Search Results (142)

Achieving a win-win situation for both economy and ecology is crucial for promoting sustainable social development and shaping new advantages in high-quality developments. This article constructs an ecological economic resilience (EER) analysis framework by integrating both ecological and economic dimensions from a resilience perspective. Based on panel data from 290 cities in China, it explores the dynamic evolution characteristics, regional differences, and convergence trends of EER. The findings indicate that the EER has weakened nationwide and in the four major economic regions, overall tending towards stability. Significant disparities exist in EER, particularly pronounced in the northeast. There is $\sigma$ convergence in the nation as well as in the northeast and east regions. Additionally, both absolute and conditional $\beta$ convergence is evident nationwide and in all regions, with conditional convergence occurring at a faster pace. The research findings in this paper provide solid theoretical support for promoting regional coordinated development and constructing a new development paradigm. Full article

Suppose X and Y are Banach spaces, K is a compact Hausdorff space, and $C(K, X)$ is the Banach space of all continuous X-valued functions (with the supremum norm). We will study some strongly bounded operators $T:C(K, X)\to Y$ with representing measures $m:\Sigma \to L(X,Y)$, where $L(X,Y)$ is the Banach space of all operators $T:X\to Y$ and $\Sigma$ is the $\sigma$-algebra of Borel subsets of K. The classes of operators that we will discuss are the Grothendieck, p-limited, p-compact, limited, operators with completely continuous, unconditionally converging, and p-converging adjoints, compact, and absolutely summing. We give a characterization of the limited operators (resp. operators with completely continuous, unconditionally converging, p-convergent adjoints) in terms of their representing measures. Full article

Addressing the stability control challenges of roadways with composite roofs in the No. 34 coal seam of Donghai Mine under high-strength mining conditions, this study employed integrated methodologies including laboratory experiments, numerical modeling, and field trials. It investigated the mechanical response characteristics of the composite roof and developed a synergistic control system, validated through industrial application. Key findings indicate significant differences in mechanical behavior and failure mechanisms between individual rock specimens and composite rock masses. A theoretical “elastic-plastic-fractured” zoning model for the composite roof was established based on the theory of surrounding rock deterioration, elucidating the mechanical mechanism where the cohesive strength of hard rock governs the load-bearing capacity of the outer shell, while the cohesive strength of soft rock controls plastic flow. The influence of in situ stress and support resistance on the evolution of the surrounding rock zone radii was quantitatively determined. The FLAC^3D strain-softening model accurately simulated the post-peak behavior of the surrounding rock. Analysis demonstrated specific inherent patterns in the magnitude, ratio, and orientation of principal stresses within the composite roof under mining influence. A high differential stress zone (σ₁/σ₃ = 6–7) formed within 20 m of the working face, accompanied by a deflection of the maximum principal stress direction by 53, triggering the expansion of a butterfly-shaped plastic zone. Based on these insights, we proposed and implemented a synergistic control system integrating high-pressure grouting, pre-stressed cables, and energy-absorbing bolts. Field tests demonstrated significant improvements: roof-to-floor convergence reduced by 48.4%, rib-to-rib convergence decreased by 39.3%, microseismic events declined by 61%, and the self-stabilization period of the surrounding rock shortened by 11%. Consequently, this research establishes a holistic “theoretical modeling-evolution diagnosis-synergistic control” solution chain, providing a validated theoretical foundation and engineering paradigm for composite roof support design. Full article

Conventional integer-order models fail to adequately capture non-local memory effects and constrained nonlinear interactions in emotional dynamics. To address these limitations, we propose a coupled framework that integrates Caputo fractional derivatives with hyperbolic tangent–based interaction functions. The fractional-order term quantifies power-law memory decay in affective states, while the nonlinear component regulates connection strength through emotional difference thresholds. Mathematical analysis establishes the existence and uniqueness of solutions with continuous dependence on initial conditions and proves the local asymptotic stability of network equilibria ($W_{ij}^{*}={\displaystyle \frac{1}{\delta }}{\sec \mathrm{h}}^2(\parallel {\mathrm{E}}_i-{\mathrm{E}}_j\parallel )$, e.g., $W^{*}\approx 1.40$ under typical parameters $\eta =0.5$, $\delta =0.3$). We further derive closed-form expressions for the steady-state variance under stochastic perturbations ($\mathrm{Var}\left(W_{ij}\right)={\displaystyle \frac{{\sigma }_{\zeta }^2}{2\eta \delta }}$) and demonstrate a less than 6% deviation between simulated and theoretical values when ${\sigma }_{\zeta }=0.1$. Numerical experiments using the Euler–Maruyama method validate the convergence of connection weights toward the predicted equilibrium, reveal Gaussian features in the stationary distributions, and confirm power-law scaling between noise intensity and variance. The numerical accuracy of the fractional system is further verified through L1 discretization, with observed error convergence consistent with theoretical expectations for $\mu =0.5$. This framework advances the mechanistic understanding of co-evolutionary dynamics in emotion-modulated social networks, supporting applications in clinical intervention design, collective sentiment modeling, and psychophysiological coupling research. Full article

