Projection Pursuit Research Articles

Resilience Assessment and Influencing Factors Analysis of Water Security System in the Yellow River Basin

The assessment and regulation of water security system resilience (WSSR) are important ways to alleviate water resource crises. On the basis of the three characteristics of resilience, namely, resistance, restoration, and adaptability, an evaluation index system of the WSSR was built for the Yellow River Basin (YRB). A projection pursuit model based on the sparrow search algorithm (SSA-PP model) was constructed to assess the WSSR at the overall and provincial scales from 2009 to 2022. The factors influencing the spatial distribution patterns of WSSR was identified through factor detector and interactive detector techniques. The results revealed that: (1) From 2009 to 2022, the YRB exhibited a rising trend in WSSR, with the western region attaining the peak level, and the eastern region recording the lowest magnitude. (2) the adaptability capacity of most provinces and regions in the YRB tended to decrease to about 1.0, whereas the resistance and restoration capacities tended to increase towards 2.0. (3) Factors relevant to the restoration and adaptability subsystems, such as the development and utilization ratio of water resources and surface water resources (B2 and B3), water resource load index (C1), water consumption per 10,000 yuan of GDP (C8), and total precipitation (A1), significantly affected the WSSR. The interaction between factors exhibited significant enhancement effects on explanatory. Therefore, targeted countermeasures and recommendations were provided to improve the WSSR in the YRB.

Structural resilience disparities in regional city networks under the influence of Typhoon Fitow and COVID-19

The integration of regional city networks plays a pivotal role in the regional development. Assessing and analyzing the structural resilience of these networks holds significance in enhancing regional comprehensive disaster prevention. This study focuses on the Yangtze River Delta, examining its regional city networks encompassing information, economic, transportation, and innovation domains. Utilizing the social network analysis, projection pursuit model based on the genetic algorithm, coupling coordination degree model, coefficient of variation and spatial Gini coefficient, we scrutinized the structural resilience and evolution difference of these networks under different disasters. We found that the structural resilience of economic and transportation networks that depend on infrastructure construction are more limited by geographical distance, and information and innovation networks with weaker physical dependence have stronger structural resilience. The impact of Typhoon Fitow on the structural resilience of individual networks was mainly concentrated in coastal affected cities, while the impact after COVID-19 was mainly in marginal cities. The spatial pattern of the structural resilience of multiple networks shifted from low level equilibrium to agglomeration development. Finally, nodes were identified into three types according to the resilience performance. This research offers a scientific foundation for quantifying regional resilience and formulating network optimization strategies.

Examining the upper frequency limit of dynamic cerebral autoregulation: Considerations across the cardiac cycle during eucapnia.

There are differences within the literature regarding the upper frequency cut-off point of the dynamic cerebral autoregulation (CA) high-pass filter. The projection pursuit regression approach has demonstrated that the upper frequency limit is ∼0.07Hz, whereas another approach [transfer function analysis (TFA) phase approaching zero] indicated a theoretical upper frequency limit for the high-pass filter of 0.24Hz. We investigated how these limits accurately represent the CA upper frequency limit, in addition to extending earlier findings with respect to biological sexes and across the cardiac cycle. Sixteen participants (nine females and seven males) performed repeated squat-stand manoeuvres at frequencies of 0.05, 0.10, 0.15, 0.20 and 0.25Hz, with insonation of the middle and posterior cerebral arteries. Linear regression modelling with adjustment for sex and order of squat completion was used to compared TFA gain and phase with 0.25Hz (above the theoretical limit of CA). The upper frequency limit of CA with TFA gain was within the range of 0.05-0.10Hz, whereas TFA phase was within the range of 0.20-0.25Hz, and consistent between vessels, between sexes and across the cardiac cycle. Females displayed greater middle cerebral artery gain compared with males (all P<0.047), and no phase differences were present (all P>0.072). Although sex-specific differences were present for specific TFA metrics at a given frequency, the upper frequency limit of autoregulation was similar between cerebral conduit vessels, cardiac cycle phase and biological sex. Future work is warranted to determine whether an upper frequency limit exists with respect to hysteresis analyses.

Inspiring Student Entrepreneurship and Innovation.

