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Against the backdrop of China’s carbon emission reduction targets and the promotion of the construction of a unified domestic market, what kind of carbon emission effect has market integration had in weakening regional barriers and optimizing resource allocation? This paper adopts a two-way fixed effects analysis based on China’s provincial panel data from 2003 to 2019. It uses a mediation model to explore the relationship between market integration and carbon emissions. Furthermore, industrial rationalization and upgrade are the basis for examining whether a competitive or cooperative relationship exists between the carbon emission effects generated and promoting market integration between regions. The study finds a negative relationship between market integration and carbon emissions. In addition, there is significant heterogeneity in the effect of market integration on carbon emissions, and the influence effect is mainly in central China; industrial rationalization can play an enhanced role in the process of the negative impact of market integration on carbon emissions, further enhancing the negative contribution of market integration to carbon emissions. However, market integration can weaken its negative impact on carbon emissions with the industrial upgrade, and there may still be invisible barriers between regions in promoting market integration barriers.

China is actively promoting the deep integration of digital technology and manufacturing and helping the manufacturing industry develop into high‐end, intelligent, and green. As the concept of green development gradually deepens and the international situation becomes increasingly severe, it is necessary to discuss the coordinated development of digital technology and the manufacturing green transformation (MGT), which will better promote the realization of the goals of “double carbon,” “digital power” and “manufacturing power.” Based on this, this paper adopts the coupling coordination model, kernel density estimation, Dagum Gini coefficient decomposition, and spatial autocorrelation to conduct a spatiotemporal evolution analysis of the coupling coordination degree (the D‐G system) of digital technology and MGT in 30 provinces (municipalities, autonomous regions) of mainland China from 2011 to 2020, and adopting the spatial Markov chain to predict its evolutionary trend. The key findings of the study are as follows: (1) Digital technology and MGT have been progressing steadily in China, with continuous improvements in the level of development; (2) The degree of coupling coordination has shown consistent growth over the years, yet the distribution remains relatively uneven, exhibiting a “trapezoidal” spatial pattern with higher values in the eastern regions and lower values in the western regions; (3) Regional differences play a crucial role in the overall differences of the D-G system; and (4) The traditional Markov chain results show that the probability of the D‐G system maintaining the original state stage in the future is greater than 88.67%. The spatial Markov chain results show that the state type of the neighborhood background affects the state transition of the coupling coordination degree. The coupling coordination development of each province will not only be subjected to the “spatial drag” of the neighboring region but also show the phenomenon of “club convergence.“ These findings provide valuable theoretical insights and practical recommendations for fostering the simultaneous advancement of digital development and sustainable development.

This paper addresses the effect of population urbanization on Fine Particulate (PM2.5) in the Yangtze River Economic Belt in China from 2006 to 2016 by employing PM2.5 remote sensing data and using the Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) model. The study contributes to the growing empirical literature by addressing heterogeneity, spillover, and dynamic effects in the dynamic spatial panel modeling process simultaneously. The empirical results show that population urbanization has a significant impact on PM2.5 with a positive spillover effect and a dynamic effect being detected and controlled. The heterogeneity effects of population urbanization on PM2.5 due to geographical positions show evidence of an obvious inverted U-shaped curve relationship in the upstream area and an increasing function curve in the midstream and downstream areas. The heterogeneity effects due to population urbanization levels show that an inverted N-shape curve relationship exists in low and medium urbanization level areas, while a U-shape curve relationship exists in high urbanization level areas. It is hoped that this study will inform the local governments about the heterogeneity of population urbanization and spillover effects of air pollution when addressing air pollution control.

