Dynamic evolution of COVID-19 vaccine hesitancy over 2021-2023 among Chinese population: Repeated nationwide cross-sectional study.

Globally, the rollout of COVID-19 vaccine had been faced with a significant barrier in the form of vaccine hesitancy. This study adopts a multi-stage perspective to explore the prevalence and determinants of COVID-19 vaccine hesitancy, focusing on their dynamic evolutionary features. Guided by the integrated framework of the 3Cs model (complacency, confidence, and convenience) and the EAH model (environmental, agent, and host), this study conducted three repeated national cross-sectional surveys. These surveys carried out from July 2021 to February 2023 across mainland China, targeted individuals aged 18 and older. They were strategically timed to coincide with three critical vaccination phases: universal coverage (stage 1), partial coverage (stage 2), and key population coverage (stage 3). From 2021 to 2023, the surveys examined sample sizes of 29 925, 6659, and 5407, respectively. The COVID-19 vaccine hesitation rates increased from 8.39% in 2021 to 29.72% in 2023. Urban residency, chronic condition, and low trust in vaccine developer contributed to significant COVID-19 vaccine hesitancy across the pandemic. Negative correlations between the intensity of vaccination policies and vaccine hesitancy, and positive correlations between vaccine hesitancy and long COVID, were confirmed. This study provides insights for designing future effective vaccination programs for emerging vaccine-preventable infectious X diseases.

Spatial disparities and dynamic evolution of professional public health resource supply level in Beijing, China.

BACKGROUND: This study aims to explore the development status of the supply level of professional public health resources in Beijing Municipality, analyze the areal differences and spatial distribution characteristics of the supply level in 16 districts, and provide a scientific basis for promoting the balanced development of the supply level of professional public health resources in each district of Beijing Municipality. METHODS: Based on panel data from Statistical Yearbook of Health Work in Beijing Municipality and Health and Family Planning Work in Beijing Municipality from 2014 to 2022. Using the entropy method to measure the supply level of professional public health resources in Beijing, employing the Dagum Gini coefficient and Kernel density estimation method to analyze the spatial differentiation characteristics and dynamic evolution process of the supply level, and using heat maps to display the spatial distribution of the supply level in various districts of Beijing. RESULTS: The Dagum Gini coefficient of the supply level of professional public health resources in Beijing Municipality decreased continuously from 0.3419 in 2014 to 0.29736 in 2020, then gradually increased, showing a trend of initially decreasing and then increasing overall spatial differences. The spatial differences mainly stem from differences between areas. The kernel density curve shows that the supply level of professional public health resources in Beijing Municipality gradually increased, slightly decreased after 2021, and did not form a situation of two or multi-level differentiation. CONCLUSION: From 2014 to 2022, the supply level of professional public health resources in Beijing Municipality showed an overall upward trend, but attention should be paid to the decline after 2021; spatial differences initially decreased and then increased, and the differences between areas is the main source of the overall difference in Beijing. Therefore, the Beijing Municipal Government should focus on narrowing the differences between areas, determine the allocation and management of public health resources based on the actual situation of core areas, promote coordinated development within and outside areas, and thus enhance the supply level of professional public health resources.

Dynamic evolution and spatial difference of public health service supply in economically developed provinces of China: typical evidence from Guangdong Province.