Background While student entrepreneurial interest is significantlycorrelated with the intention to pursue innovative healthcare ventures, many medical schools lack formal programs to nurture entrepreneurial skills. To investigate student interest in entrepreneurshipand their experiences with medical innovation, the Biomedical Entrepreneurship Network at Rutgers Robert Wood Johnson Medical School engaged students nationally in a Healthcare Innovation Summit, featuring a keynote address, pitch competition, and interactive workshops with accomplished innovators. Methods A Rutgers electronic Institutional Review Board (eIRB)-approved survey was disseminated to student attendees at the summit, with questions categorized into four themes: interest/motivation, barriers to ideation and execution, support for innovation, and confidence in entrepreneurial pursuits. Responses were quantified using a Likert scale, and qualitative feedback was thematically analyzed. Results Among the 54 respondents, 100% exhibited a significant interest in healthcare entrepreneurship. Students cited the following barriers: inaccessible resources (44%), insufficient funding (51%), lack of mentorship (60%), and time limitations (82%). The quantitative thematic analyses demonstrated that students desired formal education on pursuing innovation and dedicated assistance to foster critical thinking. While students were confident in their ability to pursue entrepreneurship, they were not confident in the necessary details required for successful endeavors and avenues for mentorship. Conclusions Pursuing healthcare entrepreneurship presents numerous barriers for medical students. Integrating formal entrepreneurship education - emphasizing mentorship and connection between medical students and postgraduate trainees, funding, and critical innovative thinking - into medical curricula can empower students in the pursuit of innovation-based projects and positive change throughout their careers, enhancing access, equity, and quality of healthcare.

Spatio-temporal pattern and coordinated development of eco-compensation performance of 101 cities in the Yangtze River Economic Belt.

Eco-compensation is an important component of ecological civilization construction. Therefore, it is of great significance to elucidate the spatial and temporal pattern of eco-compensation performance and its internal coupling and coordinated features to promote ecological civilization construction. We proposed that eco-compensation performance consists of benefit and efficiency, and used the projection pursuit and super-efficiency SBM-DEA models to measure the eco-compensation benefit and efficiency of 101 cities in the Yangtze River Economic Belt from 2010 to 2021 and to analyze their spatial and temporal patterns. Finally, we used the coupling coordination degree model to reveal the coupling and coordinated features of eco-compensation performance. The results showed that the temporal trends of eco-compensation benefit and efficiency were "W" and "U" shaped. The eco-compensation benefit in eastern or mega-cities was the highest, whereas the eco-compensation efficiency in western or small/medium-sized cities was the highest. Coupling coordination degree of eco-compensation performance was in the coordinated development stage from 2010 to 2012, with a concentration of agglomeration effects in the central region. It was in the transition/adjustment stage from 2013 to 2020, with low-value areas concentrated and scattered high-value areas, and smaller regional differences. It was in the coordinated development stage in 2021, with a clear agglomeration effect in the eastern region. Cities in the Yangtze River Economic Belt should incorporate the eco-compensation performance coupling coordination mechanism into their optimized eco-compensation policy plans based on the stage of coordinated development, to achieve their environmental improvement goals.

A Comprehensive Evaluation of Water Resource Carrying Capacity Based on the Optimized Projection Pursuit Regression Model: A Case Study from China

The Han River Ecological Economic Belt (HREEB) has a substantial amount of water resources; however, its distribution is uneven, and issues such as seasonal and engineering water shortages are prevalent. This necessitates a thorough assessment of the current water resource situation and trends in water resource carrying capacity (WRCC) to provide scientific support for the rational allocation of water resources. This study employed the RAGA-PP model to establish a WRCC evaluation index system composed of four subsystems: water resources, economy, society, and the ecological environment. The WRCC of the 17 major cities in the HREEB was evaluated from 2008 to 2022. The differentiation method was introduced to compare the reliability of the RAGA-PP model with three evaluation methods: the entropy weight TOPSIS method, the rank sum ratio method, and the principal component analysis method. In addition, an obstacle degree model was introduced to analyze the factors influencing WRCC enhancement. The results indicated the following. (1) In the differentiation test of the four models, the RAGA-PP model was found to have the highest differentiation value, and the results showed that it was more reliable in the WRCC evaluation of HREEB. (2) WRCC in the HREEB underwent significant changes between 2008 and 2022. (3) The WRCC in Shiyan and Wuhan, which are located in the eastern part of the HREEB, were high in Hubei, low in four cities in Henan, and satisfactory in three cities in Shaanxi. (4) The carrying capacity of the subsystems of the cities in the HREEB exhibited fluctuating changes with obvious internal variations. (5) The problems in the WRCC guideline layer were consistent across all cities in the HREEB, with limited per capita water resources being the primary issue in the indicator layer. Assessing WRCC is essential for achieving sustainable water resource use and high-quality regional development.

