The cluster compound [Mo4S4 (μ-O2CC6H5)2(dtp)4] (dtp = S2P (OEt)2)was obtained by the ligand substitution reaction of tetranuclear molybdenum cluster [Mo4S4(μ-dtp)2(dtp)4] in the mixed solvent of acetone, ethanol an...The cluster compound [Mo4S4 (μ-O2CC6H5)2(dtp)4] (dtp = S2P (OEt)2)was obtained by the ligand substitution reaction of tetranuclear molybdenum cluster [Mo4S4(μ-dtp)2(dtp)4] in the mixed solvent of acetone, ethanol and water in the presence of C6H5CO2Na. It is monoclinic and crystallizesin space group C2/c, Mr =1495. 09, a=12. 175 (5) , b=22. 01 (1) , c=20.875(9) ,β=99. 04(4)°; V=5570(5) ; Z=4; Dc= 1. 78g/cm3;μ(MoKα) = 14. 52 cm-1; F(000) =2984. Final R factor is 0. 066. The result reveals that the [Mo4S4] cluster core and t-(dtp)1ligands are retained and onlyμ-bridged (dtp)1- ligands are substituted by (C6H5CO2)1in the substitution reaction, thus producing the title cluster compound,the structure of which contains two species of bidentate ligand.展开更多
Noncohesive particle clusters are identified and tracked in turbulent flows to determine the breakdown and time evolution of cluster statistics and their implications for interscale mass transfer,which has connections...Noncohesive particle clusters are identified and tracked in turbulent flows to determine the breakdown and time evolution of cluster statistics and their implications for interscale mass transfer,which has connections to the classical turbulent energy cascade and its mass cascade counterpart running in parallel.In particular,the formation and dynamics of sediment and larvae clusters are of interest to coral larvae settlement in coastal regions and particularly the resilience of green-gray coastal protection solutions.Analogous cluster behavior is relevant to cloud microphysics and precipitation initiation,radiation transport and light transmission through colloids and suspensions,heat and mass transfer in particle-laden flows,and viral and pollutant transmission.Following a comparison between various clustering techniques,we adopt a density-based cluster identification algorithm based on its simplicity and efficiency,where particles are clustered based on the number of neighboring particles in their individual spheres of influence.We establish parallels with lattice-based percolation theory,as evident in the power-law scaling of the cluster size distribution near the percolation threshold.The degree of discontinuity of the phase transition associated with this percolation threshold is observed to broaden with larger Stokes numbers and thereby large-scale clustering.The sensitivity of our findings to the employed clustering algorithm is discussed.A novel cluster tracking algorithm is deployed to determine the interscale transfer rate along the particle-number phase-space dimension via accounting of cluster breakup and merger events,extending previous work on the bubble breakup cascade beneath surface breaking waves.Our findings shed light on the interaction between particle clusters and their carrier turbulent flows,with an eye toward transport models incorporating cluster characteristics and dynamics.展开更多
Under hydrothermal and solvothermal conditions,two novel cobalt-based complexes,{[Co_(2)(CIA)(OH)(1,4-dtb)]·3.2H_(2)O}n(HU23)and{[Co_(2)(CIA)(OH)(1,4-dib)]·3.5H2O·DMF}n(HU24),were successfully construct...Under hydrothermal and solvothermal conditions,two novel cobalt-based complexes,{[Co_(2)(CIA)(OH)(1,4-dtb)]·3.2H_(2)O}n(HU23)and{[Co_(2)(CIA)(OH)(1,4-dib)]·3.5H2O·DMF}n(HU24),were successfully constructed by coordinatively assembling the semi-rigid multidentate ligand 5-(1-carboxyethoxy)isophthalic acid(H₃CIA)with the Nheterocyclic ligands 1,4-di(4H-1,2,4-triazol-4-yl)benzene(1,4-dtb)and 1,4-di(1H-imidazol-1-yl)benzene(1,4-dib),respectively,around Co^(2+)ions.Single-crystal X-ray diffraction analysis revealed that in both complexes HU23 and HU24,the CIA^(3-)anions adopt aκ^(7)-coordination mode,bridging six Co^(2+)ions via their five carboxylate oxygen atoms and one ether oxygen atom.This linkage forms tetranuclear[Co4(μ3-OH)2]^(6+)units.These Co-oxo cluster units were interconnected by CIA^(3-)anions to assemble into 2D kgd-type structures featuring a 3,6-connected topology.The 2D layers were further connected by 1,4-dtb and 1,4-dib,resulting in 3D pillar-layered frameworks for HU23 and HU24.Notably,despite the similar configurations of 1,4-dtb and 1,4-dib,differences in their coordination spatial orientations lead to topological divergence in the 3D frameworks of HU23 and HU24.Topological analysis indicates that the frameworks of HU23 and HU24 can be simplified into a 3,10-connected net(point symbol:(4^(10).6^(3).8^(2))(4^(3))_(2))and a 3,8-connected tfz-d net(point symbol:(4^(3))_(2)((4^(6).6^(18).8^(4)))),respectively.This structural differentiation confirms the precise regulatory role of ligands on the topology of metal-organic frameworks.Moreover,the ultraviolet-visible absorption spectra confirmed that HU23 and HU24 have strong absorption capabilities for ultraviolet and visible light.According to the Kubelka-Munk method,their bandwidths were 2.15 and 2.08 eV,respectively,which are consistent with those of typical semiconductor materials.Variable-temperature magnetic susceptibility measurements(2-300 K)revealed significant antiferromagnetic coupling in both complexes,with their effective magnetic moments decreasing markedly as the temperature lowered.CCDC:2457554,HU23;2457553,HU24.展开更多
As large-scale astronomical surveys,such as the Sloan Digital Sky Survey(SDSS)and the Large Sky Area Multi-Object Fiber Spectroscopic Telescope(LAMOST),generate increasingly complex datasets,clustering algorithms have...As large-scale astronomical surveys,such as the Sloan Digital Sky Survey(SDSS)and the Large Sky Area Multi-Object Fiber Spectroscopic Telescope(LAMOST),generate increasingly complex datasets,clustering algorithms have become vital for identifying patterns and classifying celestial objects.This paper systematically investigates the application of five main categories of clustering techniques-partition-based,density-based,model-based,hierarchical,and“others”-across a range of astronomical research over the past decade.This review focuses on the six key application areas of stellar classification,galaxy structure analysis,detection of galactic and interstellar features,highenergy astrophysics,exoplanet studies,and anomaly detection.This paper provides an in-depth analysis of the performance and results of each method,considering their respective suitabilities for different data types.Additionally,it presents clustering algorithm selection strategies based on the characteristics of the spectroscopic data being analyzed.We highlight challenges such as handling large datasets,the need for more efficient computational tools,and the lack of labeled data.We also underscore the potential of unsupervised and semi-supervised clustering approaches to overcome these challenges,offering insight into their practical applications,performance,and results in astronomical research.展开更多