OBJECTIVE: The outbreak of the COVID-19 pandemic has drawn attention from all sectors of society to the level of public health services. This study aims to investigate the level of public health service supply in the four major regions of Guangdong Province, providing a basis for optimizing health resource allocation. METHODS: This article uses the entropy method and panel data of 21 prefecture-level cities in Guangdong Province from 2005 to 2021 to construct the evaluation index system of public health service supply and calculate its supply index. On this basis, the standard deviation ellipse method, kernel density estimation, and Markov chain are used to analyze the spatiotemporal evolution trend of the public health service supply level in Guangdong Province. The Dagum Gini coefficient and panel regression model are further used to analyze the relative differences and the key influencing factors of difference formation. Finally, the threshold effect model is used to explore the action mechanism of the key factors. RESULTS: Overall, the level of public health service supply in Guangdong Province is on an upward trend. Among them, polarization and gradient effects are observed in the Pearl River Delta and Eastern Guangdong regions; the balance of public health service supply in Western Guangdong and Northern Mountainous areas has improved. During the observation period, the level of public health services in Guangdong Province shifted towards a higher level with a smaller probability of leapfrogging transition, and regions with a high level of supply demonstrated a positive spillover effect. The overall difference, intra-regional difference and inter-regional difference in the level of public health service supply in Guangdong Province during the observation period showed different evolutionary trends, and spatial differences still exist. These differences are more significantly positively affected by factors such as the level of regional economic development, the degree of fiscal decentralization, and the urbanization rate. Under different economic development threshold values, the degree of fiscal decentralization and urbanization rate both have a double threshold effect on the role of public health service supply level. CONCLUSION: The overall level of public health service supply in Guangdong Province has improved, but spatial differences still exist. Key factors influencing these differences include the level of regional economic development, the degree of fiscal decentralization, and the urbanization rate, all of which exhibit threshold effects. It is suggested that, in view of the actual situation of each region, efforts should be made to build and maintain their own advantages, enhance the spatial linkage of public health service supply, and consider the threshold effects of key factors in order to optimize the allocation of health resources.

Research on the coupling measurement of medical education and health resource allocation under the background of healthy China.

OBJECTIVE: To analyze the coupling and coordination level of medical education and health resource allocation in China, and to provide scientific basis for promoting the high-quality development of medical education and the efficient allocation of health resources. METHODS: Based on the panel data from 2011 to 2021, the coupling coordination degree model was used to measure the coupling coordination index of medical education and health resources in China. The spatial auto-correlation model was used to analyze the development status and distribution characteristics of the coupling coordination degree of the two systems. The kernel density estimation method was used to analyze the dynamic evolution trend of the coupling coordination of the two systems. The QR quantile regression model was used to explore the key factors affecting the coupling coordination degree of the two systems. RESULTS: During the observation period, the coupling coordination degree of the two systems increased from 0.393 to 0.465, with a growth rate of 18.3%. The coupling coordination degree between regions gradually decreased in the eastern-central and eastern-western regions, and there were still large differences between the central and western regions. The coupling coordination degree of the two systems in the region was significantly different in the eastern and western regions, and the central region was relatively similar. There is a positive spatial correlation between the provinces, and 25.81% of the provinces have transitions. Finally, the number of points in the first and third quadrants is higher than that in the second and fourth quadrants. In the process of dynamic distribution, the degree of polarization of the coupling coordination degree curve of the two systems is gradually weakened. Per capita GDP, residents ' income difference and population size are the positive and significant factors driving the coupling and coordinated development of the two systems. CONCLUSION: The coupling and coordination degree of the two systems of medical education and health resource allocation showed a stable upward trend during the observation period, and the global spatial positive correlation also gradually increased, showing the spatial agglomeration characteristics of ' high-high agglomeration ' and ' low-low agglomeration '. The spatial difference of coupling coordination degree shows a shrinking trend and develops towards equalization. The coupling coordination degree of the two systems is affected by social, economic and demographic factors to varying degrees. Therefore, it is necessary to innovate the coordinated development mechanism of the two systems, promote the two-way flow of medical education and health resource allocation in talents, technology and other elements, and then promote the coupling and coordinated development of the two systems.

Study on the response analysis of LID hydrological process to rainfall pattern based on framework for dynamic simulation of urban floods.