Promotion or inhibition? Exploring the influence of the digital economy on urban-rural integration: A case study of yellow River basin

The digital economy actively disrupts the "urban depression effect" and the "wealth gap" between urban and rural areas, playing a crucial role in advancing urban-rural integration. Based on this, a scientifically constructed performance evaluation indicator system for the digital economy and urban-rural integration was developed. Using the Yellow River Basin as an empirical case study area, the projection pursuit model, simulated annealing algorithm and spatial Durbin model were employed to explore the impact of the digital economy on urban-rural integration in the Yellow River Basin from 2011 to 2021. The findings reveal the following: 1) The degree of digital economy and urban-rural integration display a characteristic pattern resembling that of a downstream > midstream > upstream watershed, showcasing discernible spatial correlation features between them. 2) The digital economy in the Yellow River Basin directly fosters urban-rural integration development. Government behavior stand out as the most influential factor in promoting urban-rural integration among the control variables. 3) The impact of the digital economy on urban-rural integration in the Yellow River Basin displays regional heterogeneity, with the most pronounced effects observed in downstream areas. Moreover, the spatial spillover effect of the digital economy exhibits a distinct "good-neighborliness" characteristic. 4) The digital economy in the Yellow River Basin substantially advances urban-rural integration development through the adjustment effect of industrial structure rationalization and the mediating effect of entrepreneurial activity. These research findings shed light on the impact and spatial spillover pathways of the digital economy on urban-rural integration, aligning with the national strategy of ecological protection and high-quality development in the Yellow River Basin.

Risk evaluation, spatiotemporal evolution, and driving factors of provincial food safety in China

The cross-regional transfer of food safety risks has become more prominent, bringing new challenges to the food ecosystem and food safety regulation. This study develops an evaluation index system of food safety risks based on the pressure-state-response (PSR) framework. The food safety risk indices of 30 provinces in China from 2011 to 2020 are calculated by determining the index weights using the real-coded accelerated genetic algorithm–projection pursuit model (RAGA-PP). Furthermore, this study elaborates the spatiotemporal differences and correlations of provincial food safety risks, characterizes the spatial aggregation and spatiotemporal changes of risks, and investigates driving factors affecting the spatiotemporal evolution of risks. The following findings are established. First, the overall risk value of food safety in China in 2020 decreased by approximately 5% compared with year 2010. In 2020, the national food safety environment was relatively favorable and tended toward stability. The overall trend of food safety risks in China is decreasing, although socioeconomic development has increased the risks, and the corresponding social management measures have also reduced the risks. Second, food safety risks were unevenly distributed among provinces, showing significant regional differences. Specifically, generally higher risks were observed in eastern provinces versus other regions and in coastal provinces versus inland provinces. Concentrated and superimposed risks were observed in the Yangtze River Delta, a large urban agglomeration centered on Shanghai. Lastly, population density and urbanization level were the main drivers of the evolution of regional food safety risks; whereas policy instruments used by the government to manage risks played a limited role. The results show that establishing a cross-regional collaborative governance mechanism to manage food safety risks should constitute an important component of the regional integration strategy of China.

Multi objective optimization and evaluation approach of prefabricated component combination solutions using NSGA-II and simulated annealing optimized projection pursuit method

As a main carrier mode for the sustainable development of the construction industry in China, prefabricated building may lead to problems such as cost overruns, project delays, and waste of resources due to unreasonable selection of prefabricated components. Therefore, we quantitatively analyze the contribution rate of quality optimization of prefabricated components using QFD-SEM. Under the constraints of prefabrication rate, quality optimization contribution rate, and expected values of various sub-goals, we propose a multi-objective optimization method for prefabricated component combinations based on cost, duration, and carbon emissions. By using NSGA-II to solve the model, we can obtain a set of optimal Pareto solutions for prefabricated component combinations. Based on the optimal Pareto solution set, we establish a multi-objective evaluation model using simulated annealing optimization projection tracing method, and select the optimal prefabricated component combination solution according to the projected eigenvalues of the solutions. An empirical study is conducted using an eleven-story framed building in Shenzhen, Guangdong Province, China as a case study. The results show that: (1) Using this method, optimal solutions can be obtained in an unbounded solution space, with the optimal solution having advantages over both fully cast-in-place and fully prefabricated solutions. Compared to the fully cast-in-place solution, the duration and carbon emissions are reduced by 36.62% and 12.74% respectively, while compared to the fully prefabricated solution, costs are reduced by 4.15%. (2) There is a certain negative correlation between the cost of prefabricated component combinations and duration, carbon emissions, and quality optimization, while there is a certain positive correlation with the prefabrication rate. (3) The size of the optimal projection direction vector based on the optimization objectives indicates that carbon emissions have the greatest impact on the evaluation results of the solutions.