Nanozymes,a promising class of enzyme mimics based on nanostructures,have attracted considerable research interest.However,in sharp contrast to the structural precision of natural enzymes,most nanozymes are poorly def...Nanozymes,a promising class of enzyme mimics based on nanostructures,have attracted considerable research interest.However,in sharp contrast to the structural precision of natural enzymes,most nanozymes are poorly defined structurally.The absence of nanozyme systems that mimic natural isoenzymes-which catalyze similar reactions despite slight differences in their chemical structures-has particularly hindered the understanding of their structure-performance relationships.Such nanozyme analogues,termed iso-nanozymes,remain largely unexplored.Here,we report the first pair of iso-nanozymes.Two analogous copper nanoclusters-[Cu_(32)(SC_(2)H_(5))_(16)(PPh_(3))_(8)Cl_(9)]^(+) (Cu_(32))and[Cu_(30)(SC_(2)H_(5))_(16)(PPh_(3))_(6)Cl_(9)]^(+) (Cu_(30))-were synthesized and structurally characterized.Single-crystal X-ray diffraction analysis reveals that Cu_(30) possesses an identical metal framework and ligand types as Cu_(32),with a comparable ligand distribution.The only structural difference is the absence of two PPh_(3)Cu^(+) units in Cu_(30),which results in a substantial enhancement of its catalytic performance in the horseradish peroxidase-mimicking reaction.Under identical conditions,the specific activity(SA)of the Cu_(30) nanozyme is approximately 6.5 times higher than that of Cu_(32).Density functional theory calculations indicate that the notable difference in the SA between the two cluster nanozymes is attributed to variations in adsorption energies,which stem from their different geometric and electronic structures.This study not only introduces the novel concept of iso-nanozymes using atomically precise metal nanoclusters,but also establishes a model system for investigating the critical influence of nanozyme structure,down to the atomic level,on catalytic efficiency.These findings are anticipated to inspire further research interest in atomically precise metal nanoclusters within the nanozyme community.展开更多
Bottom-up and top-down endogenous automobile clusters exhibit distinct evolutionary traits and driving mechanisms,yet their comparative analysis remains understudied.Therefore,using Taizhou automobile industry cluster...Bottom-up and top-down endogenous automobile clusters exhibit distinct evolutionary traits and driving mechanisms,yet their comparative analysis remains understudied.Therefore,using Taizhou automobile industry cluster(TAIC)and Wuhu automobile industry cluster(WAIC)as cases,using historical statistical data and field interview data from the 1980s to 2023,combined with qualitative research methods of thematic and diachronic analysis,and quantitative research methods of social network analysis,we compare both endogenous automobile clusters’evolutionary traits and driving mechanisms.The results confirm both clusters undergo multi-scale spatial reconfiguration,organizational complexification,and intelligent networking technological transformation,yet diverge fundamentally:TAIC evolves through market-driven progressive expansion,transitioning from single to dual-core structures via private enterprise networking,with innovation following market-integrated logic and institutional thickness built on demand-driven evolution.Conversely,WAIC follows planned expansion,maintaining state-led hierarchical single-core stability through policy-driven breakthrough innovation and supply-dominated institutional construction-though both ultimately require formal-informal system synergy.Their coevolution is driven by dynamic interactions of path dependence(weakening influence),learning-innovation(strengthening influence),and relationship selection(inverted U-shaped trajectory),with divergent development paths rooted in TAIC’s grassroots self-organization genes versus WAIC’s top-level design genes,amplified by core enterprises’strategic disparities.The research findings can not only provide decision-making support for China’s industrial upgrading,but also contribute China’s insights to global economic governance.展开更多
Villager Pan Chunlin is witnessing a boom in his homestay business.More and more visitors are coming to his village,Yucun Village in Anji County,Huzhou City,Zhejiang Province.
In the Tianshan region,a complete textile industry chain has been established,covering the entire process from cotton cultivation and chemical fiber production,through spinning,weaving,dyeing,and finishing,and further...In the Tianshan region,a complete textile industry chain has been established,covering the entire process from cotton cultivation and chemical fiber production,through spinning,weaving,dyeing,and finishing,and further extending to apparel,home textiles,and industrial textiles.In November 2025,the first list of five characteristic textile and apparel industry clusters in Xinjiang was officially announced,marking a new stage in the clustering of Xinjiang's textile and apparel industry.Data shows that the total output value of Xinjiang's cotton and textile and apparel industry chain has exceeded 220 billion yuan.With the nation's largest cotton production,a complete industrial chain system,and strong synergistic effects,Xinjiang has become a leading and highly competitive textile industry hub in China.展开更多
A Cu-1.9Ni-1.9Co-0.9Si(mass fraction,%)alloy with high strength and electrical conductivity was designed by cluster formula approach.The microstructure evolution of the alloy during thermomechanical treatment was syst...A Cu-1.9Ni-1.9Co-0.9Si(mass fraction,%)alloy with high strength and electrical conductivity was designed by cluster formula approach.The microstructure evolution of the alloy during thermomechanical treatment was systematically investigated.The strengthening mechanism and electrical conductivity of the alloy were discussed in detail.The optimal thermomechanical treatment process was as follows:solid solution→80%cold rolling→(450℃,4 h)aging→50%cold rolling→(400℃,4 h)aging.The designed alloy achieved excellent comprehensive properties with a microhardness of HV 260,a yield strength of 843 MPa,a tensile strength of 884 MPa,and an electrical conductivity of 42.6%(IACS).Compared to direct aging treatment,the designed alloy subjected to multi-stage thermomechanical treatment had refined grains,high density of dislocations,and accelerated of precipitation of(Ni,Co)_(2)Si precipitates.High strength was mainly attributed to the combined effect of dislocation strengthening,work hardening and sub-grain strengthening,while good electrical conductivity was maintained through the precipitation of the large number of nanoparticles.展开更多
Developing advanced polymeric materials with enhanced mechanical properties and functionalities has been a long-standing goal in materials science.Recently,supramolecular polymeric materials (SPMs) have drawn increase...Developing advanced polymeric materials with enhanced mechanical properties and functionalities has been a long-standing goal in materials science.Recently,supramolecular polymeric materials (SPMs) have drawn increased attention due to their unique properties and potential applications in self-healing,shape memory,sensors,and flexible electronics.Here,we develop an ionic cluster-optimized microphase separation strategy to enhance the toughening and energy dissipation capabilities of polydisulfide-based supramolecular polymers.The mechanical properties,including Young’s modulus and toughness,are significantly improved by integrating the quadruple H-bonding 2-ureido-4-pyrimidone (UPy) induced microphase separation with iron(Ⅲ)-to-carboxylate ionic clusters.By combining established chemical approaches with adjustable polymer phase ratios,it is revealed that the synergistic effect of these factors expands the interchain spacing,facilitates the formation of microphase domains,and enhances the tolerance of polythioctic acid-based polymers to external mechanical and thermal stimuli,meeting the practical requirements for industrial plastic applications.Moreover,the UPy-functionalized polymers incorporating iron carboxylate clusters exhibit good one-way shape memory behavior with practical applicability at a relatively low recovery temperature.Our work demonstrates a novel strategy for constructing industrially viable shape memory dynamic SPMs and paves the way for future innovations in developing SPMs.展开更多
