Search Results (261)

Investigating the characteristics and influencing mechanisms of urban vitality in mountainous cities can contribute to enhanced urban resilience, optimised resource allocation, and sustainable development. However, most existing studies have focused on static analyses at single spatial scales, making it difficult to fully reveal the evolutionary trends of urban vitality under complex topographic constraints or the spatiotemporal heterogeneity of its influencing factors. This study examines Guiyang, one of China’s fastest-growing cities, focusing on both its economic development and population growth. Based on social media data and geospatial big data from 2019 to 2024, the spatiotemporal permutation scan statistics (STPSS) model was employed to identify spatiotemporal areas of interest (ST-AOIs) and to analyse the spatial distribution and day-night dynamics of urban vitality across different phases. Furthermore, by incorporating transportation and topographic factors characteristic of mountainous cities, the multiscale geographically and temporally weighted regression (MGTWR) model was applied to reveal the driving mechanisms of urban vitality. The main findings are as follows: (1) Urban vitality exhibits a multi-center, clustered structure, gradually expanding from gentle to steeper slopes over time, with activity patterns shifting from an afternoon peak to an all-day distribution. (2) Significant differences in regional vitality resilience were observed: the core vitality areas exhibited stable ST-AOI spatial patterns, flexible temporal rhythms, and strong adaptability; the emerging vitality areas recovered quickly with low losses, while low-vitality areas showed slow recovery and insufficient resilience. (3) The density of commercial service facilities and the level of housing prices were continuously enhancing factors for vitality improvement, whereas the density of subway stations and the degree of functional mix played key roles in supporting resilience during the COVID-19 pandemic. (4) The synergistic effect between transportation systems and commercial facilities is crucial for forming high-vitality zones in mountainous cities. In contrast, reliance on a single factor tends to lead to vitality spillover. This study provides a crucial foundation for promoting sustainable urban development in Guiyang and other mountainous regions. Full article

AIG1 (avrRpt2-induced gene 1)-like proteins are a class of GTPases that play crucial roles in plants, functioning both in chloroplast protein import and disease resistance. However, their evolutionary history and the mechanisms driving this functional diversification remain poorly understood. Here, we performed a comprehensive genomic and evolutionary analysis of this gene family across the plant kingdom. We identified 90 AIG1-like genes from 11 sequenced plant species, representing major lineages from green algae to angiosperms. Phylogenetic analysis revealed that plant AIG1-like proteins form three monophyletic lineages corresponding to the Toc34, Toc159, and IAN subfamilies, which originated via two ancient duplications predating the divergence of green algae and land plants. These lineages exhibit dramatically divergent evolutionary patterns. The Toc34 subfamily is evolutionarily conserved, maintaining stable copy numbers and gene structure, indicative of strong functional constraints in its core role in plastid import. In contrast, the Toc159 and IAN subfamilies have undergone dynamic expansion via lineage-specific duplication mechanisms, including segmental duplication and prolific tandem duplication, respectively. Notably, we uncovered a novel mechanism for generating head-to-head tandem duplicates in the IAN subfamily, mediated by recombination between inverted repeats. Our analysis of ancestral gene numbers and gene gain/loss dynamics further highlights that functional diversification was driven by both the acquisition of distinct C-terminal targeting domains (M and TM domains) and profound differences in evolutionary rates and duplication modes among subfamilies. This study provides the first full-scale evolutionary framework for plant AIG1-like genes, establishing that functional specialization is rooted in distinct modes of sequence and genomic evolution. Full article

Amid the normalization of flexible employment, labor dispatch, as a form of non-standard employment, has become an important component of China’s precarious labor market (PLM). Based on registration data of labor dispatch firms from 2002 to 2022, this paper analyzes the spatial distribution and evolutionary patterns of China’s PLM, using spatial autocorrelation, kernel density estimation, and Gini coefficient methods. Furthermore, it explores its driving mechanisms through a panel negative binomial regression model. The results show that (i) over the past two decades, China’s PLM has undergone four stages: initiation, acceleration, expansion, and adjustment. (ii) Spatially, it has evolved along the trend of “reinforced clustering with concurrent diffusion,” expanding from first-tier cities in eastern China to second- and third-tier cities in central and western China. (iii) Industrial upgrading, market competition, and the overall level of urban development have significantly promoted the growth of the PLM, while improvements in accessibility, proportion of migrant population, and public service provision have somewhat restrained its expansion. Overall, China’s PLM demonstrates both growth potential and structural vulnerability under institutional constraints and external shocks, offering valuable spatial insights for forging sustainable, high-quality employment and coordinated regional development. Full article

