Interfacial interactions between rough mineral particles have garnered considerable attention as they directly determine particle agglomeration and floatability.This study comprehensively investigates the agglomeratio...Interfacial interactions between rough mineral particles have garnered considerable attention as they directly determine particle agglomeration and floatability.This study comprehensively investigates the agglomeration characteristics of siderite particles after argon(Ar)plasma surface modification through settling tests,flocs size measurements,and fractal dimension calculations.Ar plasma surface modification promotes the agglomeration of siderite particles,as evidenced by increased floc size and density.The agglomeration mechanism induced by Ar plasma surface modification is evaluated using a theoretical model combining the surface element integration(SEI)approach,differential geometry,and the composite Simpson's rule.Changes in surface roughness,wettability,and charge are considered in this model.Compared to the unpretreated siderite particles,the energy barrier for interaction of the 30-min Ar plasma-pretreated siderite particles decreases from 2.3×10-^(17)J to 1.6×10^(-17)J.This reduction provides strong evidence for the agglomeration behavior of siderite particles.Furthermore,flotation experiments confirm that Ar plasma surface modification is conducive to the aggregation flotation of siderite.These findings offer crucial insights into particle aggregation and dispersion behaviors,with notable application in mineral flotation.展开更多
The effect of mechanical activation on the granulometric parameters,microstructure,and leaching efficiency of chalcopyrite was evaluated,and the occurrence/transition of agglomeration and aggregation was discussed.The...The effect of mechanical activation on the granulometric parameters,microstructure,and leaching efficiency of chalcopyrite was evaluated,and the occurrence/transition of agglomeration and aggregation was discussed.The results showed that in 8 h of milling treatment,the agglomeration and the microstructure did not affect each other.However,with prolonging milling time,the crystallite size tended to reach a saturation value,and the stagnating microstructural changes led to the replacement of agglomeration by aggregation.The leaching results indicated that the mechanical activation can strongly enhance the reactivity of chalcopyrite and the hindering effect of aggregation on leaching was considerably greater than that of agglomeration.Consequently,after 8 h of milling,the maximum Cu leaching rate of 80.13%was achieved after 4 h of acid leaching.展开更多
The monomer agglomeration of nonmetallic inclusions was simulated with a diffusion limited aggregation （DLA） model of the fractal theory. The simulation study with a random two-dimensional diffusion was carried out....The monomer agglomeration of nonmetallic inclusions was simulated with a diffusion limited aggregation （DLA） model of the fractal theory. The simulation study with a random two-dimensional diffusion was carried out. The results indicate that the DLA model can be used for the simulation of agglomeration behavior of the cluster-type inclusions. The morphology of clusters was observed with SEM and compared with the simulated agglomerates. The modelling procedure of the DLA model is applicable for the agglomeration process. The uncertainty of agglomeration process and the persuasive average agglomerative ratio was analyzed. The factors about the agglomerative ratio with the collision path distance and the size of particles or seed were discussed. The adherence of the nonmetallic inclusions on the dam, the weir and the walls of a tundish, and the absorption of inclusions by stopper or nozzle were also discussed.展开更多
Patna is among the cities high populated at risk of ecological and environmental deterioration due to a variety of human activities,such as poor land cover management.One of the most crucial elements of a successful l...Patna is among the cities high populated at risk of ecological and environmental deterioration due to a variety of human activities,such as poor land cover management.One of the most crucial elements of a successful land resource management plan is the evaluation of Land Use Land Cover(LULC).Over the past 20 years,our planet’s land cover resources have undergone substantial changes due to rapid development.The Land Use Land Cover(LULC)categories of the Patna Urban Agglomeration(PUA),including water bodies,agricultural land,barren land,built-up areas,and vegetation,were identified using Geographic Information System(GIS)techniques.Three multi-temporal images were analyzed and classified through supervised classification using the maximum likelihood method.By comparing three separately created LULC categorized maps from 1990 and 2024,temporal changes were analyzed.In order to update land cover or manage natural resources,it is vital to use change detection as a tool to identify changes in LULC over time in PUA,Patna between 1990,2010 and 2024.According to their respective Kappa coefficients,the accuracy rates for 1990,2010 and 2024 LULC are 91.66 and 94.93,respectively.An accuracy evaluation was conducted to determine the correctness of the classification system and to determine the efficacy of the LULC classification maps.One hundred reference test pixels were identified.There have been found significant changes in the LULC were built up area has increased doubled in last thirty-four years of timeline.展开更多
In this study, the influence of fluid cracking catalyst(FCC) on the fluidization behavior of ZnO-CuO binary nanoparticles was systematically investigated by varying FCC size. High-speed camera was employed to analyze ...In this study, the influence of fluid cracking catalyst(FCC) on the fluidization behavior of ZnO-CuO binary nanoparticles was systematically investigated by varying FCC size. High-speed camera was employed to analyze the collision and fragmentation process of agglomerates with adding FCC coarse particles. It can be found from photographs by the camera that fluidization performance improved by the agglomerate variation that is bound to be shaped a compact and spherical structure. Furthermore, the result of agglomeration composition analysis showed that uniform mixing of nanoparticles remarkably affected the fluidization behavior of ZnO-CuO binary system. Finally, the improvement of fluidization performance can be justified by the analysis of inter-cohesive force between the two agglomerates with sharp reduction of the newly-formed agglomerates.展开更多
Majority of carbon emissions originate from fossil energy consumption,thus necessitating calculation and monitoring of carbon emissions from energy consumption.In this study,we utilized energy consumption data from Si...Majority of carbon emissions originate from fossil energy consumption,thus necessitating calculation and monitoring of carbon emissions from energy consumption.In this study,we utilized energy consumption data from Sichuan Province and Chongqing Municipality for the years 2000 to 2019 to estimate their statistical carbon emissions.We then employed nighttime light data to downscale and infer the spatial distribution of carbon emissions at the county level within the Chengdu-Chongqing urban agglomeration.Furthermore,we analyzed the spatial pattern of carbon emissions at the county level using the coefficient of variation and spatial autocorrelation,and we used the Geographically and Temporally Weighted Regression(GTWR)model to analyze the influencing factors of carbon emissions at this scale.The results of this study are as follows:(1)from 2000 to 2019,the overall carbon emissions in the Chengdu-Chongqing urban agglomeration showed an increasing trend followed by a decrease,with an average annual growth rate of 4.24%.However,in recent years,it has stabilized,and 2012 was the peak year for carbon emissions in the Chengdu-Chongqing urban agglomeration;(2)carbon emissions exhibited significant spatial clustering,with high-high clustering observed in the core urban areas of Chengdu and Chongqing and low-low clustering in the southern counties of the Chengdu-Chongqing urban agglomeration;(3)factors such as GDP,population(Pop),urbanization rate(Ur),and industrialization structure(Ic)all showed a significant influence on carbon emissions;(4)the spatial heterogeneity of each influencing factor was evident.展开更多