With the rapid development of the aviation industry,air travel has become one of the most important modes.Improving the service quality of civil aviation airports is crucial to their competitiveness.This study intends...With the rapid development of the aviation industry,air travel has become one of the most important modes.Improving the service quality of civil aviation airports is crucial to their competitiveness.This study intends to develop a scientific and rational evaluation methodology and framework for assessing service quality in civil aviation airports,thereby providing a theoretical foundation and practical guidance for enhancing service standards in the aviation industry.First,the study constructs a CRITIC-bidirectional grey possibility clustering model,which uses the CRITIC method to determine the weights of indicators and integrates the forward grey possibility clustering model and the inverse grey possibility clustering model to determine possibility functions from two perspectives.Second,a service quality evaluation index system for civil airports is constructed from four dimensions,and the weights of each index within the system are subsequently calculated.Finally,the constructed model is applied to evaluate the service quality of nine domestic civil airports.Based on the clustering results,targeted countermeasures and suggestions are proposed.Empirical results demonstrate that,compared to the traditional grey possibility clustering model,the proposed model balances the objectivity of indicator weighting,the objectivity of possibility function construction,and the simplicity of the computational process,thereby possessing significant theoretical and practical implications.展开更多
In this study,the effects of laser fields that can be achieved in the near future on cluster penetration probability and half-life are quantitatively investigated.The calculation results show that extreme laser fields...In this study,the effects of laser fields that can be achieved in the near future on cluster penetration probability and half-life are quantitatively investigated.The calculation results show that extreme laser fields can slightly change the cluster-decay half-life by affecting the penetration probability within a narrow range.Subsequently,we discuss the correlation between the change rate of the penetration probability and the tunneling path.The results indicate that for different parent nuclei emitting the same cluster,nuclei with longer tunneling paths are more easily affected by the laser fields.The shell effect on this correlation is also observed.In addition,the impact of laser fields on the penetration probability in any direction is investigated.展开更多
This study addresses the persistent scarcity of systematic and comparable data on mountain tourism,with particular reference to Northern Italy,as highlighted by FAO/UNWTO reports and recent academic literature.It aims...This study addresses the persistent scarcity of systematic and comparable data on mountain tourism,with particular reference to Northern Italy,as highlighted by FAO/UNWTO reports and recent academic literature.It aims to contribute to this gap by analyzing tourist flows,socio-demographic characteristics,preferences,and behaviors of domestic visitors to the Italian Alps.Data were collected through a survey conducted between December 2023 and January 2024 among 1,218 residents of Northwest and Northeast Italy and Friuli Venezia Giulia,using a stratified sampling approach.Descriptive statistics and inferential analyses were employed to examine visitation patterns,while K-means clustering was applied to identify distinct segments of mountain tourists based on activity preferences and motivations.Overall,82.5%of respondents reported visiting Alpine areas.Chi-square tests revealed statistically significant differences in visitation behavior according to age,occupational status,and income.Notably,spiritual activities,such as pilgrimages,elicited levels of interest comparable to those of more traditional mountain sports.The cluster analysis identified three visitor profiles:Active Young Enthusiasts,characterized by high engagement in multiple outdoor activities and motivated by psychological well-being and cultural enrichment;Well-being-Oriented Walkers,preferring low-intensity activities primarily driven by psychological relaxation;and Hiking-Oriented Explorers,exhibiting a strong propensity for mountain excursions associated with high levels of psychophysical well-being.These findings enhance understanding of the heterogeneous structure of mountain tourism demand in Northern Italy and offer insights relevant to sustainable destination planning and management in Alpine regions.展开更多
This paper aims to develop a unified Bayesian approach for clustered data analysis when observations are subject to missingness at random.The authors consider a general framework in which the parameters of interest ar...This paper aims to develop a unified Bayesian approach for clustered data analysis when observations are subject to missingness at random.The authors consider a general framework in which the parameters of interest are defined through estimating equations,and the probability of missingness follows a general parametric form.The generalized method of moments framework is employed to derive an optimal combination of inverse-probability-weighted estimating equations for the parameters of interest and score equations for propensity score.Using this framework,the authors develop a quasi-Bayesian analysis for clustered samples with missing values.A unified model selection approach is also proposed to compare models characterized by different moment conditions.The authors systematically evaluate the large-sample properties of the proposed quasi-posterior density with both fixed and shrinking priors and establish the selection consistency of the proposed model selection criterion.The proposed results are valid under very mild conditions and offer significant advantages for parameters defined through non-smooth estimating functions.Extensive numerical studies demonstrate that the proposed method performs exceptionally well in finite samples.展开更多
Exploring high-performance electrocatalysts for the nitrate reduction reaction(NO_(3)RR)is crucial for environmental nitrate removal and ammonia synthesis.Single-atom collaboration with cluster can provide sufficient ...Exploring high-performance electrocatalysts for the nitrate reduction reaction(NO_(3)RR)is crucial for environmental nitrate removal and ammonia synthesis.Single-atom collaboration with cluster can provide sufficient active sites for catalysts to promote NO_(3)RR,yet the unclear synergistic effect between the two hinders their rational design.Herein,a series of Ir_(3)clusters and metal single atoms co-embedded in graphitic carbon nitride(g-CN)catalysts(Ir_(3)M1)were constructed,and the synergistic effects of Ir_(3)clusters and M1 single atoms on the NO_(3)RR catalytic mechanism and activity were systematically explored using density functional theory(DFT)calculations combined with machine learning.Comprehensive evaluations of structural stability and catalytic activity demonstrate that the synergy between single atoms and clusters effectively balances the adsorption energies of key intermediates,yielding exceptional catalytic performance(the limiting potential of Ir_(3)Ti_(1)can reach−0.22 V).Machine learning models further clarify the synergistic mechanism,where the geometric configurations of clusters serve as critical features for modulating the catalytic activity of single-atom sites,whereas the electronic structures of single atoms directly govern the reactivity of cluster sites.This DFT-machine learning approach provides theoretical guidelines for catalyst design and a predictive framework for efficient NO_(3)RR electrocatalysts.展开更多
Multichannel signals have the characteristics of information diversity and information consistency.To better explore and utilize the affinity relationship within multichannel signals,a new graph learning technique bas...Multichannel signals have the characteristics of information diversity and information consistency.To better explore and utilize the affinity relationship within multichannel signals,a new graph learning technique based on low rank tensor approximation is proposed for multichannel monitoring signal processing and utilization.Firstly,the affinity relationship of multichannel signals can be acquired based on the clustering results of each channel signal.Wherein an affinity tensor is constructed to integrate the diverse and consistent information of the clustering information among multichannel signals.Secondly,a low-rank tensor optimization model is built and the joint affinity matrix is optimized with the assistance of the strong confidence affinity matrix.Through solving the optimization model,the fused affinity relationship graph of multichannel signals can be obtained.Finally,the multichannel fused clustering results can be acquired though the updated joint affinity relationship graph.The multichannel signal utilization examples in health state assessment with public datasets and microwave detection with actual echoes verify the advantages and effectiveness of the proposed method.展开更多