Developing a deep understanding of the evolutionary driving mechanisms of university–industry collaborative innovation networks among Chinese cities is of great significance for advancing sustainable urban development. Based on university–industry collaborative patent data from 275 prefecture-level and above cities in China during the period 2004–2020, this study constructs an intercity university–industry collaborative innovation network and employs the temporal exponential random graph model to analyze its evolutionary driving mechanisms. The results indicate that the network structure has become increasingly complex over time and exhibits pronounced small-world characteristics in the later stages. Network formation is distinctly non-random and is jointly shaped by endogenous structural effects and exogenous factors. Diffusion, connectivity, and closure effects are all significant, while intercity collaborative ties are influenced by multidimensional proximity, including economic, geographic, and organizational proximity. Moreover, the network structure demonstrates strong temporal stability. In the context of high-intensity collaboration, cities place greater emphasis on economic and organizational proximity, and cities with higher levels of economic development and prior experience in high-intensity collaboration are more likely to establish collaborative ties. Furthermore, eastern cities tend to collaborate with partners at similar levels of economic development, whereas cities in central and western regions display a more pronounced core–periphery pattern. Overall, from the perspective of intercity university–industry collaborative innovation networks, this study provides new empirical evidence and insights for promoting coordinated regional innovation capacity and sustainable urban development. Full article

The global countryside constitutes a complex social–ecological system undergoing profound transformation. Understanding how such systems navigate transitions and achieve resilient, sustainable outcomes requires examining the interactions and adaptive behaviors of multiple actors. This study investigates the restructuring of rural China through a complex adaptive systems lens, focusing on the county of Lin’an in Zhejiang Province. We employ a middle-range theory and process-tracing approach to analyze the co-evolutionary pathways shaped by the interactions among three key agents: local governments, enterprises, and village communities. Our findings reveal distinct yet interdependent behavioral logics—local governments and enterprises primarily exhibit instrumental rationality, driven by political performance and profit maximization, respectively, while villages demonstrate value-rational behavior anchored in communal well-being and territorial identity. Crucially, this study identifies the emergence of a vital integrative mechanism, the “village operator” model, underpinned by the collective economy. This institutional innovation facilitates the synergistic linkage of interests and the integration of endogenous and exogenous resources, thereby mitigating conflicts and alienation. We argue that this multi-agent collaboration drives a synergistic restructuring of spatial, economic, and social subsystems. The case demonstrates that sustainable rural revitalization hinges not on the dominance of a single logic, but on the emergence of adaptive governance structures that effectively coordinate diverse actor logics. This process fosters systemic resilience, enabling the rural system to adapt to external pressures and internal changes. The Lin’an experience offers a transferable framework for understanding how coordinated multi-agent interactions can guide complex social–ecological systems toward sustainable transitions. Full article

The healthy evolution of an entrepreneurial ecosystem relies on the symbiotic relationships among its diverse internal actors. This study addresses a gap in entrepreneurial ecosystem research, which has predominantly focused on two-agent models, by constructing a tripartite symbiotic evolution model that incorporates entrepreneurial ventures, incubation chains, and customers. Based on the Logistic and Lotka-Volterra models, the research identifies the system’s equilibrium points and their stability conditions. Simulations reveal evolutionary paths from parasitism and commensalism to mutualism. A comparative case study of SenseTime (Shanghai, China) and Lanma Technology (Shanghai, China) validates these findings. The comparison shows that an influx of multiple agents, coupled with the core venture’s ability to strengthen key symbiotic coefficients, drives the ecosystem towards a dynamic multi-agent symbiosis in the post-optimization phase. Conversely, the failure to establish these robust reciprocal value flows leads to ecosystem fragility. The results indicate that: (1) Multi-agent entrepreneurial ecosystems are complex systems where symbiotic units form adaptive relationships for value creation, adhering to market laws. (2) The system’s equilibrium depends on symbiotic coefficients, leading to four modes—independent coexistence, parasitism, commensalism, and mutualism—with mutualism being the optimal state. (3) The contrasting cases further demonstrate that the evolution towards mutualism is not automatic but hinges on the core venture’s strategic agency in constructing and strengthening synergistic pathways with forward and backward linkages. This study provides a theoretical model for understanding the evolutionary mechanisms of entrepreneurial ecosystems and offers practical insights for optimizing ecosystem governance. Full article