China has been facing serious water scarcity, and improving the supply and utilization of water resources from the perspective of resource endowment, economic development and water infrastructure is of great significance toward sustainable water development. In this work, two index systems for evaluating the water supply capacity (WSC) and the water infrastructure construction level (WICL) were constructed; the water resource utilization efficiency (WRUE) was measured by applying a super slack-based measure model; the ordinary least squares and geographically weighted regression models were used to explore the heterogeneity of spatial relationships. The results showed that both WSC (0.15~0.67) and WRUE (0.25~1.18) had spatial heterogeneity. WSC was positively correlated with water resource accessibility and GDP per capita (R2 = 0.406, p < 0.01), which represented water resource endowment and economic development, respectively. WRUE was positively correlated with GDP per capita but was negatively correlated with accessibility (R2 = 0.654, p < 0.01). The relationship of WICL with accessibility and GDP per capita varied over the study’s area. We found that the WSC in the southeast, WRUE in the north and WICL in the south were mainly associated with water resource endowments. The WSC in the north, WRUE in the southwest and WICL in the north were mainly associated with the economic development level. Noteworthily, strengthening the construction of water conservancy is one of the effective ways to improve water supply. Suggestions on improving WSC and WRUE were provided based on different accessibility and economic conditions, to promote the sustainable development of water resources.

Intense human activities have significantly altered landscape structure, affected ecosystem services, and threatened ecological security. However, the spatial coupling relationship between regional ecological security patterns (ESPs) and human activity is still unclear. Taking southwest China as the study area, this study firstly assessed ecosystem service importance (ESI) and then identified ecological sources in conjunction with nature reserves. A minimum cumulative resistance model and circuit theory were used to extract ecological corridors and nodes to construct ESPs, and we further analyzed spatial relationships between ESPs and regional human activity intensity factors. Our results showed that ESI had obvious regional differences, and considering diversity and uniqueness of ecosystem functions, it is crucial for constructing ESPs. The ESPs—195 ecological sources, 490 ecological corridors, 212 ecological pinch points, and 17 barrier points—were important priority areas for ecological protection and restoration and will effectively guide differentiated ecosystem management. Intense human activities had significantly differentiated negative impacts on regional ESPs, and balancing regional ecological protection and economic development can achieve a win–win situation. Our research not only provides a new perspective for constructing ESPs but also provides important practical guidance for maintaining ecological security and landscape sustainability.

Climate change and human activities have considerably changed the spatial patterns and functional elements of regional habitats. Understanding spatiotemporal changes in habitat quality (HQ) and their potential driving factors is essential for maintaining ecosystem health and protecting biodiversity. To explore the effect of physical and human factors on HQ changes in Southwest China, we firstly analyzed the land-use change intensity (LCI). We then evaluated spatiotemporal changes in HQ based on the InVEST model and explored the spatial heterogeneity of the main driving factors of HQ changes based on a geographical detector and a geographical weighted regression model. The results showed that LCI had obvious spatiotemporal differences, and LCI from low-quality habitat to high-quality habitat (LCI1) was significantly higher than that from high-quality habitat to low-quality habitat (LCI2). The HQ improved steadily in Southwest China in 1990–2015, showing a trend of low–high–low from southeast to northwest. Moreover, there were twelve factors, including aboveground biomass, ecological land area ratio, population density, slope, etc., which had a significant impact on the spatial differences in HQ, and the effects of different factors on HQ had observable spatial heterogeneity. The effect of LCI2 on the spatial difference of HQ was greater than that of LCI1. These results suggested that the current ecosystem protection and management policy had a positive effect on improving HQ. Our study provides an important decision-making reference for sustainable land development and utilization and regional ecological protection and restoration.

Immunohistochemistry has become a valuable ancillary tool for the accurate classification of pleuropulmonary and mediastinal neoplasms necessary for therapeutic decisions and predicting prognostic outcome. Diagnostic accuracy has significantly improved because of the continuous discoveries of tumor-associated biomarkers and the development of effective immunohistochemical panels. To increase the accuracy of diagnosis and classify pleuropulmonary neoplasms through immunohistochemistry. Literature review and the author's research data and personal practice experience. This review article highlights that appropriately selecting immunohistochemical panels enables pathologists to effectively diagnose most primary pleuropulmonary neoplasms and differentiate primary lung tumors from a variety of metastatic tumors to the lung. Knowing the utilities and pitfalls of each tumor-associated biomarker is essential to avoid potential diagnostic errors.