Neurons are highly polarized cells with axons reaching over a meter long in adult humans.To survive and maintain their proper function,neurons depend on specific mechanisms that regulate spatiotemporal signaling and m...Neurons are highly polarized cells with axons reaching over a meter long in adult humans.To survive and maintain their proper function,neurons depend on specific mechanisms that regulate spatiotemporal signaling and metabolic events,which need to be carried out at the right place,time,and intensity.Such mechanisms include axonal transport,local synthesis,and liquid-liquid phase separations.Alterations and malfunctions in these processes are correlated to neurodegenerative diseases such as amyotrophic lateral sclerosis(ALS).展开更多
In global navigation satellite system denial environment,cross-view geo-localization based on image retrieval presents an exceedingly critical visual localization solution for Unmanned Aerial Vehicle(UAV)systems.The e...In global navigation satellite system denial environment,cross-view geo-localization based on image retrieval presents an exceedingly critical visual localization solution for Unmanned Aerial Vehicle(UAV)systems.The essence of cross-view geo-localization resides in matching images containing the same geographical targets from disparate platforms,such as UAV-view and satellite-view images.However,images of the same geographical targets may suffer from occlusions and geometric distortions due to variations in the capturing platform,view,and timing.The existing methods predominantly extract features by segmenting feature maps,which overlook the holistic semantic distribution and structural information of objects,resulting in loss of image information.To address these challenges,dilated neighborhood attention Transformer is employed as the feature extraction backbone,and Multi-feature representations based on Multi-scale Hierarchical Contextual Aggregation(MMHCA)is proposed.In the proposed MMHCA method,the multiscale hierarchical contextual aggregation method is utilized to extract contextual information from local to global across various granularity levels,establishing feature associations of contextual information with global and local information in the image.Subsequently,the multi-feature representations method is utilized to obtain rich discriminative feature information,bolstering the robustness of model in scenarios characterized by positional shifts,varying distances,and scale ambiguities.Comprehensive experiments conducted on the extensively utilized University-1652 and SUES-200 benchmarks indicate that the MMHCA method surpasses the existing techniques.showing outstanding results in UAV localization and navigation.展开更多
The rapid proliferation of electric vehicle(EV)charging infrastructure introduces critical cybersecurity vulnerabilities to power grids system.This study presents an innovative anomaly detection framework for EV charg...The rapid proliferation of electric vehicle(EV)charging infrastructure introduces critical cybersecurity vulnerabilities to power grids system.This study presents an innovative anomaly detection framework for EV charging stations,addressing the unique challenges posed by third-party aggregation platforms.Our approach integrates node equations-based on the parameter identification with a novel deep learning model,xDeepCIN,to detect abnormal data reporting indicative of aggregation attacks.We employ a graph-theoretic approach to model EV charging networks and utilize Markov Chain Monte Carlo techniques for accurate parameter estimation.The xDeepCIN model,incorporating a Compressed Interaction Network,has the ability to capture complex feature interactions in sparse,high-dimensional charging data.Experimental results on both proprietary and public datasets demonstrate significant improvements in anomaly detection performance,with F1-scores increasing by up to 32.3%for specific anomaly types compared to traditional methods,such as wide&deep and DeepFM(Factorization-Machine).Our framework exhibits robust scalability,effectively handling networks ranging from 8 to 85 charging points.Furthermore,we achieve real-time monitoring capabilities,with parameter identification completing within seconds for networks up to 1000 nodes.This research contributes to enhancing the security and reliability of renewable energy systems against evolving cyber threats,offering a comprehensive solution for safeguarding the rapidly expanding EV charging infrastructure.展开更多
As smart grid technology rapidly advances,the vast amount of user data collected by smart meter presents significant challenges in data security and privacy protection.Current research emphasizes data security and use...As smart grid technology rapidly advances,the vast amount of user data collected by smart meter presents significant challenges in data security and privacy protection.Current research emphasizes data security and user privacy concerns within smart grids.However,existing methods struggle with efficiency and security when processing large-scale data.Balancing efficient data processing with stringent privacy protection during data aggregation in smart grids remains an urgent challenge.This paper proposes an AI-based multi-type data aggregation method designed to enhance aggregation efficiency and security by standardizing and normalizing various data modalities.The approach optimizes data preprocessing,integrates Long Short-Term Memory(LSTM)networks for handling time-series data,and employs homomorphic encryption to safeguard user privacy.It also explores the application of Boneh Lynn Shacham(BLS)signatures for user authentication.The proposed scheme’s efficiency,security,and privacy protection capabilities are validated through rigorous security proofs and experimental analysis.展开更多
This study focuses on urgent research on restoring and enhancing carbon storage capacity in the Beibu Gulf Urban Agglomer-ation of China,a key area in the‘Belt and Road’Initiative,which aligns with carbon peaking an...This study focuses on urgent research on restoring and enhancing carbon storage capacity in the Beibu Gulf Urban Agglomer-ation of China,a key area in the‘Belt and Road’Initiative,which aligns with carbon peaking and neutrality goals.This research ana-lyzes the spatial characteristics of carbon metabolism from 2000 to 2020 and uses models to identify stable carbon sink areas,positive carbon flow corridors,and carbon sequestration nodes.The goal is to construct a carbon metabolism spatial security pattern(CMSSP)and propose territorial ecological restoration strategies under different development demand scenarios.The results show the following:1)in 2020,the study area’s carbon sink decreased by 8.29×10^(4) t C/yr compared with that in 2010 and by 10.83×10^(4) t C/yr compared with that in 2000.High-carbon sinks were found mainly in mountainous areas,whereas low-carbon sinks are concentrated in urban con-struction land,rural residential areas,and land margins.2)From 2000 to 2020,the spatial security pattern of carbon metabolism tended to be‘high in the middle of the east and west and low in the gulf.’In 2000,2010,and 2020,16 stable carbon sinks were identified.The carbon energy flow