To address the structural differences between closed-track and open-road testing in terms of scenario coverage, risk controllability, and validation consistency, this study proposes a scenario-driven combined testing method for automated driving systems. The proposed approach constructs a multi-dimensional scenario space based on functional decomposition and jointly quantifies scenario complexity and hazard level from the perspectives of information heterogeneity and interaction-induced risks. Based on these two-dimensional scenario attributes, a fuzzy inference mechanism is developed to dynamically allocate validation resources across different testing environments. To further improve rule-base generalization and mapping stability, an enhanced genetic algorithm integrating simulated annealing and K-means clustering is introduced to optimize the rule structures in an evolutionary manner. Experimental results demonstrate that, compared with traditional testing methods and single-mechanism optimization strategies, the proposed approach achieves a more consistent and interpretable mapping between scenarios and testing proportions in high-complexity urban traffic scenarios. While ensuring test adequacy, the testing economy is significantly improved, with an overall average improvement exceeding 20%. In addition, stable resource allocation performance is observed across multiple scenarios with different levels of complexity and risk, confirming the scalability and applicability of the proposed method for multi-scenario automated driving system testing. Full article

Flow velocity is a key environmental factor that exerts multifaceted effects on fish growth and adaptation. Through long-term natural selection, fish have evolved adaptability to specific flow conditions, which not only relate to oxygen supply and food acquisition but also play a decisive role in reproduction, development, and population maintenance. To investigate the genomic mechanisms through which hydrodynamic environments drive divergence in closely related species, we focused on two sister species, Hemiculter bleekeri and Hemiculter leucisculus, which are adapted to contrasting flow regimes. We generated high-quality, chromosome level telomere-to-telomere (T2T) genomes and integrated comparative genomic analyses, we investigated the genetic basis underlying body shape regulation and reproductive strategies, aiming to decipher the adaptive evolutionary patterns of these species in response to differing hydrodynamic conditions from an integrated genotype phenotype perspective. We integrated PacBio HiFi, Hi-C, and Oxford Nanopore Technologies (ONT) ultra-long read sequencing data to construct high-quality T2T reference genomes for both species. The final genome assemblies are 0.998 Gb for H. bleekeri and 1.05 Gb for H. leucisculus, with each species possessing 24 chromosomes and all chromosomal sequences assembled into single contigs. Contig N50 values reached 40.45 Mb and 40.66 Mb, respectively, and both assemblies are gap-free. BUSCO assessments yielded completeness scores of 99.34% for both genomes, confirming their high continuity and accuracy. Integrated morphometric and genomic analyses revealed distinct adaptive strategies in two Hemiculter Species. H. bleekeri has evolved a streamlined body, underpinned by expansions in body shape related genes, and a pelagic egg strategy. In contrast, the adhesive egg strategy of H. leucisculus is supported by expansions in adhesion-related gene families. This divergence reflects adaptation to distinct flow velocity. By combining high-quality chromosome-level T2T genomes with morphometric and comparative genomic approaches, this study establishes a comprehensive framework for understanding the molecular mechanisms underlying adaptive evolution in freshwater fishes inhabiting contrasting flow velocity. Full article