Infill Well Location Optimization Method Based on Recoverable Potential Evaluation of Remaining Oil

Infill well location optimization poses significant challenges due to its complexity and time-consuming nature. Currently, determining the scope of infill wells relies heavily on field engineers’ experience, often using single indices such as the remaining oil saturation or abundance of remaining oil reserves to evaluate the potential of remaining oil. However, this approach lacks effectiveness in guiding the precise tapping of remaining oil in ultra-high water cut reservoirs. To address this, our study comprehensively considers the factors influencing the recoverable potential of remaining oil in such reservoirs. We characterize the differences in reservoir heterogeneity, scale of recoverable remaining oil reserves, water flooding conditions, and oil–water flow capacity to construct a quantitative evaluation index system for the recoverable potential of remaining oil. Recognizing the varying degrees of influence of different indices on the recoverable potential of remaining oil, we determine the objective weight of each evaluation index by combining an accelerated genetic algorithm with the projection pursuit model. This approach enables the construction of a recoverable potential index for remaining oil and forms a quantitative evaluation method for the recoverable potential of remaining oil in ultra-high water cut reservoirs. Subsequently, we establish a mathematical model for infill well location optimization, integrating and optimizing the infill well location coordinates, well length, well inclination angle, and azimuth angle. Using the main layer sand body of an oilfield in Bohai as a case study, we conducted evaluations of the remaining oil potential and infill well location optimization. Our results demonstrate that the assessment of the remaining oil potential comprehensively characterizes the influence of the reservoir’s physical properties and oil–water diversion capacity on the remaining oil potential across different regional positions. This evaluation can effectively guide the determination of infill well location ranges based on the evaluation results. Furthermore, infill well location optimization can effectively enhance reservoir development outcomes.

Strategic analysis of intelligent connected vehicle industry competitiveness: a comprehensive evaluation system integrating rough set theory and projection pursuit

As a carrier of multi-industrial technology integration and the key to industrial competition, the intelligent connected vehicle (ICV) has been taken seriously around the world. However, as a fast-growing emerging industry, its development process varies greatly from place to place. Hence, the merits and demerits are analyzed for the development of the ICV industry in different cities scientifically and to clarify the development of different links in each city, this paper suggests an extensive assessment framework integrating rough set theory and projection pursuit-based computation to systematically assess and thoroughly evaluate the level of competitiveness of the ICV industry. First, through big data text analysis technology, we constructed a "5 + 24" two-tier evaluation index system composed of 24 level-II evaluation indexes as well as five level-I evaluation indexes and selected 19 typical cities as input data for the comprehensive evaluation system. Further, the Adaptive Random Forest based Crossover Tactical Unit (ARF-CTU) algorithm is proposed for evaluating the performance of the industrial vehicle industry. However, the ARF algorithm is employed to estimate the lowering of overfitting issues and handling of high dimensional data. Moreover, the continuously varying conditions are analyzed by CTU. Then, we constructed a comprehensive evaluation system in the rough set theory and projection pursuit: (I) Quoting the rough set non-decision-making algorithm for attribute reduction, that is, under the premise of unchanged classification ability, derive a new evaluation system, and calculate the index weight and score based on the new system. (II) Based on the projection pursuit technology, the index score is mapped by a genetic algorithm to a linear structure, and a one-dimensional projection vector is an output.