With the popularization of smart devices,Location-Based Services(LBS)greatly facilitates users’life,but at the same time brings the risk of users’location privacy leakage.Existing location privacy protection methods...With the popularization of smart devices,Location-Based Services(LBS)greatly facilitates users’life,but at the same time brings the risk of users’location privacy leakage.Existing location privacy protection methods are deficient,failing to reasonably allocate the privacy budget for non-outlier location points and ignoring the critical location information that may be contained in the outlier points,leading to decreased data availability and privacy exposure problems.To address these problems,this paper proposes a Mix Location Privacy Preservation Method Based on Differential Privacy with Clustering(MLDP).The method first utilizes the DBSCAN clustering algorithm to classify location points into non-outliers and outliers.For non-outliers,the scoring function is designed by combining geographic information and semantic information,and the privacy budget is allocated according to the heat intensity of the hotspot area;for outliers,the scoring function is constructed to allocate the privacy budget based on their correlation with the hotspot area.By comprehensively considering the geographic information,semantic information,and correlation with hotspot areas of the location points,a reasonable privacy budget is assigned to each location point,andfinallynoise is added throughthe Laplacemechanismto realizeprivacyprotection.Experimental results on tworeal trajectory datasets,Geolife and T-Drive,show that the MLDP approach significantly improves data availability while effectively protecting location privacy.Compared with the comparison methods,the maximum available data ratio of MLDP is 1.Moreover,compared with the RandomNoise method,its execution time is 0.056–0.061 s longer,and the logRE is 0.12951–0.62194 lower;compared with KemeansDP,QTK-DP,DPK-F,IDP-SC,and DPK-Means-up methods,it saves 0.114–0.296 s in execution time,and the logRE is 0.01112–0.38283 lower.展开更多
By encouraging collaboration,attracting young entrepreneurs,and setting up village-invested enterprises,rural communities in Zhejiang Province are growing their income streams.“Over the past years,we have seen more a...By encouraging collaboration,attracting young entrepreneurs,and setting up village-invested enterprises,rural communities in Zhejiang Province are growing their income streams.“Over the past years,we have seen more and more tourists coming to our village,and their stay here has grown longer.Many even said they don’t want to leave,”Pan Chunlin,a resident of Yucun Village in Anji County of Huzhou City,east China’s Zhejiang Province,told China Today.Pan is the owner of the Chunlin Lodge,a bed&breakfast(B&B)which received more than 70,000 visitors last year,generating over RMB 4 million in revenue.展开更多
This paper introduces a fuzzy C-means-based pooling layer for convolutional neural networks that explicitly models local uncertainty and ambiguity.Conventional pooling operations,such as max and average,apply rigid ag...This paper introduces a fuzzy C-means-based pooling layer for convolutional neural networks that explicitly models local uncertainty and ambiguity.Conventional pooling operations,such as max and average,apply rigid aggregation and often discard fine-grained boundary information.In contrast,our method computes soft membershipswithin each receptive field and aggregates cluster-wise responses throughmembership-weighted pooling,thereby preserving informative structure while reducing dimensionality.Being differentiable,the proposed layer operates as standard two-dimensional pooling.We evaluate our approach across various CNN backbones and open datasets,including CIFAR-10/100,STL-10,LFW,and ImageNette,and further probe small training set restrictions on MNIST and Fashion-MNIST.In these settings,the proposed pooling consistently improves accuracy and weighted F1 over conventional baselines,with particularly strong gains when training data are scarce.Even with less than 1%of the training set,ourmethodmaintains reliable performance,indicating improved sample efficiency and robustness to noisy or ambiguous local patterns.Overall,integrating soft memberships into the pooling operator provides a practical and generalizable inductive bias that enhances robustness and generalization in modern CNN pipelines.展开更多
The shift toward specialized and large-scale agricultural production has spurred the emergence of agricultural clusters as key forces of rural vitalization and sustainable development.This paper explored the formation...The shift toward specialized and large-scale agricultural production has spurred the emergence of agricultural clusters as key forces of rural vitalization and sustainable development.This paper explored the formation and evolution of Meizhou pomelo industry cluster in China,focusing on its role in restructuring rural socio-economic systems and integrating the whole value chains.Based on a case study employing qualitative methods such as in-depth interviews and participatory observation,the agricultural cluster evolution of Meizhou pomelo was categorized into three key phases of initial decentralization,self-organized scaling,and reorganized clustering.Geographical proximity and industrial agglomeration constitute the physical foundation,while vertical/horizontal linkages,technologic-al innovation,and policy support enhance competitiveness.Special mechanisms emerge through localized social networks,farmer co-operatives’activation,and cross-regional market expansion.The cluster’s impact is manifested in the shift from extensive to standard-ized and modernized production,diversified and flexible livelihood of farmers,and the integration of agriculture with industry and ser-vices.The development of the whole value chain based on agricultural cluster represents a critical pathway for achieving agricultural modernization,encompassing both internal and external value chain optimization.Through quality assurance systems,product diversi-fication strategies,operational efficiency improvements,and brand enhancement,these clusters amplify product value propositions and market competitiveness.This systemic approach facilitates supply-demand coordination,enables resource synergies,and optimizes eco-nomic returns across the horizontal and vertical value chain.This paper argues that agricultural clusters serve as strategic catalysts for sustainable rural development by reconstructing local production systems,fostering innovation ecosystems,and aligning agricultural modernization.It contributes to debates on rural vitalization by demonstrating how agricultural clustering can reconfigure rural areas as hubs of ecological modernization,rather than mere urban peripheries.展开更多
文摘The cluster compound [Mo4S4 (μ-O2CC6H5)2(dtp)4] (dtp = S2P (OEt)2)was obtained by the ligand substitution reaction of tetranuclear molybdenum cluster [Mo4S4(μ-dtp)2(dtp)4] in the mixed solvent of acetone, ethanol and water in the presence of C6H5CO2Na. It is monoclinic and crystallizesin space group C2/c, Mr =1495. 09, a=12. 175 (5) , b=22. 01 (1) , c=20.875(9) ,β=99. 04(4)°; V=5570(5) ; Z=4; Dc= 1. 78g/cm3;μ(MoKα) = 14. 52 cm-1; F(000) =2984. Final R factor is 0. 066. The result reveals that the [Mo4S4] cluster core and t-(dtp)1ligands are retained and onlyμ-bridged (dtp)1- ligands are substituted by (C6H5CO2)1in the substitution reaction, thus producing the title cluster compound,the structure of which contains two species of bidentate ligand.