density in Guangxi was greater than that in Guangdong and Hainan,with positive carbon flow corridors located primarily in Guangxi and Guangdong.The number of carbon sequestration nodes remained stable at approximately 15,mainly in Guangxi and Hainan.3)Scenario simulations revealed that under the Nature-based mild restoration scenario,the carbon sink rate will reach 611.85×10^(4) t C/yr by 2030 and increase to 612.45×10^(4) t C/yr by 2060,with stable carbon sinks increasing to 18.In the restora-tion scenario based on Anti-globalization,the carbon sink will decrease from 610.24×10^(4) t C/yr in 2030 to 605.19×10^(4) t C/yr in 2060,with the disappearance of some positive carbon flow corridors and stable carbon sinks.Under the Human-based sustainable restoration scenario,the carbon sink area will decrease from 607.00×10^(4) t C/yr in 2030 to 596.39×10^(4) t C/yr in 2060,with carbon sink areas frag-menting and positive carbon flow corridors becoming less dense.4)On the basis of the current and predicted CMSSPs,this study ex-plores spatial ecological restoration strategies for high-carbon storage areas in bay urban agglomerations at four levels:the land control region,urban agglomeration structure system,carbon sink structure and bay structure control region.展开更多
Accurate medical diagnosis,which involves identifying diseases based on patient symptoms,is often hindered by uncertainties in data interpretation and retrieval.Advanced fuzzy set theories have emerged as effective to...Accurate medical diagnosis,which involves identifying diseases based on patient symptoms,is often hindered by uncertainties in data interpretation and retrieval.Advanced fuzzy set theories have emerged as effective tools to address these challenges.In this paper,new mathematical approaches for handling uncertainty in medical diagnosis are introduced using q-rung orthopair fuzzy sets(q-ROFS)and interval-valued q-rung orthopair fuzzy sets(IVq-ROFS).Three aggregation operators are proposed in our methodologies:the q-ROF weighted averaging(q-ROFWA),the q-ROF weighted geometric(q-ROFWG),and the q-ROF weighted neutrality averaging(qROFWNA),which enhance decision-making under uncertainty.These operators are paired with ranking methods such as the similarity measure,score function,and inverse score function to improve the accuracy of disease identification.Additionally,the impact of varying q-rung values is explored through a sensitivity analysis,extending the analysis beyond the typical maximum value of 3.The Basic Uncertain Information(BUI)method is employed to simulate expert opinions,and aggregation operators are used to combine these opinions in a group decisionmaking context.Our results provide a comprehensive comparison of methodologies,highlighting their strengths and limitations in diagnosing diseases based on uncertain patient data.展开更多
Farmland transfer is an important land policy for reducing agricultural fragmentation and improving land use efficiency.Many studies have investigated the driving forces of farmland transfer at the farmers’scale.Howe...Farmland transfer is an important land policy for reducing agricultural fragmentation and improving land use efficiency.Many studies have investigated the driving forces of farmland transfer at the farmers’scale.However,the overall spatial distribution and driving mechanisms of farmland transfer at the county scale has been less quantified.In this study,we evaluated farmland transfer and its spatial pattern in Central Yunnan Urban Agglomeration(CYUA)of China by using statistical data at the county scale in 2020.A so-cial-ecological indicator system,comprising natural endowment,social indicators,economic indicators,and landscape patterns,was es-tablished to explore the relationship between farmland transfer and its driving factors.Additionally,a heuristic structural equation mod-el(SEM)was employed to disentangle direct and indirect drivers of farmland transfer.The results indicated that significant spatial clusters of farmland transfer,with high transfer rates concentrated in highly urbanized areas and low transfer rates prevalent in tradition-al ethnic minority regions.Farmland transfer is primarily driven by soil quality,landscape patterns,terrain,and social-economic rurality.Specifically,higher soil quality and improved landscape connectivity facilitate farmland transfer directly,while gentler slopes promote farmland transfer indirectly by supporting better educational opportunities and fewer minority population.Improving rural vocational training and optimizing landscape patterns through land consolidation and redistribution are important in the mountainous areas.This study can provide valuable analytical framework for farmland management for other mountainous regions.展开更多
Parkinson's disease (PD) is a common degenerative disorder that is becoming increasingly prevalent because of the global aging population.The exact cause of the disorder is unknown;however,recent studies have sugg...Parkinson's disease (PD) is a common degenerative disorder that is becoming increasingly prevalent because of the global aging population.The exact cause of the disorder is unknown;however,recent studies have suggested that multiple factors may contribute to its pathogenesis.PD is characterized by a movement disorder that primarily affects motor control;pathologically,the disease is marked by the presence of Lewy bodies (LBs) in the brain.展开更多
The formation of large-sized inclusions cluster severely impacts the continuous casting process and product quality of titanium-containing steel.Thermodynamic calculations were initially conducted to predict the forma...The formation of large-sized inclusions cluster severely impacts the continuous casting process and product quality of titanium-containing steel.Thermodynamic calculations were initially conducted to predict the formation of various complex oxide inclusions,namely Al_(2)O_(3),TiO_(x)and Al-Ti-O.Based on that,laboratory-scale experiments were designed to prepare samples with a single type of inclusions.Then,the scanning electron microscope-energy dispersive spectrometer was used for quantitative characterization.Subsequently,the agglomeration behavior of inclusions in Fe-Al-Ti-O melt was observed in situ by high-temperature confocal laser scanning microscopy.Furthermore,a quantitative analysis of the agglomeration characteristics of the various inclusions was conducted based on the attractive forces in accordance with Newton's second law and the capillary forces as described by the Kralchevsky-Paunov model.The results indicate that the size of Al_(2)O_(3)inclusions is larger than that of TiO_(x)and Al-Ti-O,but the number density of TiO_(x)is the highest.Based on the in situ observation and the theoretical calculation,Al_(2)O_(3),TiO_(x)and Al-Ti-O inclusions can all agglomerate into large-sized clusters without segregation,but the agglomeration tendency of Al_(2)O_(3)and TiO_(x)is stronger than that of Al-Ti-O.The attractive force between Al_(2)O_(3)inclusions’pair is the largest,ranging from 2.26×10^(-15)to 6.12×10^(-14)N,followed by TiO_(x)(7.13×10^(-16)to 3.56×10^(-14)N)and Al-Ti-O(1.16×10^(-17)to 3.77×10^(-16)N).展开更多