An in-depth analysis of the urban flood disaster level in response to different rainfall characteristics and Low Impact Development (LID) measures is of significant importance for addressing unfavorable management conditions and implementing effective flood control measures. This study proposes a dynamic urban flood simulation framework based on the Storm Water Management Model (SWMM) and Geographic Information System (GIS) spatial analysis, incorporating an active inundation seed search algorithm. The framework is calibrated and validated using nine historical urban flood events. Subsequently, the impact of rainfall patterns on urban inundation under LID measures is analyzed based on the dynamic urban flood simulation framework. The results show that the urban flood simulation framework exhibits good applicability, with Nash-Sutcliffe Efficiency (NSE) values of 0.825 and 0.763 during the calibration and validation periods, respectively. The extent of inundation shows little variation for rainfall events with a return period greater than 20 years, and the location of flooding is minimally affected by rainfall patterns. LID measures have a decreasing effect on urban inundation control as the return period of rainfall increases, and there are variations in hydrological responses to different rainfall patterns under the same return period. For single-peak rainfall events with the same return period, the control rates of inundation volume, flow, and infiltration decrease as the rainfall peak coefficient increases, indicating a weakening effect of LID measures on flood control with increasing rainfall peak coefficient. Under the same return period conditions, LID measures exhibit the best runoff control effect for uniform rainfall, while their effectiveness is lower for double-peak rainfall events and single-peak rainfall events with an r = 0.75 coefficient. The findings of this study provide a theoretical basis for urban flood warning and management of Low Impact Development measures.

The Dynamic Evolution Model of the Chemical and Carbon Isotopic Composition of C1-3 during the Hydrocarbon Generation Process.

A new approach is presented in this paper for the dynamic modeling of the chemical and isotopic evolution of C1-3 during the hydrocarbon generation process. Based on systematic data obtained from published papers for the pyrolysis of various hydrocarbon sources (type I kerogen/source rock, type II kerogen/source rock, type III kerogen/source rock, crude oil, and asphalt, etc.), the empirical evolution framework of the chemical and isotopic composition of C1-3 during the hydrocarbon generation process was built. Although the empirical framework was built only by fitting a large amount of pyrolysis data, the chemical and isotopic composition of C1-3 derived from the pyrolysis experiments all follow evolution laws, convincing us that it is applicable to the thermal evolution process of various hydrocarbon sources. Based on the simplified formula of the isotopic composition of mixed natural gas at different maturities (δ13Cmixed), δ13Cmixed = X×niA×δ13CiA+Y×niB×δ13CiBX×niA+Y×niB, it can be derived that the cumulative isotopic composition of alkane generated in a certain maturity interval can be expressed by the integral of the product of the instantaneous isotopic composition and instantaneous yield at a certain maturity point, and then divided by the cumulative yield of alkane generated in the corresponding maturity interval. Thus, the cumulative isotopic composition (A(X)), cumulative yield (B(X)), instantaneous isotope (C(X)), and instantaneous yield (D(x)) in the dynamic model, comply with the following formula during the maturity interval of (X0~X). A(X) = ∫X0XCX×DXdxB(X), where A(X) and B(X) can be obtained by the fitting of pyrolysis data, and D(x) can also be obtained from the derivation of B(X). The dynamic model was applied on the pyrolysis data of Pingliang Shale to illustrate the quantitative evolution of the cumulative yield, instantaneous yield, cumulative isotope, and instantaneous isotope of C1-3 with increasing maturity. The dynamic model can quantify the yield of methane, ethane, and propane, as well as δ13C1, δ13C2, and δ13C3, respectively, during the hydrocarbon generation process. This model is of great significance for evaluating the natural gas resources of hydrocarbon source rock of different maturities and for identifying the origin and evolutionary process of hydrocarbons by chemical and isotopic data. Moreover, this model provides an approach to study the dynamic evolution of the isotope series of C1-3 (including reversed isotopic series), which is promising for revealing the mechanism responsible for isotopic reversal when combined with post-generation studies.

Boosting Electrocatalytic Carbon Dioxide Reduction via Self-Relaxation of Asymmetric Coordination in Fe-Based Single Atom Catalyst.

Addressing the limitations arising from the consistent catalytic behavior observed for various intermediates during the electrochemical carbon dioxide reduction reaction (CO2 RR) poses a significant challenge in the optimization of catalytic activity. In this study, we aimed to address this challenge by constructing an asymmetric coordination Fe single atom catalyst (SCA) with a dynamically evolved structure. Our catalyst, consisting of a Fe atom coordinated with one S atom and three N atoms (Fe-S1 N3 ), exhibited exceptional selectivity (CO Faradaic efficiency of 99.02 %) and demonstrated a high intrinsic activity (TOF of 7804.34 h-1 ), and remarkable stability. Using operando XAFS spectra and Density Functional Theory (DFT) calculations, we elucidated the self-relaxation of geometric distortion and dynamic evolution of bond lengths within the catalyst. These structure changes enabled independent regulation of the *COOH and *CO intermediate adsorption energies, effectively breaking the linear scale relationship and enhancing the intrinsic activity of CO2 RR. This study provides valuable insights into the dynamic evolution of SACs and paves the way for targeted catalyst designs aimed to disrupt the linear scaling relationships.