PurposeIt has been well reported in many studies globally that the increased atmospheric carbon dioxide (CO2) concentration has positively influenced plant growth in the past century. However, it is crucial to understand how long the tree growth trend will remain alongside the rising CO2 concentration before it is tipped over.MethodsIn this study, we focused on studying the long-term tree growth responses to the rising CO2 concentration, in combination with other environmental factors, and its feedback to the changing climate. This study has reported two tree species, Pseudolarix amabilis (P. amabilis) and Cryptomeria japonica (C. japonica), sampled from a subtropical monsoon forest located in eastern China, and established the long-term tree ring chronologies by applying tree ring width measurement and cross dating, and then, basal area increment (BAI) was calculated. Meanwhile, intrinsic water-use efficiency (iWUE) was calculated through the measurement of carbon isotope composition (δ13C) in tree ring samples, and its relationships with BAI and atmospheric CO2 concentration were also quantified.ResultsBAI values continuously increased in both P. amabilis and C. japonica with the rising of CO2 concentration until the atmospheric CO2 concentration tipping points were reached, after which tree growth started to decline with the rising CO2, while iWUE exerted a continuous increase trend with the increasing CO2 concentration.ConclusionsTree growth of both species was more photosynthesis driven before reaching the maximum BAI points, once the tipping points of atmospheric CO2 were passed, leading to the positive feed of forest carbon cycling to climate change and global warming. Therefore, tree growth was more water limitation driven in the last 20 years.

Various strategies are developed to engineer aligned hierarchical architectures in polymer hydrogels for enhanced mechanical performance. However, chain alignment remains impeded by the presence of hydrogen bonds between adjacent chains. Herein, a facile sacrificial micelle‐assisted‐alignment strategy is proposed, leading to well‐aligned, strong and tough pure chitosan hydrogels. The sacrificial sodium dodecyl sulfate micelles electrostatically interact with the protonated chitosan chains, enabling chain sliding and alignment under uniaxial forces. Subsequently, sacrificial micelles can be easily removed via NaOH treatment, causing the reforming of H‐bond in the chain networks. The strength of the pure chitosan hydrogels increases 140‐fold, reaching 58.9 ± 3.4 MPa; the modulus increases 595‐fold, reaching 226.4 ± 42.8 MPa. After drying‐rehydration, the strength and modulus further rise to 70.3 ± 2.4 and 403.5 ± 76.3 MPa, marking a significant advancement in high‐strength pure chitosan hydrogel films. Furthermore, the designed multiscale architectures involving enhanced crystallinity, well‐aligned fibers, strong interfaces, robust multilayer Bouligand assembly contribute to the exact replica of lobster underbelly with impact resistance up to 6.8 ± 1.0 kJ m−1. This work presents a promising strategy for strong, tough, stiff and impact‐resistant polymer hydrogels via well‐aligned hierarchical design. A sacrificial micelle‐assisted‐alignment strategy is proposed, leading to well‐aligned, strong pure chitosan hydrogels. The strength and modulus of chitosan hydrogels reach 70.3 ± 2.4 and 403.5 ± 76.3 MPa, marking a significant advancement in high‐strength pure chitosan hydrogel films. Furthermore, the designed replica of lobster underbelly shows impact resistance up to 6.8 ± 1.0 kJ m−1.

A strong environmental regulatory framework enhances green technology innovation (GTI), which is crucial for sustainable economic growth. We construct SDM models by using panel data from 108 cities in China’s Yangtze River Economic Belt (YREB) from 2011 to 2020 to investigate the effects of heterogeneous environmental regulations (ER) on GTI in local and neighboring cities. The moderating influence of digital financial inclusion (DFI) is also examined within the SDM model. Our findings reveal that: (1) Different types of ER have varying impacts on GTI. (2) Command-and-control environmental regulation (CER) hinders local GTI but promotes GTI in neighboring cities. Both market-based (MER) and public-participation environmental regulations (PER) promote GTI in both local and neighboring cities. (3) DFI positively moderates the impact of ER on GTI by providing flexible finance support to enterprises. The study concludes with policy recommendations to improve environmental regulation systems, enhance regional synergistic governance, and promote digital financial inclusion for green sustainable development.