Search Results (53)

Green inclusive growth is a crucial strategic choice for achieving high-quality development in China. This study constructs an indicator system encompassing economic, social, and ecological dimensions to quantitatively measure the level of green inclusive growth across 31 provinces (cities, autonomous regions) in China from 2001 to 2021. The regional disparities, spatiotemporal evolution trends, and convergence characteristics are analyzed using the Dagum Gini coefficient, kernel density function, and σ-convergence and conditional β-convergence. The findings indicate the following: (1) China’s green inclusive growth generally exhibits a “high in the east, low in the west” spatial distribution pattern, with western regions demonstrating a catching-up trend. (2) The regional disparities in China’s green inclusive growth levels are showing a trend of gradual narrowing, though imbalances within eastern and western regions remain relatively pronounced. (3) The kernel density curve of China’s green inclusive growth maintains a “unimodal” shape, with no significant polarization or multi-polar differentiation. (4) Both the national level and the four major regional clusters exhibit σ-convergence and conditional β-convergence in green inclusive growth, demonstrating the effectiveness of policies aimed at reducing regional disparities. (5) Social capital, human capital, technological innovation, material capital investment, foreign direct investment, urbanization level, and government fiscal expenditure all have a positive promoting effect on China’s green and inclusive growth. These results provide decision-making references for promoting coordinated regional development and guiding the inclusive and green transformation of China’s economic growth. Full article

With the increasing constraints of resource and environmental factors and the prominent issues of regional development imbalance, how to scientifically measure the level of agricultural sustainable development and reveal its spatial-temporal differentiation patterns has become a key scientific question that urgently needs to be addressed in optimizing land use layout and promoting rural revitalization. This study takes the human-land spatial systems coupling theory as the core framework and constructs an evaluation index system for agricultural sustainable development covering five dimensions: economy, society, resources, ecology, and technology. Based on provincial panel data in China from 2001 to 2024, the entropy method is employed to measure agricultural sustainable development, while Dagum’s Gini coefficient, kernel density estimation, and convergence models are applied to analyze its spatial–temporal evolution. Furthermore, the fuzzy-set qualitative comparative analysis (fsQCA) method is introduced to identify multi-factor configurational driving pathways. The results indicate that the overall level of agricultural sustainable development in China shows a steady upward trend, exhibiting a regional gradient pattern characterized by “central region leading, eastern region steadily advancing, and western region gradually catching up”. The overall disparity presents a weak convergence trend, with inter-regional differences as the primary source, although their contribution is gradually declining. The development structure has evolved from regional fragmentation to a more complex spatial interaction pattern. The overall distribution shifts rightward with evident stage-based differentiation, accompanied by significant positive spatial dependence, with “high–high” and “low–low” clustering coexisting over the long term. Convergence analysis shows that σ-convergence exists at the national level. After accounting for spatial effects, significant absolute β-convergence is observed in the eastern and western regions, while the central region does not exhibit significant convergence. Conditional β-convergence further confirms the existence of regional convergence trends, although the convergence speeds vary. The fsQCA results indicate that agricultural sustainable development is not driven by a single factor but by multiple configurational pathways formed through the interaction of various conditions. These findings provide empirical evidence for optimizing agricultural spatial layout, strengthening land factor support, and promoting regionally coordinated agricultural sustainable development. Full article

The development of effective antioxidants has evolved from descriptive analysis toward a precise, mechanism-driven discipline targeting the molecular “redox switch”. This review synthesizes the critical advances reported since 2021, focusing on how the interplay between polyphenolic architecture and electronic descriptors, such as bond dissociation enthalpy and ionization potential, governs radical scavenging through the HAT, SET, and SPLET pathways. We evaluate the dual influence of metal coordination, where interactions can either enhance antioxidant stability through σ bond polarization or trigger pro-oxidant transitions via ligand-to-metal charge transfer. Central to this progress is the integration of computational models (DFT, QSAR) with advanced synchrotron methodologies (XAS, STXM, SR-FTIR, and SAXS), which provide element-specific validation of antioxidant behavior and subcellular oxidative mapping within complex matrices. Furthermore, we highlight how these molecular insights inform formulation engineering, specifically the development of organic nanocarriers and hybrid delivery systems, such as metal–phenolic networks, that shield therapeutic cargo from degradation and govern release in challenging physiological environments. These fundamental studies provide an essential physicochemical basis for medicine by enabling a better understanding and the rational design of antioxidant drugs, dietary supplements, and antioxidant strategies. Full article