Optimizing vertical-axis hydrokinetic turbines is essential to enhance their energy conversion efficiency and structural reliability, particularly for decentralized renewable energy applications. This study focuses on identifying the most effective turbine design by evaluating the influence of three key parameters: aspect ratio ($AR$), solidity ($\sigma$), and the index of revolution (I). Specifically, the study considers Gorlov-type vertical-axis turbines, known for their helical design and favorable hydrodynamic characteristics. To achieve this, fifteen turbine configurations were analyzed using a combination of two methods: response surface methodology (RSM) and multi-criteria decision matrices. Both methods converged on the same optimal turbine model, characterized by an I of 0.1, a $\sigma$ of 0.40, and an $AR$ of 1.0, demonstrating superior energy efficiency and structural robustness, as the design achieved a power coefficient ($C_p$) of 40.8% at a tip speed ratio ($TSR$) of 1.01. The integration of numerical simulations and experimental validation provides comprehensive insights into turbine behavior, ensuring reliability in practical applications. These findings advance hydrokinetic energy technologies by identifying configurations that optimize both performance and manufacturability. Full article

The convergence rate of the augmented Lagrangian method (ALM) for solving the nonlinear semidefinite optimization problem is studied. Under the Jacobian uniqueness conditions, when a multiplier vector $(\pi ,Y)$ and the penalty parameter $\sigma$ are chosen such that $\sigma$ is larger than a threshold ${\sigma }^{*}>0$ and the ratio $\parallel (\pi ,Y)-({\pi }^{*},Y^{*})\parallel /\sigma$ is small enough, it is demonstrated that the convergence rate of the augmented Lagrange method is linear with respect to $\parallel (\pi ,Y)-({\pi }^{*},Y^{*})\parallel$ and the ratio constant is proportional to $1/\sigma$, where $({\pi }^{*},Y^{*})$ is the multiplier corresponding to a local minimizer. Furthermore, by analyzing the second-order derivative of the perturbation function of the nonlinear semidefinite optimization problem, we characterize the rate constant of local linear convergence of the sequence of Lagrange multiplier vectors produced by the augmented Lagrange method. This characterization shows that the sequence of Lagrange multiplier vectors has a Q-linear convergence rate when the sequence of penalty parameters $\left\{{\sigma }_k\right\}$ has an upper bound and the convergence rate is superlinear when $\left\{{\sigma }_k\right\}$ is increasing to infinity. Full article

This paper mainly investigates a class of third-order semilinear delay differential equations with a nonhomogeneous term ${\left({\left[x^{″}\left(t\right)\right]}^{\alpha }\right)}^{\prime }+q\left(t\right)x^{\alpha }\left(\sigma \left(t\right)\right)+f\left(t\right)=0,t\ge t_0.$ Under the oscillation criteria, we propose a sufficient condition to ensure that all solutions for the equation exhibit oscillatory behavior when $\alpha$ is the quotient of two positive odd integers, supported by concrete examples to verify the accuracy of these conditions. Furthermore, for the case $\alpha =1,$ a sufficient condition is established to guarantee that the solutions either oscillate or asymptotically converge to zero. Moreover, under these criteria, we demonstrate that the global oscillatory behavior of solutions remains unaffected by time-delay functions, nonhomogeneous terms, or nonlinear perturbations when $\alpha =1.$ Finally, numerical simulations are provided to validate the effectiveness of the derived conclusions. Full article

The scientific evaluation of ecological total factor productivity of cultivated land use (ETFPCLU) is fundamental for advancing sustainable utilization of cultivated land resources and safeguarding national food security and ecological stability. Using the epsilon-based measure and the global Malmquist–Luenberger (EBM–GML) index, this study quantifies and decomposes ETFPCLU across China. Spatial–temporal variations and convergence patterns are systematically investigated via an analytical toolkit comprising the spatial mismatch index, Dagum’s Gini coefficient decomposition, and convergence models. The results indicate that Chinese ETFPCLU increased by an average of 2.1% per year from 2001 to 2022, primarily attributed to technical change (TC), with limited contributions from efficiency change (EC). The spatial mismatch between ETFPCLU and TC, as well as EC, is predominantly characterized by low to medium mismatch types, exhibiting a high degree of spatial distribution similarity; inter-regional differences are the main contributors to regional disparities. Furthermore, except for the central region, significant σ-convergence exists in ETFPCLU across the country and in other regions, alongside absolute β-convergence and conditional β-convergence in the four major regions. The analysis concludes that to enhance ETFPCLU, it is essential to strengthen technological innovation, synergistically improve technological efficiency, formulate ecological protection policies tailored to local conditions, and foster collaboration among regions for cultivated land protection. Full article