Understanding the motion behaviors of non-metallic inclusions in the liquid metal is important for clean steel production.High-temperature confocal laser scanning microscopy is applied to investigate the effect of dif...Understanding the motion behaviors of non-metallic inclusions in the liquid metal is important for clean steel production.High-temperature confocal laser scanning microscopy is applied to investigate the effect of different Ti and Al contents on the agglomeration behavior of non-metallic inclusions in low carbon steels.Furthermore,the agglomeration mechanism of inclusions was investigated through quantitative analysis of in-situ observation experiments and a modified Kralchevsky-Paunov model.The obtained results indicate that Al_(2)O_(3)is the main type inclusion in the low-alloys steels with both Al and Ti addition.This type of inclusion is more likely to absorb surrounding small-size inclusion particles,leading to a further growth for the cluster formation and contributing to a serious engineering problem,nozzle clogging.Besides,TiO_(x)is the main type inclusion in the molten steel with only Ti addition,and this type of inclusion is less likely to agglomerate and the individual inclusion particles show a‘free’motion with the fluid of molten steel.The difference between these two types of inclusions is due to the difference in attractive force and action distance at the meniscus created by the inclusion/steel/Ar multiple interfaces and influenced by the physical parameters,e.g.,contact angle and interface energy between inclusion and steel,and surface tension of the melt.展开更多
Integrating Artificial Intelligence of Things(AIoT)in healthcare offers transformative potential for real-time diagnostics and collaborative learning but presents critical challenges,including privacy preservation,com...Integrating Artificial Intelligence of Things(AIoT)in healthcare offers transformative potential for real-time diagnostics and collaborative learning but presents critical challenges,including privacy preservation,computational efficiency,and regulatory compliance.Traditional approaches,such as differential privacy,homomorphic encryption,and secure multi-party computation,often fail to balance performance and privacy,rendering them unsuitable for resource-constrained healthcare AIoT environments.This paper introduces LMSA(Lightweight Multi-Key Secure Aggregation),a novel framework designed to address these challenges and enable efficient,secure federated learning across distributed healthcare institutions.LMSA incorporates three key innovations:(1)a lightweight multikey management system leveraging Diffie-Hellman key exchange and SHA3-256 hashing,achieving O(n)complexity with AES(Advanced Encryption Standard)-256-level security;(2)a privacy-preserving aggregation protocol employing hardware-accelerated AES-CTR(CounTeR)encryption andmodular arithmetic for securemodel weight combination;and(3)a resource-optimized implementation utilizing AES-NI(New Instructions)instructions and efficient memory management for real-time operations on constrained devices.Experimental evaluations using the National Institutes of Health(NIH)Chest X-ray dataset demonstrate LMSA’s ability to train multi-label thoracic disease prediction models with Vision Transformer(ViT),ResNet-50,and MobileNet architectures across distributed healthcare institutions.Memory usage analysis confirmed minimal overhead,with ViT(327.30 MB),ResNet-50(89.87 MB),and MobileNet(8.63 MB)maintaining stable encryption times across communication rounds.LMSA ensures robust security through hardware acceleration,enabling real-time diagnostics without compromising patient confidentiality or regulatory compliance.Future research aims to optimize LMSA for ultra-low-power devices and validate its scalability in heterogeneous,real-world environments.LMSA represents a foundational advancement for privacy-conscious healthcare AI applications,bridging the gap between privacy and performance.展开更多
In the context of China’ s dual carbon goals, transforming traditional manufacturing agglomeration into green manufacturing agglomeration is pivotal in aligning economic development with environmental protection, ult...In the context of China’ s dual carbon goals, transforming traditional manufacturing agglomeration into green manufacturing agglomeration is pivotal in aligning economic development with environmental protection, ultimately contributing to the country’ s high-quality economic growth. This study examines the dynamic nonlinear effects of manufacturing agglomeration on economic development, energy consumption, environmental pollution, and green total factor productivity. We developed a theoretical framework that considered local government constraints and incentives as transition variables and employed panel data from 280 cities at or above the prefecture level in China from 2006 to 2020 using a Panel Smooth Transition Regression model. The results reveal that, first, under both constraints and incentives, a single threshold effect exists beyond which the positive impact of manufacturing agglomeration on economic development, energy consumption, and environmental pollution gradually weakens. Second, the spatiotemporal evolution of manufacturing agglomeration shows that traditional manufacturing agglomerations are gradually spreading from the central and western regions to the resourcebased regions in the eastern part of the country, while green manufacturing agglomerations are shrinking annually. Third, a comparative analysis indicates that, in both developed and developing countries, manufacturing agglomeration effects are strongest when government constraints do not exceed the threshold. However, in developing countries, when this threshold is surpassed, the momentum for green transformation becomes insufficient. Finally, digital infrastructure positively promotes the green transformation of manufacturing agglomerations, although its effects are influenced by other factors.展开更多
AP(Ammonium Perchlorate)and HMX(Octogen)are the two oxidizers most often used in Nitrate-Ester-Plasticized Polyether(NEPE)rocket propellants.How the AP–HMX ratio influences the agglomeration of NEPE propellants remai...AP(Ammonium Perchlorate)and HMX(Octogen)are the two oxidizers most often used in Nitrate-Ester-Plasticized Polyether(NEPE)rocket propellants.How the AP–HMX ratio influences the agglomeration of NEPE propellants remains unclear.We experimentally investigated the effect of the AP–HMX ratio on the combustion and agglomeration of NEPE propellants using burning rate test,quenched surface analysis,microscopic observations,and the collection of condensed combustion products.It was found that with the decrease in AP content from 40wt%to 10wt%,the burning rate decreased from 14.2 mm/s to 9.2 mm/s because the adiabatic flame temperature of NEPE propellants decreased from 3828 K to 3736 K.Pockets bounded by AP particles appeared on the surface when AP content was 40wt%;however,the accumulations grew and covered the burning surface eventually as the AP–HMX ratio decreased.The time required for the accumulation to coalesce into agglomerates increased with decreasing AP content.Even with similar agglomerate sizes,the coalescence time increased by 83%when the AP content decreased from 40wt%to 30wt%.The agglomerate size in the Condensed Combustion Products(CCPs)increased from 100μm to 200μm,and the fraction of large agglomerations increased from 6.4%to 24.7%when the AP content decreased from 40wt%to 10wt%.Overall,the high flame temperature of the AP particles enhanced the decomposition of the surrounding binder,resulting in the rapid ejection of the aluminum particles into the gas,which had a separating effect on the accumulation,thus weakening the agglomeration.展开更多