We introduce a geometric framework in which classical transforms are represented as coordinate charts on a symbolic manifold. The construction defines symbolic curvature (κ), strain (τ), compressibility (σ), and the ratio Γ = κ/τ, which together provide a diagnostic coordinate system for comparing representational stability across chart transitions. Within this setting, transforms such as Fourier, Laplace, wavelet, Jordan, and polynomial projection can be treated as charts connected by transition maps that preserve Γ on specified domains. We also introduce a symmetric positive-definite metric tensor $G_{ab}$ to quantify displacement in the invariant coordinates and to formalize minimal-effort paths (geodesics) under modeling assumptions stated in the text. The resulting framework provides a reproducible screening method for evaluating transform stability, diagnosing closure failure, and comparing transform behavior under a shared set of invariants. Full article

Metallic biomaterials play essential roles in modern medical devices, but their long-term performance depends critically on protein adsorption and subsequent cellular responses at material interfaces. This review examines the molecular mechanisms governing these interactions and discusses surface modification strategies for controlling biocompatibility. The physicochemical properties of oxide layers formed on metal surfaces—including Lewis acid-base chemistry, surface charge, surface free energy, and permittivity—collectively determine protein adsorption behavior. Titanium surfaces promote stable protein adsorption through strong coordination bonds with carboxylate groups, while stainless steel surfaces show complex formation with proteins that can lead to metal ion release. Surface modification strategies can be systematically categorized based on two key parameters: effective ligand density (σ_eff) and effective mechanical response (E_eff). Direct control approaches include protein immobilization, self-assembled monolayers, and ionic modifications. The most promising strategies involve coupled control of both parameters through hierarchical surface architectures and three-dimensional modifications. Despite advances in understanding molecular-level interactions, substantial challenges remain in bridging the gap between surface chemistry and tissue-level biological performance. Future developments must address three-dimensional interfacial interactions and develop systems-level approaches integrating multiple scales of biological organization to enable rational design of next-generation metallic biomaterials. Full article

Against the backdrop of China’s “carbon peaking” and “carbon neutrality” goals, as well as the advancement of new industrialization, the oil and gas industry is undergoing a critical transformation from resource-dependent growth toward innovation-driven, low-carbon, and high-quality development. The integrated advancement of high-end, intelligent, and green transformation—collectively referred to as the “Three Modernizations”—has become a vital pathway for promoting industrial upgrading and sustainable growth. Based on panel data from 30 Chinese provinces from 2009 to 2023, this study constructs a comprehensive evaluation index system covering 19 secondary indicators across three dimensions: high-end, intelligent, and green development. Using the entropy-weighted TOPSIS method, kernel density estimation, Dagum Gini coefficient decomposition, and σ–β convergence models, the study examines the spatiotemporal evolution, regional disparities, and convergence characteristics of HIG integration, and further explores its driving mechanisms through a two-way fixed effects model and mediation effect analysis. The results show that (1) the overall HIG integration index rose from 0.34 in 2009 to 0.46 in 2023, forming a spatial pattern of “high in the east, low in the west, stable in the center, and fluctuating in the northeast”; (2) regional disparities narrowed significantly, with the Gini coefficient declining from 0.093 to 0.058 and σ decreasing from 7.114 to 6.350; and (3) oil and gas resource endowment, policy support, technological innovation, and carbon emission constraints all positively promote integration, with regression coefficients of 0.152, 0.349, 0.263, and 0.118, respectively. Heterogeneity analysis reveals an increasing integration level from upstream to downstream, with eastern regions leading in innovation-driven development. Based on these findings, the study recommends strengthening policy and institutional support, accelerating technological innovation, improving intelligent infrastructure, deepening green and low-carbon transformation, promoting regional coordination, and establishing a long-term monitoring mechanism to advance the integrated high-quality development of China’s oil and gas industry. Overall, this study deepens the understanding of the internal logic and spatial dynamics of the “Three Modernizations” integration in China’s oil and gas industry, providing empirical evidence and policy insights for accelerating the construction of a low-carbon, secure, and efficient modern energy system. Full article