It is important to study the difference, distribution dynamics and convergence of China’s renewable energy development level to stimulate its potential. Based on China’s provincial panel data from 2006 to 2021, this paper analyzes the regional characteristics of China’s renewable energy development using the Dagum Gini coefficient, kernel density estimation, σ convergence and spatial β convergence, and draws the following conclusions: Firstly, renewable energy in the country and the four major regions have achieved stable growth. Secondly, the intra-group differences in China and the four major regions are gradually decreasing, and the contribution rate of inter-group differences to the overall differences is gradually increasing, which is the main source of the overall differences. Thirdly, the national renewable energy development has a positive spatial correlation. Fourthly, there are σ convergence and spatial β convergence in the whole country and the four major regions; the σ convergence coefficient gradually decreases, and the β convergence regression coefficient is significantly negative. Therefore, this paper proposes the following recommendations: formulate government policies according to local conditions, strengthen technical exchanges and cooperation among regions, and encourage investment in renewable energy development; thus, we can promote a more efficient realization of the “dual carbon” goal. Full article

Promoting the comprehensive green transformation (CGT) of China’s economy and society is vital for achieving high-quality economic growth and building a beautiful China. This study establishes a CGT evaluation index system across four dimensions: comprehensiveness, synergy, innovation, and security. Using the entropy weighting method, it evaluates the CGT development level across 30 Chinese provinces from 2011 to 2022. Subsequently, it examines regional differences and convergence features in CGT development through the application of the Theil index, kernel density estimation (replaced by KDE below), and convergence analysis methods. The findings indicate the following: Firstly, the CGT development level nationwide and within the four key regions has been on the rise annually; yet, regional variations persist. Secondly, both the overall disparities in CGT development across China’s economy and society and the discrepancies within the four key regions are diminishing. Furthermore, interregional variations are the main contributor to the overall disparities in CGT development. Thirdly, while the number of provinces achieving CGT development has gradually increased nationwide, their unevenness has also intensified. Fourthly, regarding convergence characteristics, σ-convergence, along with both absolute and conditional β-convergence are observed in all regions but the central; in the central region, absolute β-convergence is not statistically significant, but conditional β-convergence is. Conclusions from this study can offer theoretical insights for further elevating the CGT level of China’s economy and society and fostering coordinated regional development. Full article

The integration of the agricultural product market is of great significance to reducing price fluctuations and improving social welfare. In this study, we employ the relative price method to measure the integration of the agricultural product market in 31 Chinese provinces from 2003 to 2022. We use the Dagum–Gini coefficient and its decomposition and the σ convergence and β convergence models to analyze regional variations, time trends, and convergence. It is found that the degree of integration of the Chinese agricultural product market did not increase continuously but fluctuated with increasing intensity. The spatial differentiation degree of agricultural market integration fluctuated. The integration degree of the agricultural product market has σ convergence, absolute β convergence, and conditional β convergence. The marginal contribution of this study is the systematic analysis of the dynamic evolution and convergence of the integration of the Chinese agricultural product market. In order to improve the integration degree of the agricultural product market, in this paper, we put forward policy suggestions from three aspects: strengthening policy support, optimizing resource allocation, and building agricultural product market information centers. Full article

Based on the panel data of 30 provinces in China from 2013 to 2022, this paper constructs a measurement index system for the symbiotic level of digital innovation ecosystems from three dimensions: the symbiosis of digital innovation subjects, the digital innovation environment, and digital innovation interaction. This paper applies the entropy weight TOPSIS method, Dagum Gini coefficient decomposition, and spatial convergence analysis to empirically examine the symbiotic levels, regional disparities, and spatial convergence of China’s digital innovation ecosystem. The results are as follows: (i) At the national level, the symbiotic level of China’s digital innovation ecosystem has generally increased, creating a spatial distribution pattern that is “high in the east, flat in the middle, and low in the west”. (ii) From a regional perspective, the major disparities between regions are the primary factors contributing to the overall difference in the symbiotic level of China’s digital innovation ecosystem. (iii) From the perspective of σ convergence, regional disparities in the symbiotic level of the digital innovation ecosystem are constantly expanding, and uneven regional development is intensifying. (iv) From the perspective of absolute β convergence, regions with lower levels of symbiosis in the digital innovation ecosystem have a faster growth rate of symbiosis than regions with higher levels of symbiosis, and there is a certain spatial spillover effect. (v) From the perspective of conditional β convergence, economic structure and innovation application can accelerate the spatial convergence of China’s digital innovation ecosystem symbiosis to a certain extent. Full article