Electrocatalytic Mechanism of Defect in Spinels for Water and Organics Oxidation.

Spinels display promising electrocatalytic ability for oxygen evolution reaction (OER) and organics oxidation reaction because of flexible structure, tunable component, and multifold valence. Unfortunately, limited exposure of active sites, poor electronic conductivity, and low intrinsic ability make the electrocatalytic performance of spinels unsatisfactory. Defect engineering is an effective method to enhance the intrinsic ability of electrocatalysts. Herein, the recent advances in defect spinels for OER and organics electrooxidation are reviewed. The defect types that exist in spinels are first introduced. Then the catalytic mechanism and dynamic evolution of defect spinels during the electrochemical process are summarized in detail. Finally, the challenges of defect spinel electrocatalysts are brought up. This review aims to deepen the understanding about the role and evolution of defects in spinel for electrochemical water/organics oxidation and provide a significant reference for the design of efficient defect spinel electrocatalysts.

Great transition and new pattern: Agriculture and rural area green development and its coordinated relationship with economic growth in China.

Agricultural and Rural Green Development (ARGD) and economic growth are major challenges prevalent in China, but also in other developing countries. A notable gap in current literature lies in the limited holistic approach to agriculture and rural areas, with scant attention being paid to the spatiotemporal evolution of ARGD and its coordination relationship with economic growth. This paper first offers a theoretical analysis of the interactive relationship between ARGD and economic growth and subsequently examines the policy implementation process in China in this regard. It observes 31 provinces in China from 1997 to 2020 to uncover the spatiotemporal evolution of Agricultural and Rural Green Development Efficiency (ARGDE). Using the coupling coordination degree (CCD) model and the local spatial autocorrelation model, this paper analyses the coordination relationship and spatial correlation between ARGDE and economic growth. The results show that ARGDE in China exhibited a phased growth trend and was greatly affected by policies during 1997-2020. The interregional ARGD produced a hierarchical effect. However, provinces with a higher ARGDE did not necessarily exhibit faster growth, leading to a differential pattern of optimization that involved continuous optimization, phased optimization, and continuous deterioration. Over a long period, ARGDE exhibited a trend of significant upward leaps or jumps. Finally, the CCD between ARGDE and economic growth improved, with a clear trend of high-high agglomeration characteristics that shifted from the eastern and northeastern provinces to the central and western ones. This suggests that promoting "quality agriculture" and "green agriculture" can have practical significance in accelerating the development of ARGD. In the future, it is vital to promote ARGD's transformation while mitigating the risk of degrading the coordinated relationship between ARGD and economic growth.

Supply Chain Risk Diffusion in Partially Mapping Double-Layer Hypernetworks.

The impact of COVID-19 is global, and uncertain information will affect product quality and worker efficiency in the complex supply chain network, thus bringing risks. Aiming at individual heterogeneity, a partial mapping double-layer hypernetwork model is constructed to study the supply chain risk diffusion under uncertain information. Here, we explore the risk diffusion dynamics, drawing on epidemiology, and establish an SPIR (Susceptible-Potential-Infected-Recovered) model to simulate the risk diffusion process. The node represents the enterprise, and hyperedge represents the cooperation among enterprises. The microscopic Markov chain approach (MMCA) is used to prove the theory. Network dynamic evolution includes two removal strategies: (i) removing aging nodes; (ii) removing key nodes. Using Matlab to simulate the model, we found that it is more conducive to market stability to eliminate outdated enterprises than to control key enterprises during risk diffusion. The risk diffusion scale is related to interlayer mapping. Increasing the upper layer mapping rate to strengthen the efforts of official media to issue authoritative information will reduce the infected enterprise number. Reducing the lower layer mapping rate will reduce the misled enterprise number, thereby weakening the efficiency of risk infection. The model is helpful for understanding the risk diffusion characteristics and the importance of online information, and it has guiding significance for supply chain management.