Research on urban health constitutes an important issue in the field of health geography and also a strong propeller of the Healthy China Initiative.As the main form that realizes new-type urbanization,urban agglomera...Research on urban health constitutes an important issue in the field of health geography and also a strong propeller of the Healthy China Initiative.As the main form that realizes new-type urbanization,urban agglomerations should become the primal sites for the construction of a“Healthy China”.The evaluation of healthy cities’development in urban agglomerations has both theoretical and practical values.Based on the concept of urban health and its evaluation models,this paper developed an evaluation framework for healthy cities that involved multiple data sources.With 19 urban agglomerations in China as the research subjects,we used CRITIC weighting and geographical detectors to examine the geographies of healthy cities and their influencing factors in 2010 and 2020.The results were fourfold.Firstly,the urban health level of China significantly increased from 2010 to 2020,and the comprehensive health index developed towards a positive skewed distribution,along with a shift from“low in the hinterland-high in the coastal areas”to a“multipolar”pattern led by the coastal and southwest urban agglomerations.Secondly,among various dimensions of urban health,the healthy environment index became improved with narrowed regional differences;while the health services index was still polarized;health collaboration was upgraded with a strengthened intercity health network;the healthy population index slightly declined and converged to the middle.Thirdly,urban health in China has initially demonstrated the characteristics of a H-H pattern in the Yangtze River Delta and ChengduChongqing regions,as well as L-L clusters in the northern urban agglomerations,the narrowed regional differences,and increasing coordination within each urban agglomeration.Fourthly,the geographical detector found that economy,urbanization and the human capital were significant external factors that affected urban health development.The explanatory power of technological innovation and opening to the outside world were also increasing.The development of healthy cities is yet to be transformed into regional health integration.展开更多
基金financially supported by the National Natural Science Foundation of China(No.52204284)the China Postdoctoral Science Foundation(No.2025MD784125)+2 种基金the Natural Science Foundation of Shaanxi Province,China(No.2024JC-YBQN-0365)the Shaanxi Province Postdoctoral Science Foundation,China(No.2025BSHSDZZ363)Outstanding Youth Science Fund of Xi’an University of Science and Technology,China(No.202308)。
文摘Interfacial interactions between rough mineral particles have garnered considerable attention as they directly determine particle agglomeration and floatability.This study comprehensively investigates the agglomeration characteristics of siderite particles after argon(Ar)plasma surface modification through settling tests,flocs size measurements,and fractal dimension calculations.Ar plasma surface modification promotes the agglomeration of siderite particles,as evidenced by increased floc size and density.The agglomeration mechanism induced by Ar plasma surface modification is evaluated using a theoretical model combining the surface element integration(SEI)approach,differential geometry,and the composite Simpson's rule.Changes in surface roughness,wettability,and charge are considered in this model.Compared to the unpretreated siderite particles,the energy barrier for interaction of the 30-min Ar plasma-pretreated siderite particles decreases from 2.3×10-^(17)J to 1.6×10^(-17)J.This reduction provides strong evidence for the agglomeration behavior of siderite particles.Furthermore,flotation experiments confirm that Ar plasma surface modification is conducive to the aggregation flotation of siderite.These findings offer crucial insights into particle aggregation and dispersion behaviors,with notable application in mineral flotation.
基金the Special Fund for the National Natural Science Foundation of China(U1608254)the National Key R&D Program of China(2018YFC1902002).
文摘The effect of mechanical activation on the granulometric parameters,microstructure,and leaching efficiency of chalcopyrite was evaluated,and the occurrence/transition of agglomeration and aggregation was discussed.The results showed that in 8 h of milling treatment,the agglomeration and the microstructure did not affect each other.However,with prolonging milling time,the crystallite size tended to reach a saturation value,and the stagnating microstructural changes led to the replacement of agglomeration by aggregation.The leaching results indicated that the mechanical activation can strongly enhance the reactivity of chalcopyrite and the hindering effect of aggregation on leaching was considerably greater than that of agglomeration.Consequently,after 8 h of milling,the maximum Cu leaching rate of 80.13%was achieved after 4 h of acid leaching.
文摘The monomer agglomeration of nonmetallic inclusions was simulated with a diffusion limited aggregation （DLA） model of the fractal theory. The simulation study with a random two-dimensional diffusion was carried out. The results indicate that the DLA model can be used for the simulation of agglomeration behavior of the cluster-type inclusions. The morphology of clusters was observed with SEM and compared with the simulated agglomerates. The modelling procedure of the DLA model is applicable for the agglomeration process. The uncertainty of agglomeration process and the persuasive average agglomerative ratio was analyzed. The factors about the agglomerative ratio with the collision path distance and the size of particles or seed were discussed. The adherence of the nonmetallic inclusions on the dam, the weir and the walls of a tundish, and the absorption of inclusions by stopper or nozzle were also discussed.
文摘Patna is among the cities high populated at risk of ecological and environmental deterioration due to a variety of human activities,such as poor land cover management.One of the most crucial elements of a successful land resource management plan is the evaluation of Land Use Land Cover(LULC).Over the past 20 years,our planet’s land cover resources have undergone substantial changes due to rapid development.The Land Use Land Cover(LULC)categories of the Patna Urban Agglomeration(PUA),including water bodies,agricultural land,barren land,built-up areas,and vegetation,were identified using Geographic Information System(GIS)techniques.Three multi-temporal images were analyzed and classified through supervised classification using the maximum likelihood method.By comparing three separately created LULC categorized maps from 1990 and 2024,temporal changes were analyzed.In order to update land cover or manage natural resources,it is vital to use change detection as a tool to identify changes in LULC over time in PUA,Patna between 1990,2010 and 2024.According to their respective Kappa coefficients,the accuracy rates for 1990,2010 and 2024 LULC are 91.66 and 94.93,respectively.An accuracy evaluation was conducted to determine the correctness of the classification system and to determine the efficacy of the LULC classification maps.One hundred reference test pixels were identified.There have been found significant changes in the LULC were built up area has increased doubled in last thirty-four years of timeline.
基金Supported by the National Natural Science Foundation of China(21376269)the Hunan Provincial Science and Technology Plan Project,China(2016TP1007)
文摘In this study, the influence of fluid cracking catalyst(FCC) on the fluidization behavior of ZnO-CuO binary nanoparticles was systematically investigated by varying FCC size. High-speed camera was employed to analyze the collision and fragmentation process of agglomerates with adding FCC coarse particles. It can be found from photographs by the camera that fluidization performance improved by the agglomerate variation that is bound to be shaped a compact and spherical structure. Furthermore, the result of agglomeration composition analysis showed that uniform mixing of nanoparticles remarkably affected the fluidization behavior of ZnO-CuO binary system. Finally, the improvement of fluidization performance can be justified by the analysis of inter-cohesive force between the two agglomerates with sharp reduction of the newly-formed agglomerates.