文摘Noncohesive particle clusters are identified and tracked in turbulent flows to determine the breakdown and time evolution of cluster statistics and their implications for interscale mass transfer,which has connections to the classical turbulent energy cascade and its mass cascade counterpart running in parallel.In particular,the formation and dynamics of sediment and larvae clusters are of interest to coral larvae settlement in coastal regions and particularly the resilience of green-gray coastal protection solutions.Analogous cluster behavior is relevant to cloud microphysics and precipitation initiation,radiation transport and light transmission through colloids and suspensions,heat and mass transfer in particle-laden flows,and viral and pollutant transmission.Following a comparison between various clustering techniques,we adopt a density-based cluster identification algorithm based on its simplicity and efficiency,where particles are clustered based on the number of neighboring particles in their individual spheres of influence.We establish parallels with lattice-based percolation theory,as evident in the power-law scaling of the cluster size distribution near the percolation threshold.The degree of discontinuity of the phase transition associated with this percolation threshold is observed to broaden with larger Stokes numbers and thereby large-scale clustering.The sensitivity of our findings to the employed clustering algorithm is discussed.A novel cluster tracking algorithm is deployed to determine the interscale transfer rate along the particle-number phase-space dimension via accounting of cluster breakup and merger events,extending previous work on the bubble breakup cascade beneath surface breaking waves.Our findings shed light on the interaction between particle clusters and their carrier turbulent flows,with an eye toward transport models incorporating cluster characteristics and dynamics.
文摘Under hydrothermal and solvothermal conditions,two novel cobalt-based complexes,{[Co_(2)(CIA)(OH)(1,4-dtb)]·3.2H_(2)O}n(HU23)and{[Co_(2)(CIA)(OH)(1,4-dib)]·3.5H2O·DMF}n(HU24),were successfully constructed by coordinatively assembling the semi-rigid multidentate ligand 5-(1-carboxyethoxy)isophthalic acid(H₃CIA)with the Nheterocyclic ligands 1,4-di(4H-1,2,4-triazol-4-yl)benzene(1,4-dtb)and 1,4-di(1H-imidazol-1-yl)benzene(1,4-dib),respectively,around Co^(2+)ions.Single-crystal X-ray diffraction analysis revealed that in both complexes HU23 and HU24,the CIA^(3-)anions adopt aκ^(7)-coordination mode,bridging six Co^(2+)ions via their five carboxylate oxygen atoms and one ether oxygen atom.This linkage forms tetranuclear[Co4(μ3-OH)2]^(6+)units.These Co-oxo cluster units were interconnected by CIA^(3-)anions to assemble into 2D kgd-type structures featuring a 3,6-connected topology.The 2D layers were further connected by 1,4-dtb and 1,4-dib,resulting in 3D pillar-layered frameworks for HU23 and HU24.Notably,despite the similar configurations of 1,4-dtb and 1,4-dib,differences in their coordination spatial orientations lead to topological divergence in the 3D frameworks of HU23 and HU24.Topological analysis indicates that the frameworks of HU23 and HU24 can be simplified into a 3,10-connected net(point symbol:(4^(10).6^(3).8^(2))(4^(3))_(2))and a 3,8-connected tfz-d net(point symbol:(4^(3))_(2)((4^(6).6^(18).8^(4)))),respectively.This structural differentiation confirms the precise regulatory role of ligands on the topology of metal-organic frameworks.Moreover,the ultraviolet-visible absorption spectra confirmed that HU23 and HU24 have strong absorption capabilities for ultraviolet and visible light.According to the Kubelka-Munk method,their bandwidths were 2.15 and 2.08 eV,respectively,which are consistent with those of typical semiconductor materials.Variable-temperature magnetic susceptibility measurements(2-300 K)revealed significant antiferromagnetic coupling in both complexes,with their effective magnetic moments decreasing markedly as the temperature lowered.CCDC:2457554,HU23;2457553,HU24.
基金supported by the National Natural Science Foundation of China (12473105 and 12473106)the central government guides local funds for science and technology development (YDZJSX2024D049)the Graduate Student Practice and Innovation Program of Shanxi Province (2024SJ313)
文摘As large-scale astronomical surveys,such as the Sloan Digital Sky Survey(SDSS)and the Large Sky Area Multi-Object Fiber Spectroscopic Telescope(LAMOST),generate increasingly complex datasets,clustering algorithms have become vital for identifying patterns and classifying celestial objects.This paper systematically investigates the application of five main categories of clustering techniques-partition-based,density-based,model-based,hierarchical,and“others”-across a range of astronomical research over the past decade.This review focuses on the six key application areas of stellar classification,galaxy structure analysis,detection of galactic and interstellar features,highenergy astrophysics,exoplanet studies,and anomaly detection.This paper provides an in-depth analysis of the performance and results of each method,considering their respective suitabilities for different data types.Additionally,it presents clustering algorithm selection strategies based on the characteristics of the spectroscopic data being analyzed.We highlight challenges such as handling large datasets,the need for more efficient computational tools,and the lack of labeled data.We also underscore the potential of unsupervised and semi-supervised clustering approaches to overcome these challenges,offering insight into their practical applications,performance,and results in astronomical research.
基金support from the National Key R&D Program of China(2023YFB3507100)National Natural Science Foundation of China(22301149 and 22571172)+9 种基金Natural Science Foundation of Inner Mongolia(2025JQ026)Program for Young Talents of Science and Technology in Universities of Inner Mongolia Autonomous Region(NJYT23035)Start-Up Funding of Inner Mongolia University(10000-23112101/043 and 23600-5233710)S.Li acknowledges the financial support from the National Natural Science Foundation of China(22565021)Natural Science Foundation of Inner Mongolia(2025QN02068)Start-Up Funding of Inner Mongolia University(10000-A24202027)N.F.Zheng acknowledges the financial support from the National Natural Science Foundation of China(Grant Number:92261207)NSFC Center for Single-Atom Catalysis under Grant Number 22388102)the New Cornerstone Science Foundation.We acknowledge the financial support from JST-ERATO Yamauchi Materials Space-Tectonics Project(JPMJER2003)ARC Australian Laureate Fellowship(FL230100095).