China's agricultural GHG emission efficiency: regional disparity and spatial dynamic evolution.

Improving China's agricultural greenhouse gases (GHG) emission efficiency has become an important way to cope with climate change in an ecologically-and ethically responsible manner. In this paper, we use a global slacks-based inefficiency model to evaluate the agricultural greenhouse gases (GHG) emission efficiency levels in China during 2000-2015. The regional disparity of China's GHG emission efficiency is examined by using a Dagum Gini coefficient. A spatial Markov chain technique is also employed to investigate the spatial dynamic evolution of agricultural GHG emission efficiency. The results show that: (1) China's agricultural GHG emission efficiency increased steadily during the study period; a certain gap in efficiency among provinces and regions also exists. (2) Between-group disparity is the main source of the overall regional disparities in China's agricultural GHG emission efficiency. The disparities between regions are on the rise, while the disparities within regions are relatively stable. (3) China's agricultural GHG emission efficiency demonstrates significant spatial dependence. This study provides policy implications for the sustainable development of China's agricultural sector.

[The measurements of the similarity of dynamic brain functional network].

Brain functional network changes over time along with the process of brain development, disease, and aging. However, most of the available measurements for evaluation of the difference (or similarity) between the individual brain functional networks are for charactering static networks, which do not work with the dynamic characteristics of the brain networks that typically involve a long-span and large-scale evolution over the time. The current study proposes an index for measuring the similarity of dynamic brain networks, named as dynamic network similarity (DNS). It measures the similarity by combining the "evolutional" and "structural" properties of the dynamic network. Four sets of simulated dynamic networks with different evolutional and structural properties (varying amplitude of changes, trend of changes, distribution of connectivity strength, range of connectivity strength) were generated to validate the performance of DNS. In addition, real world imaging datasets, acquired from 13 stroke patients who were treated by transcranial direct current stimulation (tDCS), were used to further validate the proposed method and compared with the traditional similarity measurements that were developed for static network similarity. The results showed that DNS was significantly correlated with the varying amplitude of changes, trend of changes, distribution of connectivity strength and range of connectivity strength of the dynamic networks. DNS was able to appropriately measure the significant similarity of the dynamics of network changes over the time for the patients before and after the tDCS treatments. However, the traditional methods failed, which showed significantly differences between the data before and after the tDCS treatments. The experiment results demonstrate that DNS may robustly measure the similarity of evolutional and structural properties of dynamic networks. The new method appears to be superior to the traditional methods in that the new one is capable of assessing the temporal similarity of dynamic functional imaging data.

Surface Degradation of Single-crystalline Ni-rich Cathode and Regulation Mechanism by Atomic Layer Deposition in Solid-State Lithium Batteries.

Single-crystalline Ni-rich cathode (SC-NCM) has attracted increasing interest owing to its greater capacity retention in advanced solid-state lithium batteries (SSLBs), while suffers from severe interfacial instability during cycling. Here, via atomic layer deposition, Li3 PO4 is introduced to coat SC-NCM (L-NCM), to suppress undesired side reaction and enhance interfacial stability. The dynamic degradation and surface regulation of SC-NCM are investigated inside a working SSLB by in situ atomic force microscopy (AFM). We directly observe the uneven cathode electrolyte interphase (CEI) and surface defects on pristine SC-NCM particle. Remarkably, the formed amorphous LiF-rich CEI on L-NCM maintains its initial structure upon cycling, and thus endows the battery with improved cycling stability and excellent rate capability. Such on-site tracking provides deep insights into surface mechanism and structure-reactivity correlation of SC-NCM, and thus benefits the optimizations of SSLBs.

Comparative genomic analysis of Polypodiaceae chloroplasts reveals fine structural features and dynamic insertion sequences.

