for HSR stations under the same classification result, these variables also have different effects on them in the geographical dimension. According to these findings, quantitative analysis of the linkages between the passenger flow patterns at different HSR stations and the impacting factors would offer implications for planners and policymakers in HSR station planning and associated urban development.

Is China's international trade exacerbating urban environmental pollution?——A quasi-natural experiment based on the opening of the CHINA RAILWAY Express

The level of international trade liberalization and facilitation between Chinese cities and countries along the route has increased significantly since the opening of the CHINA RAILWAY Express. Increased economic activity is bound to significantly affect environmental quality. However, academic empirical evidence on the effect of international trade on environmental quality is inconsistent. Moreover, there is need to further clarify the specific effect paths. Based on data from various cities in China, this study examines the direction and potential effect mechanisms of China's international trade activities on the environmental status represented by carbon dioxide using the Staggered Differences-in-Differences method, considering the opening of the CHINA RAILWAY Express as an entry point. The opening of the CHINA RAILWAY Express promotes environmental pollution in Chinese cities; this finding still holds after a series of placebo and robustness tests. A study of the mechanism of influence between the two suggests that the opening of the CHINA RAILWAY Express increased environmental pollution at the city level in China by promoting industrial agglomeration and improving green technology innovation. A study based on regional heterogeneity showed that the opening of the CHINA RAILWAY Express insignificantly negatively affected environmental quality in eastern China but significantly increased environmental pollution in the central and western regions. Further examination of the spoke network effect of the environmental pollution effect of the CHINA RAILWAY Express revealed that the opening of the CHINA RAILWAY Express in one city significantly negatively affected the environmental quality of all cities within a distance of 200 km. Although the CHINA RAILWAY Express reduces the environmental quality of cities in China where they are opened, studies using data from 145 countries or regions worldwide show that access to the CHINA RAILWAY Express is beneficial for the improvement of environmental quality in countries and regions along the route. This study explores the environmental effects of international trade from the perspective of the CHINA RAILWAY Express, enriches the relevant studies on the relationship between the two, and proposes new perspectives and conclusions to provide new empirical evidence and policy recommendations in the context of China's planning to build a strong trade nation and accelerate the transition to a low-carbon economy.

Characterizing and Forecasting Urban Vibrancy Evolution: A Multi-View Graph Mining Perspective

Urban vibrancy describes the prosperity, diversity, and accessibility of urban areas, which is vital to a city’s socio-economic development and sustainability. While many efforts have been made for statically measuring and evaluating urban vibrancy, there are few studies on the evolutionary process of urban vibrancy, yet we know little about the relationship between urban vibrancy evolution and sophisticated spatiotemporal dynamics. In this article, we make use of multi-sourced urban data to develop a data-driven framework, U-Evolve , to investigate urban vibrancy evolution. Specifically, we first exploit the spatiotemporal characteristics of urban areas to create multi-view time-dependent graphs. Then, we analyze the contextual features and graph patterns of multi-view time-dependent graphs in terms of informing future urban vibrancy variations. Our analysis validates the informativeness of multi-view time-dependent graphs for characterizing and informing future urban vibrancy evolution. After that, we construct a feature based model to forecast future urban vibrancy evolution and quantify each feature’s importance. Moreover, to further enhance the forecasting effectiveness, we propose a graph learning based model to capture spatiotemporal autocorrelation of urban areas based on multi-view time-dependent graphs in an end-to-end manner. Finally, extensive experiments on two metropolises, Beijing and Shanghai, demonstrate the effectiveness of our forecasting models. The U-Evolve framework has also been deployed in the production environment to deliver real-world urban development and planning insights for various cities in China.

Population agglomeration in Chinese cities: is it benefit or damage for the quality of economic development?