文摘Nanozymes,a promising class of enzyme mimics based on nanostructures,have attracted considerable research interest.However,in sharp contrast to the structural precision of natural enzymes,most nanozymes are poorly defined structurally.The absence of nanozyme systems that mimic natural isoenzymes-which catalyze similar reactions despite slight differences in their chemical structures-has particularly hindered the understanding of their structure-performance relationships.Such nanozyme analogues,termed iso-nanozymes,remain largely unexplored.Here,we report the first pair of iso-nanozymes.Two analogous copper nanoclusters-[Cu_(32)(SC_(2)H_(5))_(16)(PPh_(3))_(8)Cl_(9)]^(+) (Cu_(32))and[Cu_(30)(SC_(2)H_(5))_(16)(PPh_(3))_(6)Cl_(9)]^(+) (Cu_(30))-were synthesized and structurally characterized.Single-crystal X-ray diffraction analysis reveals that Cu_(30) possesses an identical metal framework and ligand types as Cu_(32),with a comparable ligand distribution.The only structural difference is the absence of two PPh_(3)Cu^(+) units in Cu_(30),which results in a substantial enhancement of its catalytic performance in the horseradish peroxidase-mimicking reaction.Under identical conditions,the specific activity(SA)of the Cu_(30) nanozyme is approximately 6.5 times higher than that of Cu_(32).Density functional theory calculations indicate that the notable difference in the SA between the two cluster nanozymes is attributed to variations in adsorption energies,which stem from their different geometric and electronic structures.This study not only introduces the novel concept of iso-nanozymes using atomically precise metal nanoclusters,but also establishes a model system for investigating the critical influence of nanozyme structure,down to the atomic level,on catalytic efficiency.These findings are anticipated to inspire further research interest in atomically precise metal nanoclusters within the nanozyme community.
基金Under the auspices of National Natural Science Foundation of China(No.42571219)Key Project of Zhejiang Province Soft Science Research Plan(No.2023C25014)。
文摘Bottom-up and top-down endogenous automobile clusters exhibit distinct evolutionary traits and driving mechanisms,yet their comparative analysis remains understudied.Therefore,using Taizhou automobile industry cluster(TAIC)and Wuhu automobile industry cluster(WAIC)as cases,using historical statistical data and field interview data from the 1980s to 2023,combined with qualitative research methods of thematic and diachronic analysis,and quantitative research methods of social network analysis,we compare both endogenous automobile clusters’evolutionary traits and driving mechanisms.The results confirm both clusters undergo multi-scale spatial reconfiguration,organizational complexification,and intelligent networking technological transformation,yet diverge fundamentally:TAIC evolves through market-driven progressive expansion,transitioning from single to dual-core structures via private enterprise networking,with innovation following market-integrated logic and institutional thickness built on demand-driven evolution.Conversely,WAIC follows planned expansion,maintaining state-led hierarchical single-core stability through policy-driven breakthrough innovation and supply-dominated institutional construction-though both ultimately require formal-informal system synergy.Their coevolution is driven by dynamic interactions of path dependence(weakening influence),learning-innovation(strengthening influence),and relationship selection(inverted U-shaped trajectory),with divergent development paths rooted in TAIC’s grassroots self-organization genes versus WAIC’s top-level design genes,amplified by core enterprises’strategic disparities.The research findings can not only provide decision-making support for China’s industrial upgrading,but also contribute China’s insights to global economic governance.
文摘Villager Pan Chunlin is witnessing a boom in his homestay business.More and more visitors are coming to his village,Yucun Village in Anji County,Huzhou City,Zhejiang Province.
文摘In the Tianshan region,a complete textile industry chain has been established,covering the entire process from cotton cultivation and chemical fiber production,through spinning,weaving,dyeing,and finishing,and further extending to apparel,home textiles,and industrial textiles.In November 2025,the first list of five characteristic textile and apparel industry clusters in Xinjiang was officially announced,marking a new stage in the clustering of Xinjiang's textile and apparel industry.Data shows that the total output value of Xinjiang's cotton and textile and apparel industry chain has exceeded 220 billion yuan.With the nation's largest cotton production,a complete industrial chain system,and strong synergistic effects,Xinjiang has become a leading and highly competitive textile industry hub in China.
基金the financial support by the National Natural Science Foundation of China(No.U2202255)the Hunan Provincial Natural Science Foundation of China(No.2024JJ2076)the Key Research and Development Program of Ningbo,China(No.2023Z092)。
文摘A Cu-1.9Ni-1.9Co-0.9Si(mass fraction,%)alloy with high strength and electrical conductivity was designed by cluster formula approach.The microstructure evolution of the alloy during thermomechanical treatment was systematically investigated.The strengthening mechanism and electrical conductivity of the alloy were discussed in detail.The optimal thermomechanical treatment process was as follows:solid solution→80%cold rolling→(450℃,4 h)aging→50%cold rolling→(400℃,4 h)aging.The designed alloy achieved excellent comprehensive properties with a microhardness of HV 260,a yield strength of 843 MPa,a tensile strength of 884 MPa,and an electrical conductivity of 42.6%(IACS).Compared to direct aging treatment,the designed alloy subjected to multi-stage thermomechanical treatment had refined grains,high density of dislocations,and accelerated of precipitation of(Ni,Co)_(2)Si precipitates.High strength was mainly attributed to the combined effect of dislocation strengthening,work hardening and sub-grain strengthening,while good electrical conductivity was maintained through the precipitation of the large number of nanoparticles.
基金supported by the National Natural Science Foundation of China(No.22375063)Science and Technology Commission of Shanghai Municipality(No.23JC1401700)the Fundamental Research Funds for the Central Universities.
文摘Developing advanced polymeric materials with enhanced mechanical properties and functionalities has been a long-standing goal in materials science.Recently,supramolecular polymeric materials (SPMs) have drawn increased attention due to their unique properties and potential applications in self-healing,shape memory,sensors,and flexible electronics.Here,we develop an ionic cluster-optimized microphase separation strategy to enhance the toughening and energy dissipation capabilities of polydisulfide-based supramolecular polymers.The mechanical properties,including Young’s modulus and toughness,are significantly improved by integrating the quadruple H-bonding 2-ureido-4-pyrimidone (UPy) induced microphase separation with iron(Ⅲ)-to-carboxylate ionic clusters.By combining established chemical approaches with adjustable polymer phase ratios,it is revealed that the synergistic effect of these factors expands the interchain spacing,facilitates the formation of microphase domains,and enhances the tolerance of polythioctic acid-based polymers to external mechanical and thermal stimuli,meeting the practical requirements for industrial plastic applications.Moreover,the UPy-functionalized polymers incorporating iron carboxylate clusters exhibit good one-way shape memory behavior with practical applicability at a relatively low recovery temperature.Our work demonstrates a novel strategy for constructing industrially viable shape memory dynamic SPMs and paves the way for future innovations in developing SPMs.