The study at the Sanctuary of Eukleia in Aigai (Vergina, Greece) evaluates the planimetric and vertical accuracy of Digital Surface Model (DSM) generated by a Hesai XT32M2X LiDAR system mounted on UAS WingtraOne GEN II. The paper begins by outlining the evolution of UAS-LiDAR, then describing the acquisition of RGB, multispectral (MS) images and LiDAR data. Twenty-two Check Points (CPs) were measured using an RTK-GNSS receiver, which also served to establish the PPK calibration base point. This is followed by processing the images to generate DSMs and orthophotomosaics, as well as processing the LiDAR point cloud to produce both DSM and DTM products. The DSMs and orthophotomosaics were evaluated by comparing field-measured CP coordinates with those extracted from the products, computing mean values and standard deviations. RGB images yielded DSMs and orthophotomosaics with planimetric accuracy of 1.4 cm (with a standard deviation σ = ±1 cm) in X, 0.9 cm (with σ = ±0.9 cm) in Y and a vertical accuracy of 2.4 cm (with σ = ±1.7 cm). The LiDAR-derived DSM achieved similar planimetric accuracy and an overall vertical accuracy of 7.5 cm (with σ = ±6 cm). LiDAR’s ability to penetrate vegetation enabled near-complete mapping of a densely vegetated streambank, highlighting its clear advantage over images. While high-precision RGB-PPK products can surpass LiDAR in vertical accuracy, UAS-LiDAR remains indispensable for under-canopy terrain mapping. Full article

The mechanically activated transition (MAT) from linear viscoelasticity to yielding is considered an essential part of the operational behavior of ductile materials. The MAT region is restricted by proportional limit at σ₀ and ε₀ and the yield point at σ_y and ε_y, or, in terms of this paper, $E_0={\sigma }_0/{\epsilon }_0$ and ε₀ and $E_y={\sigma }_y/{\epsilon }_y$ and ε_y, respectively. This stage precedes yielding and controls the parameters of the yield point. For bulk plastic (co)polymers and cellular polymeric foams, the quantitative correlations between $E_0$, ε₀, $E_y,$ and ε_y were determined. The ratios ${\displaystyle \raisebox{1ex}{$E_0$}\!\left/ \!\raisebox{-1ex}{$E_y$}\right.}=1.55\pm 0.15$ and ${\displaystyle \raisebox{1ex}{${\epsilon }_y$}\!\left/ \!\raisebox{-1ex}{${\epsilon }_0$}\right.}=2.1\pm 0.2$ were specified as yielding criteria. For all the samples studied, their mechanical response within the MAT region was unified in terms of master curve constructed via re-calculation of the experimental “stress–strain” diagrams in the reduced coordinates ${\displaystyle \frac{\mathit{lg} E-\mathit{lg} E_0}{\mathit{lg} E_0-\mathit{lg} E_y}}=f\left({\displaystyle \frac{\mathit{lg} \epsilon -\mathit{lg} {\epsilon }_0}{\mathit{lg} {\epsilon }_y-\mathit{lg} {\epsilon }_0}}\right),$ where $E=\sigma /\epsilon$ and ε are the current modulus and strain, respectively. To generalize these regularities found for bulk plastics and foams, our earlier experimental results concerning the rheology of soil-based pastes and data from the literature concerning the computer simulation of plastic deformation were invoked. Master curves for (1) dispersed pastes, (2) bulk plastics, (3) polymeric foams, and (4) various virtual models were shown to be in satisfactory coincidence. For the materials analyzed, this result was considered as the unification of their mechanical response within the MAT region. An algorithm for the express analysis of the mechanical response of plastic systems within the MAT region is proposed. The limitations and advances of the proposed methodological approach based on correlation studies followed by construction of master curves are outlined. Full article