In this article, we examine a class of partially linear additive models (PLAM) defined via a measurable mapping $\mathsf{\Psi }:{\mathbb{R}}^q\to \mathbb{R}$. More precisely, we consider $\mathsf{\Psi }\left({\mathbf{Y}}_i\right):={\mathcal{Y}}_i={\mathbf{Z}}_i^{\top }\mathit{\beta }+{\sum }_{\mathcal{l}=1}^d{m}_{\mathcal{l}}\left(X_{\mathcal{l},i}\right)+{\epsilon }_i,i=1,\dots ,n,$ where ${\mathbf{Z}}_i={(Z_{i,1},\dots ,Z_{i,p})}^{\top }$ and ${\mathbf{X}}_i={(X_{1,i},\dots ,X_{d,i})}^{\top }$ denote vectors of explanatory variables. The unknown parameter vector is $\mathit{\beta }={({\beta }_1,\dots ,{\beta }_p)}^{\top }$, and $m_1,\dots ,m_d$ are real-valued functions of a single variable whose forms are not specified. The error terms ${\epsilon }_1,\dots ,{\epsilon }_n$ are identically distributed with mean zero and finite variance ${\sigma }_{\epsilon }$, and they fulfill the condition $\mathbb{E}(\epsilon \mid \mathbf{X},\mathbf{Z})=0$ almost surely. These models are broadly applicable in finance, biology, and engineering, where capturing intricate nonlinear effects is essential. We propose an estimation method that leverages marginal integration in conjunction with linear wavelet-based techniques to obtain estimators for the unknown components $m_1,\dots ,m_d$. Under suitable regularity conditions, we establish strong uniform convergence of these estimators, demonstrating that they achieve practically relevant convergence rates. Our theoretical results indicate that these estimators converge uniformly at rates that are favorable for practical applications, underscoring the adaptability and scope of this partially linear additive model. Full article

In the pursuit of sustainable urban development, construction land development (CLD) not only carries the important mission of promoting economic growth but also needs to actively respond to the environmental requirements of reducing carbon emissions. However, there is a tension and balance between these two objectives. This study explores the evolution characteristics and influencing mechanisms of the synergistic relationship between carbon emission efficiency and economic benefits of CLD based on the undesirable slacks-based measurement, coupling coordination degree (CCD) model, Tapio decoupling model, spatial convergence model, and interpretable machine learning techniques. The main conclusions are as follows: (1) The CCR between CEE and economic benefits of CLD in China shows the characteristic of “improvement-stability-local decline”, and it is higher in the eastern region than in the central and western regions. (2) The decoupling of carbon emission efficiency (CEE) and economic benefits of CLD between 2003 and 2023 shows diverse trends in different provinces and time scales in China. (3) China’s eastern region are consistent with σ-convergence and β-convergence, and the gap in the level of inter-regional coupling co-ordination has narrowed. On the contrary, the central and western regions do not pass the σ and β-convergence tests, and the regional equilibrium needs to be improved. (4) In descending order of influence on CCR, they are ownership structure, urban construction land per capita, energy consumption per unit of gross domestic product, energy structure, industrial structure, and foreign trade investment intensity. Full article

To achieve the green and efficient utilization of land in China’s three northeastern provinces and to harmonize the human–land relationship, this paper examines the spatiotemporal evolution and convergence of land green utilization efficiency (LGUE) in these provinces against the backdrop of population contraction. Utilizing data from 2000 to 2020, we employ the geometric mean method to characterize the features of population contraction and construct a global reference non-desired super-efficiency SBM-DEA model to measure LGUE. The dynamic evolution of LGUE is analyzed using kernel density estimation and spatial visualization techniques, and its convergence is tested through σ-convergence and absolute β-convergence methods. The results indicate that during the study period, the population in the three northeastern provinces has experienced overall contraction, predominantly characterized by a “growth-to-contraction” pattern, which is more pronounced in resource-based cities. Land green utilization efficiency exhibits a fluctuating upward trend, evolving spatially into a distribution pattern of “high in the middle and low on both sides along the northeast–southwest axis”. The degree of dispersion among cities also shows an upward fluctuation, with evidence of σ-convergence and absolute β-convergence. Regional balance has improved. This study concludes that there is significant potential for enhancing land green utilization efficiency in the three northeastern provinces. We recommend adopting the “smart contraction” model to promote coordinated development between population and land, capital and land, as well as ecology and land, thereby fostering sustainable development in these regions. Full article