基金support supplied by the National Natural Science Foundation of China(Nos.72571136,72271120)the Ministry of Education of the People’s Republic of China Humanities and Social Science project(No.24YJA630087)。
文摘With the rapid development of the aviation industry,air travel has become one of the most important modes.Improving the service quality of civil aviation airports is crucial to their competitiveness.This study intends to develop a scientific and rational evaluation methodology and framework for assessing service quality in civil aviation airports,thereby providing a theoretical foundation and practical guidance for enhancing service standards in the aviation industry.First,the study constructs a CRITIC-bidirectional grey possibility clustering model,which uses the CRITIC method to determine the weights of indicators and integrates the forward grey possibility clustering model and the inverse grey possibility clustering model to determine possibility functions from two perspectives.Second,a service quality evaluation index system for civil airports is constructed from four dimensions,and the weights of each index within the system are subsequently calculated.Finally,the constructed model is applied to evaluate the service quality of nine domestic civil airports.Based on the clustering results,targeted countermeasures and suggestions are proposed.Empirical results demonstrate that,compared to the traditional grey possibility clustering model,the proposed model balances the objectivity of indicator weighting,the objectivity of possibility function construction,and the simplicity of the computational process,thereby possessing significant theoretical and practical implications.
基金supported in part by the National Natural Science Foundation of China(Nos.12175100 and 11975132)the Construct Program of the Key Discipline in Hunan Province+5 种基金the Research Foundation of Education Bureau of Hunan Province,China(Nos.21B0402,18A237,22A0305)the Natural Science Foundation of Hunan Province,China(No.2018JJ2321)the Innovation Group of Nuclear and Particle Physics in USCthe Shandong Province Natural Science Foundation,China(No.ZR2022JQ04)the Opening Project of Cooperative Innovation Center for Nuclear Fuel Cycle Technology and Equipment,University of South China(No.2019KFZ10)the Hunan Provincial Innovation Foundation for Postgraduate(No.CX20251453)。
文摘In this study,the effects of laser fields that can be achieved in the near future on cluster penetration probability and half-life are quantitatively investigated.The calculation results show that extreme laser fields can slightly change the cluster-decay half-life by affecting the penetration probability within a narrow range.Subsequently,we discuss the correlation between the change rate of the penetration probability and the tunneling path.The results indicate that for different parent nuclei emitting the same cluster,nuclei with longer tunneling paths are more easily affected by the laser fields.The shell effect on this correlation is also observed.In addition,the impact of laser fields on the penetration probability in any direction is investigated.
基金funded by the European Union—Next Generation EU,in the framework of the consortium i NEST—Interconnected Nord-Est Innovation Ecosystem(PNRR,Missione 4 Componente 2,Investimento 1.5 D.D.105823 June 2022,ECS_00000043—Spoke1,RT2,CUP I43C22000250006)。
文摘This study addresses the persistent scarcity of systematic and comparable data on mountain tourism,with particular reference to Northern Italy,as highlighted by FAO/UNWTO reports and recent academic literature.It aims to contribute to this gap by analyzing tourist flows,socio-demographic characteristics,preferences,and behaviors of domestic visitors to the Italian Alps.Data were collected through a survey conducted between December 2023 and January 2024 among 1,218 residents of Northwest and Northeast Italy and Friuli Venezia Giulia,using a stratified sampling approach.Descriptive statistics and inferential analyses were employed to examine visitation patterns,while K-means clustering was applied to identify distinct segments of mountain tourists based on activity preferences and motivations.Overall,82.5%of respondents reported visiting Alpine areas.Chi-square tests revealed statistically significant differences in visitation behavior according to age,occupational status,and income.Notably,spiritual activities,such as pilgrimages,elicited levels of interest comparable to those of more traditional mountain sports.The cluster analysis identified three visitor profiles:Active Young Enthusiasts,characterized by high engagement in multiple outdoor activities and motivated by psychological well-being and cultural enrichment;Well-being-Oriented Walkers,preferring low-intensity activities primarily driven by psychological relaxation;and Hiking-Oriented Explorers,exhibiting a strong propensity for mountain excursions associated with high levels of psychophysical well-being.These findings enhance understanding of the heterogeneous structure of mountain tourism demand in Northern Italy and offer insights relevant to sustainable destination planning and management in Alpine regions.
基金supported by the National Key R&D Program of China under Grant No.2022YFA1003701the National Natural Science Foundation of China under Grant Nos.12331009 and 12071416the Yunnan Fundamental Research Projects under Grant No.202201AV070006。
文摘This paper aims to develop a unified Bayesian approach for clustered data analysis when observations are subject to missingness at random.The authors consider a general framework in which the parameters of interest are defined through estimating equations,and the probability of missingness follows a general parametric form.The generalized method of moments framework is employed to derive an optimal combination of inverse-probability-weighted estimating equations for the parameters of interest and score equations for propensity score.Using this framework,the authors develop a quasi-Bayesian analysis for clustered samples with missing values.A unified model selection approach is also proposed to compare models characterized by different moment conditions.The authors systematically evaluate the large-sample properties of the proposed quasi-posterior density with both fixed and shrinking priors and establish the selection consistency of the proposed model selection criterion.The proposed results are valid under very mild conditions and offer significant advantages for parameters defined through non-smooth estimating functions.Extensive numerical studies demonstrate that the proposed method performs exceptionally well in finite samples.
基金the financial support from the Shandong Province colleges and universities youth innovation technology plan innovation team project(2022KJ285)the Natural Science Foundation of Shandong Province(ZR2022QE076)+1 种基金the National Natural Science Foundation of China(52202092)the Science and Technology Support Plan for Youth Innovation of Colleges and Universities of Shandong Province of China(2023KJ104).
文摘Exploring high-performance electrocatalysts for the nitrate reduction reaction(NO_(3)RR)is crucial for environmental nitrate removal and ammonia synthesis.Single-atom collaboration with cluster can provide sufficient active sites for catalysts to promote NO_(3)RR,yet the unclear synergistic effect between the two hinders their rational design.Herein,a series of Ir_(3)clusters and metal single atoms co-embedded in graphitic carbon nitride(g-CN)catalysts(Ir_(3)M1)were constructed,and the synergistic effects of Ir_(3)clusters and M1 single atoms on the NO_(3)RR catalytic mechanism and activity were systematically explored using density functional theory(DFT)calculations combined with machine learning.Comprehensive evaluations of structural stability and catalytic activity demonstrate that the synergy between single atoms and clusters effectively balances the adsorption energies of key intermediates,yielding exceptional catalytic performance(the limiting potential of Ir_(3)Ti_(1)can reach−0.22 V).Machine learning models further clarify the synergistic mechanism,where the geometric configurations of clusters serve as critical features for modulating the catalytic activity of single-atom sites,whereas the electronic structures of single atoms directly govern the reactivity of cluster sites.This DFT-machine learning approach provides theoretical guidelines for catalyst design and a predictive framework for efficient NO_(3)RR electrocatalysts.