This paper explores the impact of population agglomeration on urban economic development quality in various cities of China. The results show that population agglomeration significantly contributes to the improvement of urban green total factor productivity by increasing population diversification, promoting knowledge spillovers, and reducing pollution emission intensity. Moreover, we find that population agglomeration in type II big cities and type I large cities significantly improves green total factor productivity, while the impact of population agglomeration in metropolises and mega-cities on green total factor productivity is not significant. On the one hand, type II big cities and type I large cities are in the period of rising economic development, the population has not yet reached saturation, and there is still a large demographic dividend space. On the other hand, excessive population agglomeration also brings about "urban diseases" such as population congestion and traffic congestion, especially in the metropolises and mega-cities. Finally, using data on producer services and its sub-sectors, we identify a more significant driving effect of high-end talent agglomeration on green total factor productivity.

The Impacts of Popularization of Electric Vehicles on Urban Air Pollution: Evidence from China

This research explores the impact of popularizing electric vehicles (EVs) on China's urban air pollution or contagion. With the rapid growth of the transportation industry and the increasing concern about air pollution, the Chinese administration has been promoting the use of EVs to mitigate the adverse effects of traditional gasoline-powered vehicles on the environment. Using empirical data collected from various cities in China, this study exploits a difference-in-differences approach to analyze the causal connection between the EV implementation and urban air quality. According to the findings, the increase in EV usage significantly and positively impacts reducing the concentration of air emissions such as PM2.5 and SO2. Moreover, the study also finds that the magnitude of the effect varies across different types of cities with varying levels of economic development and air pollution. This research provides valuable insights into the effectiveness of promoting EVs in reducing urban air pollution in China. It has important implications for policymakers and stakeholders in other countries.

The Significant Factors in Refuse Classification Based on Correlation and Multiple Regression Analysis

With the rapid growth of China's economy, great achievements have been made in various constructions. Meanwhile, huge resources and environmental damage have been paid. To reduce pollution and protect environment, the continuous implementation of mandatory waste classification policy in various cities in China, refuse classification has been a practical problem that tightly related to mankind’s live. In this article, it finds the significant factors that affect the effectiveness of the refuse classification as well as the people’s attitude toward it. Based on the questionnaire, people’s will turn positive as the classification commences and guidance takes quite an important role in the process. Refuse classification is a long-term project beneficial to the country and the people. Contemporarily, the government has been advocating waste classification, but it has not been effectively implemented in the actual operation process. On the basis of in-depth analysis of the problems existing in the implementation of garbage classification, key objects are found to form a green and environment-friendly resource conserving society. These results provide some reference for further garbage classification.

Empirical study on urban sustainable development model based on identification of advantages and disadvantages

Promoting the sustainable development of cities and unifying ecological, economic, and social benefits are of great significance to the long-term development of the country. Taking the macro level as the starting point, this paper constructs a hierarchical identification model of urban personality advantage characteristics from the perspective of sustainable development. To identify, classify and compare the sustainable urban development models, SPSS was used to analyze the weights of the dominant characteristics of various cities in China. First, according to the identification model, the individual advantages of each city are identified hierarchically; Secondly, all feature weights are clustered, and finally, the sustainable development patterns of different cities are discussed according to the clustering results, and relevant countermeasures are proposed. The comparison shows that each city has its advantages and disadvantages in sustainable development, and these cities have not been able to implement the concept and policies of sustainable development well. Given these problems, this paper recommends grasping the main force, gradually solving and improving the weaker links in sustainable development, and reducing the imbalance in development. In the context of sustainable development strategies, the development of Chinese cities in a virtuous circle is of great significance.

Evaluation and driving factors of land use economic efficiency in China's urban agglomerations under the impact of COVID-19 epidemic.