基金supported by the Humanities and Social Sciences Project of the Ministry of Education of the Peoples Republic(No.21YJCZH099)the National Natural Science Foundation of China(Nos.41401089 and 41741014)the Science and Technology Project of Sichuan Province(No.2023NSFSC1979).
文摘Majority of carbon emissions originate from fossil energy consumption,thus necessitating calculation and monitoring of carbon emissions from energy consumption.In this study,we utilized energy consumption data from Sichuan Province and Chongqing Municipality for the years 2000 to 2019 to estimate their statistical carbon emissions.We then employed nighttime light data to downscale and infer the spatial distribution of carbon emissions at the county level within the Chengdu-Chongqing urban agglomeration.Furthermore,we analyzed the spatial pattern of carbon emissions at the county level using the coefficient of variation and spatial autocorrelation,and we used the Geographically and Temporally Weighted Regression(GTWR)model to analyze the influencing factors of carbon emissions at this scale.The results of this study are as follows:(1)from 2000 to 2019,the overall carbon emissions in the Chengdu-Chongqing urban agglomeration showed an increasing trend followed by a decrease,with an average annual growth rate of 4.24%.However,in recent years,it has stabilized,and 2012 was the peak year for carbon emissions in the Chengdu-Chongqing urban agglomeration;(2)carbon emissions exhibited significant spatial clustering,with high-high clustering observed in the core urban areas of Chengdu and Chongqing and low-low clustering in the southern counties of the Chengdu-Chongqing urban agglomeration;(3)factors such as GDP,population(Pop),urbanization rate(Ur),and industrialization structure(Ic)all showed a significant influence on carbon emissions;(4)the spatial heterogeneity of each influencing factor was evident.
文摘Neurons are highly polarized cells with axons reaching over a meter long in adult humans.To survive and maintain their proper function,neurons depend on specific mechanisms that regulate spatiotemporal signaling and metabolic events,which need to be carried out at the right place,time,and intensity.Such mechanisms include axonal transport,local synthesis,and liquid-liquid phase separations.Alterations and malfunctions in these processes are correlated to neurodegenerative diseases such as amyotrophic lateral sclerosis(ALS).
基金supported by the National Natural Science Foundation of China(Nos.12072027,62103052,61603346 and 62103379)the Henan Key Laboratory of General Aviation Technology,China(No.ZHKF-230201)+3 种基金the Funding for the Open Research Project of the Rotor Aerodynamics Key Laboratory,China(No.RAL20200101)the Key Research and Development Program of Henan Province,China(Nos.241111222000 and 241111222900)the Key Science and Technology Program of Henan Province,China(No.232102220067)the Scholarship Funding from the China Scholarship Council(No.202206030079).
文摘In global navigation satellite system denial environment,cross-view geo-localization based on image retrieval presents an exceedingly critical visual localization solution for Unmanned Aerial Vehicle(UAV)systems.The essence of cross-view geo-localization resides in matching images containing the same geographical targets from disparate platforms,such as UAV-view and satellite-view images.However,images of the same geographical targets may suffer from occlusions and geometric distortions due to variations in the capturing platform,view,and timing.The existing methods predominantly extract features by segmenting feature maps,which overlook the holistic semantic distribution and structural information of objects,resulting in loss of image information.To address these challenges,dilated neighborhood attention Transformer is employed as the feature extraction backbone,and Multi-feature representations based on Multi-scale Hierarchical Contextual Aggregation(MMHCA)is proposed.In the proposed MMHCA method,the multiscale hierarchical contextual aggregation method is utilized to extract contextual information from local to global across various granularity levels,establishing feature associations of contextual information with global and local information in the image.Subsequently,the multi-feature representations method is utilized to obtain rich discriminative feature information,bolstering the robustness of model in scenarios characterized by positional shifts,varying distances,and scale ambiguities.Comprehensive experiments conducted on the extensively utilized University-1652 and SUES-200 benchmarks indicate that the MMHCA method surpasses the existing techniques.showing outstanding results in UAV localization and navigation.
基金supported by Jiangsu Provincial Science and Technology Project,grant number J2023124.Jing Guo received this grant,the URLs of sponsors’website is https://kxjst.jiangsu.gov.cn/(accessed on 06 June 2024).
文摘The rapid proliferation of electric vehicle(EV)charging infrastructure introduces critical cybersecurity vulnerabilities to power grids system.This study presents an innovative anomaly detection framework for EV charging stations,addressing the unique challenges posed by third-party aggregation platforms.Our approach integrates node equations-based on the parameter identification with a novel deep learning model,xDeepCIN,to detect abnormal data reporting indicative of aggregation attacks.We employ a graph-theoretic approach to model EV charging networks and utilize Markov Chain Monte Carlo techniques for accurate parameter estimation.The xDeepCIN model,incorporating a Compressed Interaction Network,has the ability to capture complex feature interactions in sparse,high-dimensional charging data.Experimental results on both proprietary and public datasets demonstrate significant improvements in anomaly detection performance,with F1-scores increasing by up to 32.3%for specific anomaly types compared to traditional methods,such as wide&deep and DeepFM(Factorization-Machine).Our framework exhibits robust scalability,effectively handling networks ranging from 8 to 85 charging points.Furthermore,we achieve real-time monitoring capabilities,with parameter identification completing within seconds for networks up to 1000 nodes.This research contributes to enhancing the security and reliability of renewable energy systems against evolving cyber threats,offering a comprehensive solution for safeguarding the rapidly expanding EV charging infrastructure.
基金supported by the National Key R&D Program of China(No.2023YFB2703700)the National Natural Science Foundation of China(Nos.U21A20465,62302457,62402444,62172292)+4 种基金the Fundamental Research Funds of Zhejiang Sci-Tech University(Nos.23222092-Y,22222266-Y)the Program for Leading Innovative Research Team of Zhejiang Province(No.2023R01001)the Zhejiang Provincial Natural Science Foundation of China(Nos.LQ24F020008,LQ24F020012)the Foundation of State Key Laboratory of Public Big Data(No.[2022]417)the“Pioneer”and“Leading Goose”R&D Program of Zhejiang(No.2023C01119).
文摘As smart grid technology rapidly advances,the vast amount of user data collected by smart meter presents significant challenges in data security and privacy protection.Current research emphasizes data security and user privacy concerns within smart grids.However,existing methods struggle with efficiency and security when processing large-scale data.Balancing efficient data processing with stringent privacy protection during data aggregation in smart grids remains an urgent challenge.This paper proposes an AI-based multi-type data aggregation method designed to enhance aggregation efficiency and security by standardizing and normalizing various data modalities.The approach optimizes data preprocessing,integrates Long Short-Term Memory(LSTM)networks for handling time-series data,and employs homomorphic encryption to safeguard user privacy.It also explores the application of Boneh Lynn Shacham(BLS)signatures for user authentication.The proposed scheme’s efficiency,security,and privacy protection capabilities are validated through rigorous security proofs and experimental analysis.