Understanding the coupled and coordinated development of China’s urban and rural basic education systems is crucial for fostering their interaction and synergistic growth. Using China’s provincial panel data from 2011 to 2023, this study measures the coupled and coordinated development level of urban–rural basic education (CCD-URBE) via the entropy weight method, G1-method and coupling coordination degree model. On this basis, the Dagum Gini coefficient decomposition method, traditional and spatial Markov chain models, as well as convergence test models are employed for empirical research. The results show that: (1) During the study period, the CCD-URBE across the nation and the four major regions improves significantly. Both intra-regional and inter-regional disparities show a consistent downward trend. Inter-regional disparities are the main source of the overall disparities, and the contribution rate of transvariation density to the overall disparities exhibits the most significant increase. (2) The CCD-URBE demonstrates strong stability, as most regions tend to maintain their original CCD-URBE grades. Meanwhile, neighborhood grades moderate the local transition probability significantly. Neighborhoods with high CCD-URBE promote the upward improvement of the local CCD-URBE, while those with low CCD-URBE inhibit it. (3) The CCD-URBE across the nation and the four major regions shows obvious trends of σ-convergence, absolute β-convergence, and conditional β-convergence. The central region, which has lower CCD-URBE, exhibits higher convergence speed. Based on these findings, targeted policy implications are derived. Full article

Polymer-based hybrid composites have emerged as promising platforms for multifunctional energy applications, combining structural versatility with tunable dielectric behavior. In this study, synthesized [Fe(bpy)₃]SO₄; (tris(2,2′-bipyridine)iron(II) sulfate) coordination compound was incorporated into a green epoxy resin matrix to fabricate nanocomposites aimed at enhancing dielectric permittivity (ε′), piezoelectric coefficient (d₃₃, pC/N), energy-storage efficiency (n_rel, %), and mechanical strength (σ, MPa). The integration of the Fe(II) complex via Scanning Electron Microscopy (SEM) confirmed a homogeneous dispersion within the matrix. Broadband Dielectric Spectroscopy (BDS) revealed the presence of three relaxation processes in the spectra of the tested systems, demonstrating enhanced dielectric permittivity with increasing Fe(II) content. Under progressively shorter relaxation times (τ, s), key processes such as interfacial polarization, the polymer matrix’s transition from a glassy to a rubbery state, and the dynamic reorganization of polar side groups along the polymer backbone are activated. The ability to store and retrieve electric energy was confirmed by varying filler content under direct current (dc) conditions. The nanocomposite with 10 phr (mass parts/100 mass parts of resin) filler achieved a piezoelectric coefficient of d₃₃ = 5.1 pC/N, an energy-storage efficiency of n_rel = 44%, and a tensile strength of σ = 55.5 MPa, all of which surpass values reported for conventional epoxy-based composites. These results confirm the ability of the system to store and retrieve electric energy under direct current (dc) fields, while maintaining mechanical robustness and thermal stability due to synergistic interactions between the epoxy matrix and the Fe(II) complex. The multifunctional behavior of the composites underscores their potential as advanced materials for integrated dielectric, piezoelectric, and energy storage and harvesting applications. Full article

Pentagonal two-dimensional allotropes—penta-graphene (PG) and penta-SiC₂—are promising but experimentally elusive materials whose identification requires spectroscopic fingerprints that extend beyond ground-state descriptors. Using density functional theory within a core-hole formalism and polarisation-resolved cross sections, we compute element- and site-resolved K-edge spectra for pristine H- and OH-terminated PG, Si-substituted PG, and pristine/H-passivated penta-SiC₂. In PG, the C K-edge shows a ${\pi }^{*}$ onset at 285 eV from three-coordinated C and ${\sigma }^{*}$ bands at 293–303 eV, yielding three plateaus and a strong low-energy z-polarised response. The H/OH functionalisation suppresses the 283–288 eV plateau and weakens the polarisation anisotropy, which can be rationalised by PDOS changes at the two non-equivalent C sites. Si substitution generates a polarisation-dependent Si K-edge doublet (∼1844/1857 eV). In penta-SiC₂, the high-energy Si feature broadens (1850–1860 eV) and the C K-edge becomes strongly anisotropic; H-passivation yields a sharp, almost polarisation-independent C K-edge at 290 eV. The presence of clearly resolved, system-dependent spectral features enables unambiguous experimental discrimination between phases and terminations, facilitating spectroscopic discovery and supporting device development in 2D pentagonal materials. Full article