BACKGROUND: Comparative chloroplast genomics could shed light on the major evolutionary events that established plastomic diversity among closely related species. The Polypodiaceae family is one of the most species-rich and underexplored groups of extant ferns. It is generally recognized that the plastomes of Polypodiaceae are highly notable in terms of their organizational stability. Hence, no research has yet been conducted on genomic structural variation in the Polypodiaceae. RESULTS: The complete plastome sequences of Neolepisorus fortunei, Neolepisorus ovatus, and Phymatosorus cuspidatus were determined based on next-generation sequencing. Together with published plastomes, a comparative analysis of the fine structure of Polypodiaceae plastomes was carried out. The results indicated that the plastomes of Polypodiaceae are not as conservative as previously assumed. The size of the plastomes varies greatly in the Polypodiaceae, and the large insertion fragments present in the genome could be the main factor affecting the genome length. The plastome of Selliguea yakushimensis exhibits prominent features including not only a large-scale IR expansion exceeding several kb but also a unique inversion. Furthermore, gene contents, SSRs, dispersed repeats, and mutational hotspot regions were identified in the plastomes of the Polypodiaceae. Although dispersed repeats are not abundant in the plastomes of Polypodiaceae, we found that the large insertions that occur in different species are mobile and are always adjacent to repeated hotspot regions. CONCLUSIONS: Our results reveal that the plastomes of Polypodiaceae are dynamic molecules, rather than constituting static genomes as previously thought. The dispersed repeats flanking insertion sequences contribute to the repair mechanism induced by double-strand breaks and are probably a major driver of structural evolution in the plastomes of Polypodiaceae.

Identifying the Evolution of Selenium-Vacancy-Modulated MoSe2 Precatalyst in Lithium-Sulfur Chemistry.

Witnessing compositional evolution and identifying the catalytically active moiety of electrocatalysts is of paramount importance in Li-S chemistry. Nevertheless, this field remains elusive. We report the scalable salt-templated synthesis of Se-vacancy-incorporated MoSe2 architecture (SeVs-MoSe2 ) and reveal the phase evolution of the defective precatalyst in working Li-S batteries. The interaction between lithium polysulfides and SeVs-MoSe2 is probed to induce the transformation from SeVs-MoSe2 to MoSeS. Furthermore, operando Raman spectroscopy and ex situ X-ray diffraction measurements in combination with theoretical simulations verify that the effectual MoSeS catalyst could help promote conversion of Li2 S2 to Li2 S, thereby boosting the capacity performance. The Li-S battery accordingly exhibits a satisfactory rate and cycling capability even with and elevated sulfur loading and lean electrolyte conditions (7.67 mg cm-2 ; 4.0 µL mg-1 S ). This work elucidates the design strategies and catalytic mechanisms of efficient electrocatalysts bearing defects.

Inequalities of China's regional low-carbon development.

As China plays an important role in global climate change, investigating its low-carbon development (LCD) will shed light on the global low-carbon economy. This study aims to explore the drivers of LCD inequality and evolution based on an extended spatial decomposition model. We find that potential energy intensity is the most important factor responsible for both national LCD inequality and its evolution. Further analysis suggests that the central region made some progress in LCD due to the decline of potential energy intensity. Nonetheless, the west must pay attention to the high potential energy intensity and deteriorating industry structure for the persistent poor LCD. And the provincial results indicate that the poorer the economy, the worse the LCD. The LCD formation and evolution mechanism of the various provinces are highly heterogeneous. Overall, we underscore the comprehensive investigation of inequality issues of LCD and provide insights for other regions desiring to develop the low-carbon economy.

Two-phase vesicles: a study on evolutionary and stationary models.

In the current article, the dynamic evolution of two-phase vesicles is presented as an extension to a previous stationary model and based on an equilibrium of local forces. In the simplified model, ignoring the effects of membrane inertia, a dynamic equilibrium between the membrane bending potential and local fluid friction is considered in each phase. The equilibrium equations at the domain borders are completed by extended introduction of membrane section reactions. We show that in some cases, the results of stationary and evolutionary models are in agreement with each other and also with experimental observations, while in others the two models differ markedly. The value of our approach is that we can account for unresponsive points of uncertainty using our equations with the local velocity of the lipid membranes and calculating the intermediate states (shapes) in the consequent evolutionary, or response, path.