Background/Objectives: The mammalian microbiota constitutes a reservoir of antimicrobial resistance genes (ARGs), which can be shaped by environmental and anthropogenic factors. Although bat-associated bacteria have been reported to harbor diverse ARGs globally, the ecological and evolutionary determinants driving this diversity remain unclear. Methods: To characterize ARG diversity in wildlife exposed to contrasting levels of human influence, we analyzed homologs of resistance mechanisms from the Comprehensive Antibiotic Resistance Database in shotgun metagenomes of bat guano. Samples were collected from a colony exposed to continuous anthropogenic activity in Spain (Salamanca) and from a wild, non-impacted bat community in China (Guangdong). Metagenomic analyses revealed marked differences in taxonomic and resistome composition between sites. Results: Salamanca samples contained numerous hospital-associated genera (e.g., Mycobacterium, Staphylococcus, Corynebacterium), while Guangdong was dominated by Lactococcus, Aeromonas, and Stenotrophomonas. β-lactamases and MurA transferase homologs were the most abundant ARGs in both datasets, yet Salamanca exhibited higher richness and functional diversity (median Shannon index = 1.5; Simpson = 0.8) than Guangdong (Shannon = 1.1; Simpson = 0.66). Salamanca also showed enrichment of clinically relevant ARGs, including qacG, emrR, bacA, and acrB, conferring resistance to antibiotics critical for human medicine. In contrast, Guangdong exhibited a more restricted resistome dominated by β-lactamase and MurA homologs. Beta diversity analysis confirmed significant compositional differences between resistomes (PERMANOVA, R² = 0.019, F = 1.33, p = 0.001), indicating ecological rather than stochastic structuring. Conclusions: These findings suggest that anthropogenic exposure enhances the diversity and evenness of resistance mechanisms within bat-associated microbiomes, potentially increasing their role as reservoirs of antimicrobial resistance. Full article

This study investigates the spatial patterns and driving mechanisms of China’s industrial heritage using nationwide provincial-level geospatial data. It combines multiple spatial analysis techniques to identify distribution characteristics and applies a multi-model framework integrating Multi-Scale Geographically Weighted Regression and machine learning to assess the impacts of demographic, economic, climatic, and topographic factors. Results reveal a pronounced clustered pattern and marked spatial differentiation, with core concentrations in the southeastern coastal and central regions. Industrial layouts across historical periods show a shift from coastal to inland areas, reflecting security-oriented spatial strategies. Economic development has a significant positive influence, whereas temperature and the number of industrial enterprises exert negative effects. Natural environmental conditions—such as slope, vegetation coverage, and water systems—serve as both spatial supports and constraints. At the macro level, the spatial configuration of industrial heritage emerges from the structured interplay of historical path dependence, national strategic regulation, and geographic environmental constraints, rather than short-term interactions among isolated variables. The study elucidates the evolutionary logic of industrial civilization and highlights the synergistic mechanisms linking economic, social, and environmental dimensions. It concludes by advocating a hierarchical and multi-factor balanced framework for spatial governance. Full article

As the aging society progresses, it is particularly important to strengthen the sharing of silver economy data to promote the development of the silver economy. This paper focuses on analyzing the mechanism by which digital platforms promote silver economy data sharing and constructs an evolutionary game model that includes government departments, digital platforms, enterprises, and elderly people. On this basis, the stability of the strategies of each subject in the system is analyzed, and the influence of key parameters is also discussed. The simulation draws the following conclusions. Firstly, initial strategy proportions significantly influence evolutionary directions. Higher initial proactive participation increases the probability of convergence to the optimal state. Secondly, digital platforms are driven by government regulation intensity, user complaint probabilities, and reputational losses. Increasing fines and user complaint probabilities incentivize platforms to offer high-quality protection. Thirdly, government departments can initially incentivize enterprises and elderly people to participate in data sharing through subsidies and tax incentives and build a long-term driving mechanism by improving regulatory mechanisms and enhancing digital literacy among the elderly people. The research results can serve as a reference for government departments to promote data sharing in the silver economy. Full article

Landscapes in semiarid regions are highly sensitive to climate change and anthropogenic activities, and their evolution directly influences ecosystem services and regional ecological security. Although previous research has examined land use changes, systematic quantitative analyses of long-term evolutionary trends and driving mechanisms, particularly the comprehensive relationships between key hydrological elements and landscape pattern evolution in water-scarce, semiarid watersheds, remain limited. To address the research gap in long-term, multifactor, and hydro–landscape integrated analysis, China’s Tuwei River watershed was selected as the study area in this study, and methods such as landscape pattern indices and gray relational analysis were employed to quantitatively reveal the spatiotemporal evolution of watershed landscape fragmentation from 1980 to 2020 and identify its dominant driving forces. The results revealed that (1) over the 40-year period, the land use structure of the watershed underwent significant restructuring, with developed land expanding by 1282%, cropland and bare land areas decreasing by 14.2% and 32.01%, respectively, and grassland and forestland areas increasing by 24.5% and 14.9%, respectively; (2) land-scape fragmentation continued to intensify, with the landscape fragmentation composite index (FCI) increasing by 37.6%, patch density (PD) continuously increasing, edge density (ED) and landscape shape index (LSI) increasing significantly, and landscape connectivity weakening; (3) natural and socioeconomic factors jointly drove landscape evolution, with temperature and mean annual flow contributing the most among natural factors and the urbanization rate and secondary industry output value serving as the core drivers among socioeconomic factors; and (4) the trend of landscape fragmentation was synchronized with changes in annual rainfall and runoff and exhibited a significant negative correlation with the groundwater level. In summary, through long-term, multifactor comprehensive analysis, the evolution characteristics and driving mechanisms of landscape patterns in the Tuwei River watershed were systematically revealed in this study. These findings not only deepen the understanding of landscape fragmentation processes under the dual pressures of climate change and anthropogenic activities but also provide scientific evidence for the sustainable management of landscapes and associated ecosystems in semiarid watersheds. Full article

