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
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
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
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
We study Onsager vortex clustered states in a shell-shaped superfluid containing a large number of quantum vortices.In the incompressible limit and at low temperatures,the relevant problem can be boiled down to the st...We study Onsager vortex clustered states in a shell-shaped superfluid containing a large number of quantum vortices.In the incompressible limit and at low temperatures,the relevant problem can be boiled down to the statistical mechanics of neutral point vortices confined on a sphere.We analyze rotation-free vortex-clustered states within the mean-field theory in the microcanonical ensemble.We find that the sandwich state,which involves the separating of vortices with opposite circulation and the clustering of vortices with the same circulation around the poles and the equator,is the maximum entropy vortex distribution,subject to a zero angular momentum constraint.The dipole moment vanishes for the sandwich state and the quadrupole tensor serves as an order parameter to characterize the vortex cluster structure.For a given finite angular momentum,the equilibrium vortex distribution forms a dipole structure,i.e.,vortices with opposite sign are separated and accumulate around the south and north poles,respectively.The conditions for the onset of clustering and the exponents associated with the quadrupole moment and the dipole moment as functions of energy are obtained within the mean field theory.At large energies,we obtain asymptotically exact vortex density distributions using the stereographic projection method,yielding the parameter bounds for the vortex clustered states.The analytical predictions are in excellent agreement with microcanonical Monte Carlo simulations.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
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
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
This paper proposes an equivalent modeling method for photovoltaic(PV)power stations via a particle swarm optimization(PSO)K-means clustering(KMC)algorithm with passive filter parameter clustering to address the compl...This paper proposes an equivalent modeling method for photovoltaic(PV)power stations via a particle swarm optimization(PSO)K-means clustering(KMC)algorithm with passive filter parameter clustering to address the complexities,simulation time cost and convergence problems of detailed PV power station models.First,the amplitude–frequency curves of different filter parameters are analyzed.Based on the results,a grouping parameter set for characterizing the external filter characteristics is established.These parameters are further defined as clustering parameters.A single PV inverter model is then established as a prerequisite foundation.The proposed equivalent method combines the global search capability of PSO with the rapid convergence of KMC,effectively overcoming the tendency of KMC to become trapped in local optima.This approach enhances both clustering accuracy and numerical stability when determining equivalence for PV inverter units.Using the proposed clustering method,both a detailed PV power station model and an equivalent model are developed and compared.Simulation and hardwarein-loop(HIL)results based on the equivalent model verify that the equivalent method accurately represents the dynamic characteristics of PVpower stations and adapts well to different operating conditions.The proposed equivalent modeling method provides an effective analysis tool for future renewable energy integration research.展开更多
In Wireless Sensor Networks(WSNs),survivability is a crucial issue that is greatly impacted by energy efficiency.Solutions that satisfy application objectives while extending network life are needed to address severe ...In Wireless Sensor Networks(WSNs),survivability is a crucial issue that is greatly impacted by energy efficiency.Solutions that satisfy application objectives while extending network life are needed to address severe energy constraints inWSNs.This paper presents an Adaptive Enhanced GreyWolf Optimizer(AEGWO)for energy-efficient cluster head(CH)selection that mitigates the exploration–exploitation imbalance,preserves population diversity,and avoids premature convergence inherent in baseline GWO.The AEGWO combines adaptive control of the parameter of the search pressure to accelerate convergence without stagnation,a hybrid velocity-momentum update based on the dynamics of PSO,and an intelligent mutation operator to maintain the diversity of the population.The search is guided by a multi-objective fitness,which aims at maximizing the residual energy,equal distribution of CH,minimizing the intra-cluster distance,desirable proximity to sinks,and enhancing the coverage.Simulations on 100 nodes homogeneousWSN Tested the proposed AEGWO under the same conditions with LEACH,GWO,IGWO,PSO,WOA,and GA,AEGWO significantly increases stability and lifetime compared to LEACHand other tested algorithms;it has the best first,half,and last node dead,and higher residual energy and smaller communication overhead.The findings prove that AEGWO provides sustainable energy management and better lifetime extension,which makes it a robust,flexible clustering protocol of large-scaleWSNs.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
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.