Site Suitability Evaluation of a Large Commercial Complex Using an Improved Projection Pursuit Model

In developing countries, especially China, large-scale commercial complexes are the current trend in commercial real estate. Compared with other similar buildings, scientific site selection is very important for the smooth construction and efficient operation of these complexes. However, there is still a lack of a targeted evaluation index system and quantitative evaluation methods. Therefore, this paper put forward the evaluation index system and method of large-scale commercial-complex location based on a projection pursuit model. First, this paper comprehensively considered the environmental, social, and economic factors, and used secondary and tertiary indicators to systematically establish an evaluation index system. This index system effectively dealt with the complex problem of its site selection. Compared with the traditional multi-attribute evaluation method based on expert advice, the evaluation method of the improved projection pursuit model based on a sparrow search algorithm constructed in this paper was to mine key information from the evaluation data, which could evaluate the site suitability of large commercial complexes more scientifically and objectively. In addition, this paper made a detailed empirical study of the Joy City project in Nanchang, China. The research results found the key factors affecting the site selection of the project and determined that the site-selection evaluation result of the project was medium. The research results of this paper provide the scientific and objective decision-making basis for the development enterprises of large commercial complexes to reduce site-selection risk and improve investment efficiency.

Heavy Metal Concentration Estimation for Different Farmland Soils Based on Projection Pursuit and LightGBM with Hyperspectral Images.

Heavy metal pollution in farmland soil threatens soil environmental quality. It is an important task to quickly grasp the status of heavy metal pollution in farmland soil in a region. Hyperspectral remote sensing technology has been widely used in soil heavy metal concentration monitoring. How to improve the accuracy and reliability of its estimation model is a hot topic. This study analyzed 440 soil samples from Sihe Town and the surrounding agricultural areas in Yushu City, Jilin Province. Considering the differences between different types of soils, a local regression model of heavy metal concentrations (As and Cu) was established based on projection pursuit (PP) and light gradient boosting machine (LightGBM) algorithms. Based on the estimations, a spatial distribution map of soil heavy metals in the region was drawn. The findings of this study showed that considering the differences between different soils to construct a local regression estimation model of soil heavy metal concentration improved the estimation accuracy. Specifically, the relative percent difference (RPD) of As and Cu element estimations in black soil increased the most, by 0.30 and 0.26, respectively. The regional spatial distribution map of heavy metal concentration derived from local regression showed high spatial variability. The number of characteristic bands screened by the PP method accounted for 10-13% of the total spectral bands, effectively reducing the model complexity. Compared with the traditional machine model, the LightGBM model showed better estimation ability, and the highest determination coefficients (R2) of different soil validation sets reached 0.73 (As) and 0.75 (Cu), respectively. In this study, the constructed PP-LightGBM estimation model takes into account the differences in soil types, which effectively improves the accuracy and reliability of hyperspectral image estimation of soil heavy metal concentration and provides a reference for drawing large-scale spatial distributions of heavy metals from hyperspectral images and mastering soil environmental quality.

A novel framework for urban flood resilience assessment at the urban agglomeration scale

With global climate change and continuous urbanization exacerbating floods, urban flood resilience (UFR) has become a key to cope with floods. However, few studies target frameworks of UFR assessment at the urban agglomeration scale over a longer time span. This study, taking the Yangtze River Delta urban agglomeration as a case study, developed an evaluation framework to detail the building of a final evaluation index system of UFR, to analyze UFR's driving factors and spatiotemporal features based on the SSA-PP-KL-TOPSIS (projection pursuit based on sparrow search algorithm-Kullback-Leibler-technique for order of preference by similarity to ideal solution) model. From the perspectives of comparing numerical values and spatial distribution results, the evaluation indicators and method proposed in this article perform better. The case results showed that UFR displayed an overall growth trend and significant spatial heterogeneities. The economic, social, and infrastructure resilience showed a similar growth trend, while the environmental resilience demonstrated a decreasing trend. Environmental resilience has become a weak link in improving resilience. Higher resilience levels were concentrated in the central metropolis, provincial capitals, and industrial cities. The findings could be of use to researchers and practitioners, and the framework presented would be of reference to other flood-stricken areas.

Study on agricultural drought disaster risk assessment in Heilongjiang reclamation area based on SSAPSO optimization projection pursuit model.