Salinity is a key abiotic stress limiting crop growth. Accurate quantification of carbon budgets and their environmental responses is critical for sustainable cotton production, yet regional-scale assessments remain scarce. To clarify the evolutionary patterns and driving mechanisms of soil organic carbon (SOC) in saline cotton fields of arid Central Asia, this study focused on Xinjiang and modified the RothC model by integrating salinity adjustment factors and vegetation carbon decomposition indices, simulating SOC dynamics (1980–2022) with multi-source data. Results showed the improved model achieved high accuracy in capturing SOC dynamics in salinized cotton fields. Spatially, SOC exhibited high levels south of the Tianshan Mountains and low levels in southwestern Xinjiang; temporally, it showed an overall fluctuating upward trend, though both high- and low-value zones displayed localized declines. Geodetector analysis revealed fertilizer application as the primary driver of SOC spatial variation, followed by straw return, precipitation, and temperature, with most factors showing synergistic enhancement effects. Human management (fertilization and straw return) is the core regulator of SOC, and its synergy with natural factors shapes SOC spatiotemporal patterns. The salinization-adapted RothC model provides a novel framework for arid cotton field SOC simulation, offering scientific support for carbon pool optimization and sustainable agriculture in arid regions. Full article

This paper presents a systematic review of linear motor-based electromagnetic suspension, a key technology for reconciling vehicle comfort, handling stability, and energy consumption. The review focuses on two core areas: actuator configuration and control strategy. In configuration design, a comparison of moving-coil, permanent magnet synchronous (PMSLM), and switched-reluctance linear motors identifies the PMSLM as the mainstream approach due to its high-power density and performance. Key design challenges for meeting stringent vehicle operating conditions, such as mass-volume optimization, thermal management, and high reliability, are also analyzed. Regarding control strategy, the review outlines the evolutionary path from classical to advanced and intelligent control. It also examines the energy-efficiency trade-off between vibration suppression and energy recovery. Furthermore, the paper summarizes three core challenges for industrialization: nonlinear issues like thrust fluctuation and friction, the coupling of electromagnetic–mechanical–thermal multi-physical fields, and bottlenecks related to high costs and reliability verification. Finally, future research directions are envisioned, including new materials, sensorless control, and active safety integration for autonomous driving. Full article

Soil microbial carbon use efficiency (CUE) is the core of the soil carbon (C) cycle that captures a dual microbial control point between soil organic C (SOC) accumulation and loss. The interpretation of these patterns and drivers of microbial CUE after long-term afforestation remains, however, a major scientific challenge. In particular, there are major uncertainties about the role of microbial traits in driving CUE. Here, we compared sites along a 45-year afforestation chronosequence and combined the novel ¹⁸O-H₂O tracer method with metagenomic analysis to quantify CUE and explore the mechanisms underlying microbe-mediated C dynamics. The results showed that soil microbial CUE significantly increased following afforestation and showed a positive relationship with SOC, which suggested that microbial CUE could promote C accumulation in afforested ecosystems. We further found the critical role of microbial traits in the regulation of CUE through altering microbial life history strategies: microbial CUE was positively and significantly correlated with resource acquisition (A) genes, but showed a negative and significant correlation with stress tolerance (S) strategy genes. These results suggested that soil microbes reduce investment in S strategies and shift to A and high yield (Y) strategies, thereby increasing CUE. This knowledge is important because it advances our understanding of the microbial physiological and evolutionary tradeoffs mediating soil C cycling in the context of human-induced land use change. Full article