Introduction:Chemotherapy-induced gastrointestinal symptom clusters in breast cancer impair quality of life and treatment adherence,yet lack effective interventions.While acupuncture mitigates isolated chemotherapy-in...Introduction:Chemotherapy-induced gastrointestinal symptom clusters in breast cancer impair quality of life and treatment adherence,yet lack effective interventions.While acupuncture mitigates isolated chemotherapy-induced symptoms,its mechanisms for multi-symptom clusters remain unclear.This study evaluates electroacupuncture's efficacy and explores its biological mechanisms in managing these clusters.Methods:This prospective,multicenter,block-randomized,double-blind,sham-controlled trial will enroll 388 patients with breast cancer undergoing neoadjuvant/adjuvant chemotherapy,to be randomly assigned(1:1)to electroacupuncture or sham electro-acupuncture groups.Both groups will receive the standard quadruple antiemetic regimen combined with electroacupuncture or sham intervention.The primary endpoint is the incidence of chemotherapy-induced gastrointestinal symptom clusters within 120 h after chemotherapy.Secondary endpoints include improvement in gastrointestinal symptom clusters post-first chemotherapy cycle,nausea-free rates during acute and delayed phases,vomiting-free rates during overall,acute,and delayed phases,complete response rate,complete protection rate,and quality of life.Adverse events will be documented throughout the study.Discussion:This study will assess the efficacy and safety of electroacupuncture in alleviating chemotherapy-induced gastro-intestinal symptom clusters in patients with breast cancer.By integrating multi-omics analyses,we aim to elucidate the biological mechanisms underlying its therapeutic effects.The findings may offer a robust clinical foundation for optimizing symptom cluster management in cancer care.Trial Registration:Clinical Trials ID:NCT06952920.Date of registration:April 16,2025.Prospectively registered.URL of Trial Registry Record:https://clinicaltrials.gov/study/NCT06952920cond=NCT06952920&rank=1.展开更多
Based on the conventional observation data,daily reanalysis data from NCAR/NCEP,and TBB data derived from FY-2G infrared cloud images in April 2018,a heavy snowfall weather process in central Inner Mongolia from April...Based on the conventional observation data,daily reanalysis data from NCAR/NCEP,and TBB data derived from FY-2G infrared cloud images in April 2018,a heavy snowfall weather process in central Inner Mongolia from April 4 to 6 in 2018 was analyzed.The results show that the low trough at 500 hPa,the southerly wind jet stream at 700 hPa,and the inverted trough on the ground were the main influencing systems causing this blizzard.The transportation of warm and humid air by the southerly wind jet stream at 700 hPa and intense water vapor convergence provided sufficient water vapor conditions for the blizzard,and the moist layer in the blizzard area was deep.The low-level MPV in the blizzard area was<0,and the atmosphere was in a conditional symmetric instability state.The coupling of the upper and lower-level jets induced strong ascending motion.With the invasion of cold air,a low-level cold pad was formed,so that the warm and humid air tilted upward.The secondary circulation updraft triggered by the wet Q vector system released the conditional symmetric instability energy,so that the sloping motion was more intense,and the heavy snowfall appeared.Meanwhile,there was a good correspondence relationship between the blizzard area and the large-value area of low-level wet Q vector divergence.The mesoscale cloud clusters continuously generating,merging,and moving eastward in Hetao area were the direct cause of this blizzard,and the TBB of the cloud clusters was≤-56℃.The blizzard happened in the the edge gradient and large-value area of TBB.展开更多
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.
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 from the National Natural Science Foundation of China(Grant No.12175215,Grant No.12475041)the National Key Research and Development Program of China(Grant No.2022YFA 1405300)NSAF(Grant No.U2330401)。
文摘We study Onsager vortex clustered states in a shell-shaped superfluid containing a large number of quantum vortices.In the incompressible limit and at low temperatures,the relevant problem can be boiled down to the statistical mechanics of neutral point vortices confined on a sphere.We analyze rotation-free vortex-clustered states within the mean-field theory in the microcanonical ensemble.We find that the sandwich state,which involves the separating of vortices with opposite circulation and the clustering of vortices with the same circulation around the poles and the equator,is the maximum entropy vortex distribution,subject to a zero angular momentum constraint.The dipole moment vanishes for the sandwich state and the quadrupole tensor serves as an order parameter to characterize the vortex cluster structure.For a given finite angular momentum,the equilibrium vortex distribution forms a dipole structure,i.e.,vortices with opposite sign are separated and accumulate around the south and north poles,respectively.The conditions for the onset of clustering and the exponents associated with the quadrupole moment and the dipole moment as functions of energy are obtained within the mean field theory.At large energies,we obtain asymptotically exact vortex density distributions using the stereographic projection method,yielding the parameter bounds for the vortex clustered states.The analytical predictions are in excellent agreement with microcanonical Monte Carlo simulations.
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.
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 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 the Research Project of China Southern Power Grid(No.056200KK52222031).
文摘This paper proposes an equivalent modeling method for photovoltaic(PV)power stations via a particle swarm optimization(PSO)K-means clustering(KMC)algorithm with passive filter parameter clustering to address the complexities,simulation time cost and convergence problems of detailed PV power station models.First,the amplitude–frequency curves of different filter parameters are analyzed.Based on the results,a grouping parameter set for characterizing the external filter characteristics is established.These parameters are further defined as clustering parameters.A single PV inverter model is then established as a prerequisite foundation.The proposed equivalent method combines the global search capability of PSO with the rapid convergence of KMC,effectively overcoming the tendency of KMC to become trapped in local optima.This approach enhances both clustering accuracy and numerical stability when determining equivalence for PV inverter units.Using the proposed clustering method,both a detailed PV power station model and an equivalent model are developed and compared.Simulation and hardwarein-loop(HIL)results based on the equivalent model verify that the equivalent method accurately represents the dynamic characteristics of PVpower stations and adapts well to different operating conditions.The proposed equivalent modeling method provides an effective analysis tool for future renewable energy integration research.