Heilongjiang reclamation area serves as a crucial hub for commodity grain production and strategic reserves in China, playing a vital role in maintaining national food security. Investigating the assessment of agricultural drought risk in this region can yield valuable insights into spatial and temporal variations in drought risk. Such insights can aid in formulating effective strategies for disaster prevention and mitigation, thereby minimizing food losses caused by drought disasters. This study employs a comprehensive indicator system comprising 17 indicators categorized into hazard, exposure, vulnerability, and resistance capacity. The projection pursuit model is applied to evaluate regional drought risk, while the PSO algorithm, optimized by the SSA algorithm, addresses the limitations of low local search ability and search accuracy during the large-scale search process of the PSO optimization algorithm. This study examines and compares the optimization and convergence capabilities of three algorithms: real number encoding-based genetic algorithm (RAGA), particle swarm optimization algorithm (PSO), and sparrow algorithm-based improved particle swarm optimization algorithm (SSAPSO). The analysis demonstrates that SSAPSO exhibits superior optimization performance and convergence properties, establishing it as a highly effective algorithm for optimization tasks. The findings reveal the following trends: over time, agricultural drought risk in Heilongjiang reclamation area has generally declined, with fluctuations observed in hazard and vulnerability, an increase in exposure, and a continuous enhancement of resistance capacity. Spatially, the western region exhibits significantly higher agricultural drought risk compared to the eastern region, primarily due to elevated hazard and vulnerability, coupled with lower resistance capacity. As the agricultural economy grows and agricultural expertise accumulates, the risk of agricultural drought decreases. However, variations in economic growth among different regions lead to diverse spatial distributions of risk.

Probabilistic assessment of scalar transport under hydrodynamically unstable flows in heterogeneous porous media

Quantitative predictions of scalar transport in natural porous media is a nontrivial task given the presence of multi-scale spatial heterogeneity in the permeability field. Due to data scarcity, the structural map of the permeability field is subject to uncertainty and therefore, model predictions are uncertain. For such reasons, probabilistic models of flow and transport in natural porous media are required in risk assessment and to provide reliable decision making under uncertainty. Further complexities arise when the viscosity of the injected solute differs from that of the ambient fluid. Under the presence of viscosity contrast, hydrodynamic instabilities give rise to viscous fingering, which induces additional disorder in both velocity and solute concentration fields. This work examines the combined role of viscous fingering and permeability heterogeneity in the probabilistic description of transport predictions. In particular, we focus on metrics that are important for risk analysis, such as the solute plume’s early arrival times and the maximum concentration observed at a given location. We propose to use the Projection Pursuit Adaptation (PPA) method in the Polynomial Chaos Expansion (PCE) framework to quantify uncertainty in transport model predictions. The PPA method is a data-driven approach that optimally represents a given quantity of interest in a low-dimensional manifold. Unlike other dimension reduction techniques in uncertainty quantification, the PPA method utilizes non-linear information of the quantity of interest to identify the low-dimensional manifold, thereby increasing the likelihood of finding a more accurate lower-dimensional space. Moreover, the PPA model converges to the physical solution in a mean squared sense with respect to the polynomial order, enabling the construction of a converged model even with limited available data. Then, the PPA results are compared to Monte Carlo simulations using the same amount of data. This comparison illustrates that while Monte Carlo simulations are able to capture low-order statistics, they struggle to represent more detailed probability density functions. Our results show how the combined effect of permeability heterogeneity and viscosity contrast can enhance the mobility of the solute plume.

Research on the coordinated development and convergence characteristics of China’s urban competitiveness and green total factor productivity

The coordinated development of urban competitiveness (UC) and green total factor productivity (GTFP) is paramount for achieving global sustainable development objectives, especially for regional sustainability in China. This study utilizes panel data from 2011 to 2019 encompassing 273 Chinese cities to evaluate the urban competitiveness index employing the projection pursuit method. The research categorizes Chinese cities into four regions—East, Central, West, and Northeast—for comparative analysis purposes. The findings unveil: (1) a discernible rise in both overall and regional coordination between urban competitiveness and green total factor productivity in China; (2) throughout the study period, except for fluctuations observed in Northeastern China, coordination in other regions sustained relative stability, manifesting a trend of divergence-convergence; (3) the coordination between urban competitiveness and green total factor productivity across all regions demonstrated β-convergence, with Central China exhibiting the swiftest convergence and Northeastern China the slowest; (4) taking into account factors such as government intervention, industrial structure, and human capital, there is a likelihood that the growth rate of coordination between urban competitiveness and green total factor productivity in diverse regions will converge towards a synergistic trend. Therefore, as Chinese cities strive to enhance competitiveness and green total factor productivity, governmental attention should be directed towards discerning the developmental trends and influencing factors affecting their coordination. Such an approach will facilitate the realization of regional sustainable development objectives while propelling the synchronized advancement of urban competitiveness and green total factor productivity.