基金Under the auspices of the National Natural Science Foundation of China(No.52268008)。
文摘This study focuses on urgent research on restoring and enhancing carbon storage capacity in the Beibu Gulf Urban Agglomer-ation of China,a key area in the‘Belt and Road’Initiative,which aligns with carbon peaking and neutrality goals.This research ana-lyzes the spatial characteristics of carbon metabolism from 2000 to 2020 and uses models to identify stable carbon sink areas,positive carbon flow corridors,and carbon sequestration nodes.The goal is to construct a carbon metabolism spatial security pattern(CMSSP)and propose territorial ecological restoration strategies under different development demand scenarios.The results show the following:1)in 2020,the study area’s carbon sink decreased by 8.29×10^(4) t C/yr compared with that in 2010 and by 10.83×10^(4) t C/yr compared with that in 2000.High-carbon sinks were found mainly in mountainous areas,whereas low-carbon sinks are concentrated in urban con-struction land,rural residential areas,and land margins.2)From 2000 to 2020,the spatial security pattern of carbon metabolism tended to be‘high in the middle of the east and west and low in the gulf.’In 2000,2010,and 2020,16 stable carbon sinks were identified.The carbon energy flow density in Guangxi was greater than that in Guangdong and Hainan,with positive carbon flow corridors located primarily in Guangxi and Guangdong.The number of carbon sequestration nodes remained stable at approximately 15,mainly in Guangxi and Hainan.3)Scenario simulations revealed that under the Nature-based mild restoration scenario,the carbon sink rate will reach 611.85×10^(4) t C/yr by 2030 and increase to 612.45×10^(4) t C/yr by 2060,with stable carbon sinks increasing to 18.In the restora-tion scenario based on Anti-globalization,the carbon sink will decrease from 610.24×10^(4) t C/yr in 2030 to 605.19×10^(4) t C/yr in 2060,with the disappearance of some positive carbon flow corridors and stable carbon sinks.Under the Human-based sustainable restoration scenario,the carbon sink area will decrease from 607.00×10^(4) t C/yr in 2030 to 596.39×10^(4) t C/yr in 2060,with carbon sink areas frag-menting and positive carbon flow corridors becoming less dense.4)On the basis of the current and predicted CMSSPs,this study ex-plores spatial ecological restoration strategies for high-carbon storage areas in bay urban agglomerations at four levels:the land control region,urban agglomeration structure system,carbon sink structure and bay structure control region.
文摘Accurate medical diagnosis,which involves identifying diseases based on patient symptoms,is often hindered by uncertainties in data interpretation and retrieval.Advanced fuzzy set theories have emerged as effective tools to address these challenges.In this paper,new mathematical approaches for handling uncertainty in medical diagnosis are introduced using q-rung orthopair fuzzy sets(q-ROFS)and interval-valued q-rung orthopair fuzzy sets(IVq-ROFS).Three aggregation operators are proposed in our methodologies:the q-ROF weighted averaging(q-ROFWA),the q-ROF weighted geometric(q-ROFWG),and the q-ROF weighted neutrality averaging(qROFWNA),which enhance decision-making under uncertainty.These operators are paired with ranking methods such as the similarity measure,score function,and inverse score function to improve the accuracy of disease identification.Additionally,the impact of varying q-rung values is explored through a sensitivity analysis,extending the analysis beyond the typical maximum value of 3.The Basic Uncertain Information(BUI)method is employed to simulate expert opinions,and aggregation operators are used to combine these opinions in a group decisionmaking context.Our results provide a comprehensive comparison of methodologies,highlighting their strengths and limitations in diagnosing diseases based on uncertain patient data.
基金Under the auspices of Yunnan Provincial Science and Technology Project at Southwest United Graduate School(No.202302AO370012)National Natural Science Foundation of China(No.42201290)+1 种基金Talent Introduction Fund of Yunnan University(No.CZ22623101)the Fourteenth Program of Research Innovation Fund for Graduate Students of Yunnan University(No.KC-22221099)。
文摘Farmland transfer is an important land policy for reducing agricultural fragmentation and improving land use efficiency.Many studies have investigated the driving forces of farmland transfer at the farmers’scale.However,the overall spatial distribution and driving mechanisms of farmland transfer at the county scale has been less quantified.In this study,we evaluated farmland transfer and its spatial pattern in Central Yunnan Urban Agglomeration(CYUA)of China by using statistical data at the county scale in 2020.A so-cial-ecological indicator system,comprising natural endowment,social indicators,economic indicators,and landscape patterns,was es-tablished to explore the relationship between farmland transfer and its driving factors.Additionally,a heuristic structural equation mod-el(SEM)was employed to disentangle direct and indirect drivers of farmland transfer.The results indicated that significant spatial clusters of farmland transfer,with high transfer rates concentrated in highly urbanized areas and low transfer rates prevalent in tradition-al ethnic minority regions.Farmland transfer is primarily driven by soil quality,landscape patterns,terrain,and social-economic rurality.Specifically,higher soil quality and improved landscape connectivity facilitate farmland transfer directly,while gentler slopes promote farmland transfer indirectly by supporting better educational opportunities and fewer minority population.Improving rural vocational training and optimizing landscape patterns through land consolidation and redistribution are important in the mountainous areas.This study can provide valuable analytical framework for farmland management for other mountainous regions.
基金supported by the Innovation and Technology Commission (ITCPD/17-9)the Hong Kong Research Grants Council,China (GRF16104517)(to KKKC)。
文摘Parkinson's disease (PD) is a common degenerative disorder that is becoming increasingly prevalent because of the global aging population.The exact cause of the disorder is unknown;however,recent studies have suggested that multiple factors may contribute to its pathogenesis.PD is characterized by a movement disorder that primarily affects motor control;pathologically,the disease is marked by the presence of Lewy bodies (LBs) in the brain.
基金support of Postdoctoral Fellowship Program of CPSF(GZC20230393)Natural Science Foundation of Liaoning Province in China(2023-BSBA-112)Fundamental Research Funds for the Central Universities(N2425032).