基金The Open Access publication fee for this article was fully covered by Abu Dhabi University.
文摘In Wireless Sensor Networks(WSNs),survivability is a crucial issue that is greatly impacted by energy efficiency.Solutions that satisfy application objectives while extending network life are needed to address severe energy constraints inWSNs.This paper presents an Adaptive Enhanced GreyWolf Optimizer(AEGWO)for energy-efficient cluster head(CH)selection that mitigates the exploration–exploitation imbalance,preserves population diversity,and avoids premature convergence inherent in baseline GWO.The AEGWO combines adaptive control of the parameter of the search pressure to accelerate convergence without stagnation,a hybrid velocity-momentum update based on the dynamics of PSO,and an intelligent mutation operator to maintain the diversity of the population.The search is guided by a multi-objective fitness,which aims at maximizing the residual energy,equal distribution of CH,minimizing the intra-cluster distance,desirable proximity to sinks,and enhancing the coverage.Simulations on 100 nodes homogeneousWSN Tested the proposed AEGWO under the same conditions with LEACH,GWO,IGWO,PSO,WOA,and GA,AEGWO significantly increases stability and lifetime compared to LEACHand other tested algorithms;it has the best first,half,and last node dead,and higher residual energy and smaller communication overhead.The findings prove that AEGWO provides sustainable energy management and better lifetime extension,which makes it a robust,flexible clustering protocol of large-scaleWSNs.
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.
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.
基金Noncommunicable Chronic Diseases-National Science and Technology Major Project,Grant/Award Numbers:2024ZD0521400,2024ZD0521404Affiliated Hospital of Qinghai University。
文摘Introduction:Chemotherapy-induced gastrointestinal symptom clusters in breast cancer impair quality of life and treatment adherence,yet lack effective interventions.While acupuncture mitigates isolated chemotherapy-induced symptoms,its mechanisms for multi-symptom clusters remain unclear.This study evaluates electroacupuncture's efficacy and explores its biological mechanisms in managing these clusters.Methods:This prospective,multicenter,block-randomized,double-blind,sham-controlled trial will enroll 388 patients with breast cancer undergoing neoadjuvant/adjuvant chemotherapy,to be randomly assigned(1:1)to electroacupuncture or sham electro-acupuncture groups.Both groups will receive the standard quadruple antiemetic regimen combined with electroacupuncture or sham intervention.The primary endpoint is the incidence of chemotherapy-induced gastrointestinal symptom clusters within 120 h after chemotherapy.Secondary endpoints include improvement in gastrointestinal symptom clusters post-first chemotherapy cycle,nausea-free rates during acute and delayed phases,vomiting-free rates during overall,acute,and delayed phases,complete response rate,complete protection rate,and quality of life.Adverse events will be documented throughout the study.Discussion:This study will assess the efficacy and safety of electroacupuncture in alleviating chemotherapy-induced gastro-intestinal symptom clusters in patients with breast cancer.By integrating multi-omics analyses,we aim to elucidate the biological mechanisms underlying its therapeutic effects.The findings may offer a robust clinical foundation for optimizing symptom cluster management in cancer care.Trial Registration:Clinical Trials ID:NCT06952920.Date of registration:April 16,2025.Prospectively registered.URL of Trial Registry Record:https://clinicaltrials.gov/study/NCT06952920cond=NCT06952920&rank=1.
基金Supported by the Meteorological Science and Technology Innovation Project of North China(HBXM202415)Research Project of the Meteorological Bureau of Inner Mongolia Autonomous Region(nmqxkjcx202311).
文摘Based on the conventional observation data,daily reanalysis data from NCAR/NCEP,and TBB data derived from FY-2G infrared cloud images in April 2018,a heavy snowfall weather process in central Inner Mongolia from April 4 to 6 in 2018 was analyzed.The results show that the low trough at 500 hPa,the southerly wind jet stream at 700 hPa,and the inverted trough on the ground were the main influencing systems causing this blizzard.The transportation of warm and humid air by the southerly wind jet stream at 700 hPa and intense water vapor convergence provided sufficient water vapor conditions for the blizzard,and the moist layer in the blizzard area was deep.The low-level MPV in the blizzard area was<0,and the atmosphere was in a conditional symmetric instability state.The coupling of the upper and lower-level jets induced strong ascending motion.With the invasion of cold air,a low-level cold pad was formed,so that the warm and humid air tilted upward.The secondary circulation updraft triggered by the wet Q vector system released the conditional symmetric instability energy,so that the sloping motion was more intense,and the heavy snowfall appeared.Meanwhile,there was a good correspondence relationship between the blizzard area and the large-value area of low-level wet Q vector divergence.The mesoscale cloud clusters continuously generating,merging,and moving eastward in Hetao area were the direct cause of this blizzard,and the TBB of the cloud clusters was≤-56℃.The blizzard happened in the the edge gradient and large-value area of TBB.