Uncovering the dynamic evolution of nucleotide-binding site-leucine-rich repeat (NBS-LRR) genes in Brassicaceae.

Plant genomes harbor dozens to hundreds of nucleotide-binding site-leucine-rich repeat (NBS-LRR) genes; however, the long-term evolutionary history of these resistance genes has not been fully understood. This study focuses on five Brassicaceae genomes and the Carica papaya genome to explore changes in NBS-LRR genes that have taken place in this Rosid II lineage during the past 72 million years. Various numbers of NBS-LRR genes were identified from Arabidopsis lyrata (198), A. thaliana (165), Brassica rapa (204), Capsella rubella (127), Thellungiella salsuginea (88), and C. papaya (51). In each genome, the identified NBS-LRR genes were found to be unevenly distributed among chromosomes and most of them were clustered together. Phylogenetic analysis revealed that, before and after Brassicaceae speciation events, both toll/interleukin-1 receptor-NBS-LRR (TNL) genes and non-toll/interleukin-1 receptor-NBS-LRR (nTNL) genes exhibited a pattern of first expansion and then contraction, suggesting that both subclasses of NBS-LRR genes were responding to pathogen pressures synchronically. Further, by examining the gain/loss of TNL and nTNL genes at different evolutionary nodes, this study revealed that both events often occurred more drastically in TNL genes. Finally, the phylogeny of nTNL genes suggested that this NBS-LRR subclass is composed of two separate ancient gene types: RPW8-NBS-LRR and Coiled-coil-NBS-LRR.

Regional differences, dynamic evolution and trend prediction of green manufacturing development levels in China.

Green manufacturing has become a necessary way to promote new industrialization and realize the high-quality development of China's manufacturing industry. Based on the panel data of 30 provinces in China from 2012 to 2022, this paper constructs a comprehensive evaluation index system for the green manufacturing development level and introduces the TOPSIS- Gray correlation method to comprehensively measure the green manufacturing development level of China as a whole and the four major regions in the eastern, central, western, and northeastern parts of the country. The regional differences, distribution dynamics and evolutionary trends of China's green manufacturing development level are also explored with the help of the Gini coefficient, kernel density estimation and Markov chain methods. Research Findings: (1) The green manufacturing development level in China is on an upward trend, with an overall spatial distribution pattern of "East is superior and West is inferior". (2) There are regional differences in the green manufacturing development level in China, and the differences are widening, with interregional differences being the main reason for this overall difference. (3) The country as a whole, the central region and the western region are polarized to varying degrees, with the rest of the country showing an improvement in polarization. (4) Without considering spatial factors, the development of green manufacturing in each province experiences "club convergence" in the short term, and it is difficult to realize rapid development. Considering spatial factors, China's green manufacturing development level is generally characterized by "elevated in proximity to high levels and suppressed in proximity to low levels", and in the long run, it shows a distribution trend toward the concentration of high values. The findings of this study can provide new ideas for promoting synergistic efficient development of green manufacturing in China.

Rural revitalization in China: Measurement indicators, regional differences and dynamic evolution.

It is crucial to scientifically assess China's rural revitalization and grasp its evolution laws. This paper constructs an indicator system to measure the level of rural revitalization in China from 2011 to 2021 using the entropy weight method. Then, we explore the spatial and temporal divergence and dynamic evolutionary characteristics of rural revitalization using the Dagum Gini coefficient and Kernel density. We found that the level of rural revitalization in China is low but fluctuating and increasing. Regionally, eastern China scores higher than central, western and northeastern China. In terms of dimensions, ecological livability scores are higher than prosperous industry, effective governance, affluent living and civilized countryside in that order. The regional differences in the level of rural revitalization are mainly reflected between regions, especially between eastern and western China, but the gap between regions is narrowing year by year. And the results of the Kernel density show that the level of rural revitalization in China shows a slow and balanced growth, but the eastern China shows a polarization growth. These findings can provide a comprehensive and objective outline of the advantages and shortcomings of rural revitalization development in China, and provide a policy reference for the comprehensive and stable promotion of rural revitalization construction.