Clean and accurate soil quality monitoring in mining areas under environmental rehabilitation in the Eastern Brazilian Amazon.

Soil quality monitoring in mining rehabilitation areas is a crucial step to validate the effectiveness of the adopted recovery strategy, especially in critical areas for environmental conservation, such as the Brazilian Amazon. The use of portable X-ray fluorescence (pXRF) spectrometry allows a rapid quantification of several soil chemical elements, with low cost and without residue generation, being an alternative for clean and accurate environmental monitoring. Thus, this work aimed to assess soil quality in mining areas with different stages of environmental rehabilitation based on predictions of soil fertility properties through pXRF along with four machine learning algorithms (projection pursuit regression, PPR; support vector machine, SVM; cubist regression, CR; and random forest, RF) in the Eastern Brazilian Amazon. Sandstone and iron mines in different chronological stages of rehabilitation (initial, intermediate, and advanced) were evaluated, in addition to non-rehabilitated and native forest areas. A total of 81 soil samples (26 from sandstone mine and 55 from iron mine) were analyzed by both traditional wet-chemistry methods and pXRF. The available/exchangeable contents of K, Ca, B, Fe, and Al, in addition to H+Al, cation exchange capacity at pH = 7, Al saturation, soil organic matter, pH, sum of bases, base saturation, clay, and sand were accurately predicted (R2 > 0.70) using pXRF data, with emphasis on the prediction of Fe (R2 = 0.93), clay content (R2 = 0.81), H+Al (R2 = 0.81), and K+ (R2 = 0.85). The best predictive models were developed by RF and CR (86%) and when considering pXRF data + mining area + stage of rehabilitation (73%). The results highlight the potential of pXRF to accurately assess soil properties in environmental rehabilitation areas in the Amazon region (yet scarcely evaluated under this approach), promoting a more agile and cheaper preliminary diagnosis compared to traditional methods.

Can smart energy alleviate energy poverty in China? –Empirical evidence using synthetic control methods

Smart energy plays an important role in alleviating energy poverty in China in the context of the new technological revolution and industrial change. This paper uses China's smart pilot policy as a quasi-natural experiment, employing China's provincial panel data from 2011 to 2022, measuring energy poverty indices based on a projection pursuit evaluation model, and conducting a quasi-natural experiment using a synthetic control method to assess the effect of smart energy on energy poverty and specific mechanisms of action. The study found that smart energy has a specific and significant impact on energy poverty, but the effect differs in different regions depending on the construction cycle and energy endowment. In the mechanism test, smart energy significantly alleviates energy poverty through the mechanisms of improving energy supply capacity, improving energy payment capacity, and improving energy cleanliness. The results of the study provide empirical references for regional solutions to energy poverty and the planning of smart energy construction.

Study on the coordinated development of urban competitiveness and energy-carbon emission reduction in China

The urban competitiveness (UC) evaluation system is multidimensional and complex. This paper takes the simulated annealing (SA) model as the projection pursuit (PP) optimization to achieve a comprehensive assessment of competitiveness of 277 Chinese cities from 2011 to 2019, accompanied by energy saving and carbon-emission reduction (ESCER) as environmental measurements, to explore whether the two can meet the Porter hypothesis through coupling coordination degree (CCD). Further using spatiotemporal autocorrelation and obstacle degree model to uncover spatiotemporal features and interfering factors of coordinated development. Key findings include: (1) UC and ESCER show a slightly fluctuating upward trend during the research period, with apparent spatial variations. The eastern coastal region has a robust UC, while the less competitive central and western regions benefit from natural conditions, excelling in ESCER. (2) 87% of cities have achieved coordinated development between competitiveness and ESCER. Some coastal areas, often with a high CCD, are improving resource use efficiency and environmental benefits through economic agglomeration. From the perspective of the CCD collaboration network, the positive correlation accounts for about 85%, which reveals that most adjacent regions can cooperate on the road of coordinated development. (3) While differences exist in the coordinated development of UC-ESCER across various regions, social factors predominantly influence the obstacles affecting coordinated development. Specifically, a substantial barrier to the concordant progression of most cities is the number of patent applications, underscoring the pivotal role of innovation in aligning UC with ESCER.