Land is an indispensable factor of production and the basic support for all social and economic activities. The COVID-19 epidemic has a great impact on China's macro-economy and land market. As a unit with a high concentration of economic entities, urban agglomeration is closely related to its land use economic efficiency. Under the impact of epidemic and the rigid constraints of the relative scarcity of land resources, improving the land use economic efficiency is crucial to the sustainable development of urban agglomerations. Taking the 10 major urban agglomerations in China as a case study, this paper constructs a theoretical and empirical analysis framework for the land use economic efficiency and its driving mechanism of urban agglomerations, and measures the land use economic efficiency of urban agglomerations from the aspects of single factor productivity and total factor productivity. The results show that the COVID-19 epidemic has a great impact on the land market of various cities in China's urban agglomerations. Whether single factor productivity or total factor productivity is used to measure land use economic efficiency of urban agglomerations, the driving effects of industrial agglomeration, industrial structure change, technological progress, and transportation infrastructure are all significant. It is necessary to take a series of measures to reform the market-oriented allocation of land elements, and improve a long-term mechanism for the smooth operation of the land market. It is necessary to improve the land use economic efficiency through a combination of industrial agglomeration, industrial structure adjustment, technological progress, and transportation infrastructure.

Effects of COVID-19 on China's civil aviation passenger transport market

COVID-19 has had an unprecedented impact on the civil aviation transportation sector. This study uses COVID-19 statistics and socioeconomic development data for various cities in China, combined with the Moran index and econometric models to analyse the spatial distribution of China's epidemic and civil aviation passenger throughput, as well as the impact of COVID-19 and socioeconomic factors on the civil aviation passenger transport market. We find that COVID-19 spread from Wuhan to the surrounding cities, showing a positive spatial autocorrelation; civil aviation passenger throughput decreased significantly in cities where the virus continued to spread and recurred frequently. Due to the effective prevention and control of the pandemic in China, the domestic passenger transport industry recovered rapidly, while international air passenger services continued to suffer; major cities with high social and economic development still show a large decline in passenger transport, but they are again undertaking most passenger transport services. COVID-19's impact on tourism has affected the civil aviation industry significantly, whose recovery depends on the tourism industry's recovery; this, in turn, is led by regions with a high degree of social and economic development.

Mobile internet-based mixed-reality interactive telecollaboration system for neurosurgical procedures: technical feasibility and clinical implementation.

To increase access to health interventions and healthcare services for patients in resource-constrained settings, strategies such as telemedicine must be implemented for the allocation of medical resources across geographic boundaries. Telecollaboration is the dominant form of surgical telemedicine. In this study, the authors report and evaluate a novel mobile internet-based mixed-reality interactive telecollaboration (MIMIT) system as a new paradigm for telemedicine and validate its clinical feasibility. The application of this system was demonstrated for long-distance, real-time collaboration of neuroendoscopic procedures. The system consists of a local video processing workstation, a head-mounted mixed-reality display device, and a mobile remote device, connected over mobile internet (4G or 5G), allowing global point-to-point communication. Using this system, 20 cases of neuroendoscopic surgery were performed and evaluated. The system setup, composite video latency, technical feasibility, clinical implementation, and future potential business model were analyzed and evaluated. The MIMIT system allows two surgeons to perform complex visual and verbal communication during the operation. The average video delay time is 184.25 msec (range 160-230 msec) with 4G mobile internet, and 23.25 msec (range 20-26 msec) with 5G mobile internet. Excellent image resolution enabled remote neurosurgeons to visualize all critical anatomical structures intraoperatively. Remote instructors could easily make marks on the surgical view; then the composite image, as well as the audio conversation, was transferred to the local surgeon. In this way, a real-time, long-distance collaboration can occur. This system was used for 20 neuroendoscopic surgeries in various cities in China and even across countries (Boston, Massachusetts, to Jingzhou, China). Its simplicity and practicality have been recognized by both parties, and there were no technically related complications recorded. The MIMIT system allows for real-time, long-distance telecollaborative neuroendoscopic procedures and surgical training through a commercially available and inexpensive system. It enables remote experts to implement real-time, long-distance intraoperative interaction to guide inexperienced local surgeons, thus integrating the best medical resources and possibly promoting both diagnosis and treatment. Moreover, it can popularize and improve neurosurgical endoscopy technology in more hospitals to benefit more patients, as well as more neurosurgeons.