基金supported by Shanghai Aerospace Science and Technology Innovation Foundation(SAST2023-075)。
文摘Multichannel signals have the characteristics of information diversity and information consistency.To better explore and utilize the affinity relationship within multichannel signals,a new graph learning technique based on low rank tensor approximation is proposed for multichannel monitoring signal processing and utilization.Firstly,the affinity relationship of multichannel signals can be acquired based on the clustering results of each channel signal.Wherein an affinity tensor is constructed to integrate the diverse and consistent information of the clustering information among multichannel signals.Secondly,a low-rank tensor optimization model is built and the joint affinity matrix is optimized with the assistance of the strong confidence affinity matrix.Through solving the optimization model,the fused affinity relationship graph of multichannel signals can be obtained.Finally,the multichannel fused clustering results can be acquired though the updated joint affinity relationship graph.The multichannel signal utilization examples in health state assessment with public datasets and microwave detection with actual echoes verify the advantages and effectiveness of the proposed method.
基金supported in part by the National Natural Science Foundation of China(Grant No.61971291)the Basic Scientific Research Project of the Liaoning Provincial Department of Education(LJ212410144013)+2 种基金the Leading Talent of the‘Xing Liao Ying Cai Plan’(XLYC2202013)the Shenyang Natural Science Foundation(22-315-6-10)the Guangxuan Scholar of Shenyang Ligong University(SYLUGXXZ202205).
文摘With the popularization of smart devices,Location-Based Services(LBS)greatly facilitates users’life,but at the same time brings the risk of users’location privacy leakage.Existing location privacy protection methods are deficient,failing to reasonably allocate the privacy budget for non-outlier location points and ignoring the critical location information that may be contained in the outlier points,leading to decreased data availability and privacy exposure problems.To address these problems,this paper proposes a Mix Location Privacy Preservation Method Based on Differential Privacy with Clustering(MLDP).The method first utilizes the DBSCAN clustering algorithm to classify location points into non-outliers and outliers.For non-outliers,the scoring function is designed by combining geographic information and semantic information,and the privacy budget is allocated according to the heat intensity of the hotspot area;for outliers,the scoring function is constructed to allocate the privacy budget based on their correlation with the hotspot area.By comprehensively considering the geographic information,semantic information,and correlation with hotspot areas of the location points,a reasonable privacy budget is assigned to each location point,andfinallynoise is added throughthe Laplacemechanismto realizeprivacyprotection.Experimental results on tworeal trajectory datasets,Geolife and T-Drive,show that the MLDP approach significantly improves data availability while effectively protecting location privacy.Compared with the comparison methods,the maximum available data ratio of MLDP is 1.Moreover,compared with the RandomNoise method,its execution time is 0.056–0.061 s longer,and the logRE is 0.12951–0.62194 lower;compared with KemeansDP,QTK-DP,DPK-F,IDP-SC,and DPK-Means-up methods,it saves 0.114–0.296 s in execution time,and the logRE is 0.01112–0.38283 lower.
文摘By encouraging collaboration,attracting young entrepreneurs,and setting up village-invested enterprises,rural communities in Zhejiang Province are growing their income streams.“Over the past years,we have seen more and more tourists coming to our village,and their stay here has grown longer.Many even said they don’t want to leave,”Pan Chunlin,a resident of Yucun Village in Anji County of Huzhou City,east China’s Zhejiang Province,told China Today.Pan is the owner of the Chunlin Lodge,a bed&breakfast(B&B)which received more than 70,000 visitors last year,generating over RMB 4 million in revenue.
文摘This paper introduces a fuzzy C-means-based pooling layer for convolutional neural networks that explicitly models local uncertainty and ambiguity.Conventional pooling operations,such as max and average,apply rigid aggregation and often discard fine-grained boundary information.In contrast,our method computes soft membershipswithin each receptive field and aggregates cluster-wise responses throughmembership-weighted pooling,thereby preserving informative structure while reducing dimensionality.Being differentiable,the proposed layer operates as standard two-dimensional pooling.We evaluate our approach across various CNN backbones and open datasets,including CIFAR-10/100,STL-10,LFW,and ImageNette,and further probe small training set restrictions on MNIST and Fashion-MNIST.In these settings,the proposed pooling consistently improves accuracy and weighted F1 over conventional baselines,with particularly strong gains when training data are scarce.Even with less than 1%of the training set,ourmethodmaintains reliable performance,indicating improved sample efficiency and robustness to noisy or ambiguous local patterns.Overall,integrating soft memberships into the pooling operator provides a practical and generalizable inductive bias that enhances robustness and generalization in modern CNN pipelines.
基金Under the auspices of the Key Projects of Philosophy and Social Sciences Research,Ministry of Education of China(No.23JZD008)National Natural Science Foundation of China(No.42171193)+2 种基金Key Project of Guangdong Provincial Philosophy and Social Sciences Planning(No.GD24ES013,GD25ZX04)2025 Guangzhou Basic and Applied Basic Research Special Project(No.2025A04J7127)Fundamental Research Funds for the Central Universities,Sun Yat-sen University(No.24wkjc11)。
文摘The shift toward specialized and large-scale agricultural production has spurred the emergence of agricultural clusters as key forces of rural vitalization and sustainable development.This paper explored the formation and evolution of Meizhou pomelo industry cluster in China,focusing on its role in restructuring rural socio-economic systems and integrating the whole value chains.Based on a case study employing qualitative methods such as in-depth interviews and participatory observation,the agricultural cluster evolution of Meizhou pomelo was categorized into three key phases of initial decentralization,self-organized scaling,and reorganized clustering.Geographical proximity and industrial agglomeration constitute the physical foundation,while vertical/horizontal linkages,technologic-al innovation,and policy support enhance competitiveness.Special mechanisms emerge through localized social networks,farmer co-operatives’activation,and cross-regional market expansion.The cluster’s impact is manifested in the shift from extensive to standard-ized and modernized production,diversified and flexible livelihood of farmers,and the integration of agriculture with industry and ser-vices.The development of the whole value chain based on agricultural cluster represents a critical pathway for achieving agricultural modernization,encompassing both internal and external value chain optimization.Through quality assurance systems,product diversi-fication strategies,operational efficiency improvements,and brand enhancement,these clusters amplify product value propositions and market competitiveness.This systemic approach facilitates supply-demand coordination,enables resource synergies,and optimizes eco-nomic returns across the horizontal and vertical value chain.This paper argues that agricultural clusters serve as strategic catalysts for sustainable rural development by reconstructing local production systems,fostering innovation ecosystems,and aligning agricultural modernization.It contributes to debates on rural vitalization by demonstrating how agricultural clustering can reconfigure rural areas as hubs of ecological modernization,rather than mere urban peripheries.