To address the challenges of model uncertainty, strong nonlinearities, and controller tuning in high-precision trajectory tracking for hydraulic servo systems, this paper proposes a hierarchical GA-PID-MPC fusion strategy. The architecture integrates three functional layers: a Genetic Algorithm (GA) for online parameter optimization, a Model Predictive Controller (MPC) for future-oriented planning, and a Proportional–Integral–Derivative (PID) controller for fast feedback correction. These modules are dynamically coordinated through an adaptive cost-aware blending mechanism based on real-time performance evaluation. The MPC module operates on a linearized state–space model and performs receding-horizon control with weights and horizon length $\theta =[q,r,T_p]$ tuned by GA. In parallel, the PID controller is enhanced with online gain projection to mitigate nonlinear effects. The blending coefficient $\sigma \left(t\right)$ is adaptively updated to balance predictive accuracy and real-time responsiveness, forming a robust single-loop controller. Rigorous theoretical analysis establishes global input-to-state stability and $H_{\infty }$ performance under average dwell-time constraints. 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

Sustainable development (SD) is vital for the progress of Chinese provinces, especially in the face of emerging challenges. This study constructs an index system for SD based on five dimensions: economic, social, ecological, political, and cultural aspects, aligning with scientific connotations and contemporary requirements. We employ an improved entropy-weight-TOPSIS method to assess the SD of 30 provinces from 2012 to 2022. Our analysis explores the dynamic evolution, regional disparities, coupling coordination, long-term trends, and convergence of provincial SD. The findings include: (1) Provincial SD in China has shown consistent growth, but significant regional disparities remain, forming a gradient distribution from high to low in the order of “East-Central-Northeast-West.” (2) While both intra-regional and inter-regional SD differences have decreased over time, inter-regional disparities continue to be significant, serving as the primary source of regional differences. (3) Coupling and coordination across the five dimensions of SD have improved; however, an imbalance persists, with uncoordinated development remaining a prominent issue. (4) A clear “club convergence” phenomenon is observed, indicating that the SD of neighboring provinces influences one another. Higher SD in adjacent regions increases the likelihood of upward shifts, while lower SD tends to lead to downward shifts. (5) Evidence of both σ-convergence and β-convergence in provincial SD development suggests that SD is ultimately converging toward a stable state. These findings provide valuable insights for policymakers aiming to enhance sustainable development across China’s provinces. Full article

This article constructs an evaluation index system for the development of nutrition-sensitive agriculture in China and measures the development level of nutrition-sensitive agriculture using the entropy method, based on the panel data of 31 provinces from 2000 to 2022. The Dagum Gini coefficient is employed to analyze the magnitude and sources of regional differences in the development level between the whole country and the four major regions. The Kernel density estimation method is applied to describe the dynamic evolutionary characteristics of the development level in different regions. Furthermore, this study delves into the σ convergence and β convergence characteristics of the development level. The results show the following: (a) The level of nutrition-sensitive agricultural development at the national level and in the four major regions has been rising year by year, with a clear spatial pattern of “high in the east and low in the west”. (b) There are significant regional differences at the national level and in the four major regions, which tend to widen. (c) The dynamic evolution characteristics of the development level of nutrition-sensitive agriculture in various regions differ greatly, with polarization in the national, eastern, western and northeastern regions. (d) There is no σ convergence in the development level of nutrition-sensitive agriculture in the country or in the four major regions, but there is absolute β convergence and conditional β convergence in all of them, with the northeastern and central regions having faster convergence speeds; the “catching-up effect” is obvious. The report concludes by outlining the policy ramifications for implementing a methodical and comprehensive strategy approach to support regionally coordinated development plans for leapfrogging and upgrading. Full article