文摘The formation of large-sized inclusions cluster severely impacts the continuous casting process and product quality of titanium-containing steel.Thermodynamic calculations were initially conducted to predict the formation of various complex oxide inclusions,namely Al_(2)O_(3),TiO_(x)and Al-Ti-O.Based on that,laboratory-scale experiments were designed to prepare samples with a single type of inclusions.Then,the scanning electron microscope-energy dispersive spectrometer was used for quantitative characterization.Subsequently,the agglomeration behavior of inclusions in Fe-Al-Ti-O melt was observed in situ by high-temperature confocal laser scanning microscopy.Furthermore,a quantitative analysis of the agglomeration characteristics of the various inclusions was conducted based on the attractive forces in accordance with Newton's second law and the capillary forces as described by the Kralchevsky-Paunov model.The results indicate that the size of Al_(2)O_(3)inclusions is larger than that of TiO_(x)and Al-Ti-O,but the number density of TiO_(x)is the highest.Based on the in situ observation and the theoretical calculation,Al_(2)O_(3),TiO_(x)and Al-Ti-O inclusions can all agglomerate into large-sized clusters without segregation,but the agglomeration tendency of Al_(2)O_(3)and TiO_(x)is stronger than that of Al-Ti-O.The attractive force between Al_(2)O_(3)inclusions’pair is the largest,ranging from 2.26×10^(-15)to 6.12×10^(-14)N,followed by TiO_(x)(7.13×10^(-16)to 3.56×10^(-14)N)and Al-Ti-O(1.16×10^(-17)to 3.77×10^(-16)N).
基金National Natural Science Foundation of China(Nos.U21A20116,U21A20117 and 52304347)National Natural Science Foundation of Liaoning(Nos.2023-MSBA-135 and 2023-BSBA-107)+1 种基金the Fundamental Research Funds for the Central Universities(Nos.N2409006 and N2409008)are acknowledged to support this workSwedish Foundation for International Cooperation in Research and Higher Education(STINT,Project No.IB2022-9228)is acknowledged by W.Mu to support his visit between KTH(Sweden)and NEU(China).
文摘Understanding the motion behaviors of non-metallic inclusions in the liquid metal is important for clean steel production.High-temperature confocal laser scanning microscopy is applied to investigate the effect of different Ti and Al contents on the agglomeration behavior of non-metallic inclusions in low carbon steels.Furthermore,the agglomeration mechanism of inclusions was investigated through quantitative analysis of in-situ observation experiments and a modified Kralchevsky-Paunov model.The obtained results indicate that Al_(2)O_(3)is the main type inclusion in the low-alloys steels with both Al and Ti addition.This type of inclusion is more likely to absorb surrounding small-size inclusion particles,leading to a further growth for the cluster formation and contributing to a serious engineering problem,nozzle clogging.Besides,TiO_(x)is the main type inclusion in the molten steel with only Ti addition,and this type of inclusion is less likely to agglomerate and the individual inclusion particles show a‘free’motion with the fluid of molten steel.The difference between these two types of inclusions is due to the difference in attractive force and action distance at the meniscus created by the inclusion/steel/Ar multiple interfaces and influenced by the physical parameters,e.g.,contact angle and interface energy between inclusion and steel,and surface tension of the melt.
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(No.NRF-2022R1C1C2012463).
文摘Integrating Artificial Intelligence of Things(AIoT)in healthcare offers transformative potential for real-time diagnostics and collaborative learning but presents critical challenges,including privacy preservation,computational efficiency,and regulatory compliance.Traditional approaches,such as differential privacy,homomorphic encryption,and secure multi-party computation,often fail to balance performance and privacy,rendering them unsuitable for resource-constrained healthcare AIoT environments.This paper introduces LMSA(Lightweight Multi-Key Secure Aggregation),a novel framework designed to address these challenges and enable efficient,secure federated learning across distributed healthcare institutions.LMSA incorporates three key innovations:(1)a lightweight multikey management system leveraging Diffie-Hellman key exchange and SHA3-256 hashing,achieving O(n)complexity with AES(Advanced Encryption Standard)-256-level security;(2)a privacy-preserving aggregation protocol employing hardware-accelerated AES-CTR(CounTeR)encryption andmodular arithmetic for securemodel weight combination;and(3)a resource-optimized implementation utilizing AES-NI(New Instructions)instructions and efficient memory management for real-time operations on constrained devices.Experimental evaluations using the National Institutes of Health(NIH)Chest X-ray dataset demonstrate LMSA’s ability to train multi-label thoracic disease prediction models with Vision Transformer(ViT),ResNet-50,and MobileNet architectures across distributed healthcare institutions.Memory usage analysis confirmed minimal overhead,with ViT(327.30 MB),ResNet-50(89.87 MB),and MobileNet(8.63 MB)maintaining stable encryption times across communication rounds.LMSA ensures robust security through hardware acceleration,enabling real-time diagnostics without compromising patient confidentiality or regulatory compliance.Future research aims to optimize LMSA for ultra-low-power devices and validate its scalability in heterogeneous,real-world environments.LMSA represents a foundational advancement for privacy-conscious healthcare AI applications,bridging the gap between privacy and performance.
基金supported by the National Social Science Founda‐tion of China[Grant No.20&ZD100]the Shandong Province Key Research and Development Program(Soft Science)Major Project[Grant No.2024RZA0101].
文摘In the context of China’ s dual carbon goals, transforming traditional manufacturing agglomeration into green manufacturing agglomeration is pivotal in aligning economic development with environmental protection, ultimately contributing to the country’ s high-quality economic growth. This study examines the dynamic nonlinear effects of manufacturing agglomeration on economic development, energy consumption, environmental pollution, and green total factor productivity. We developed a theoretical framework that considered local government constraints and incentives as transition variables and employed panel data from 280 cities at or above the prefecture level in China from 2006 to 2020 using a Panel Smooth Transition Regression model. The results reveal that, first, under both constraints and incentives, a single threshold effect exists beyond which the positive impact of manufacturing agglomeration on economic development, energy consumption, and environmental pollution gradually weakens. Second, the spatiotemporal evolution of manufacturing agglomeration shows that traditional manufacturing agglomerations are gradually spreading from the central and western regions to the resourcebased regions in the eastern part of the country, while green manufacturing agglomerations are shrinking annually. Third, a comparative analysis indicates that, in both developed and developing countries, manufacturing agglomeration effects are strongest when government constraints do not exceed the threshold. However, in developing countries, when this threshold is surpassed, the momentum for green transformation becomes insufficient. Finally, digital infrastructure positively promotes the green transformation of manufacturing agglomerations, although its effects are influenced by other factors.
基金supported by the National Natural Science Foundation of China(Nos.U2241250 and U2441284)。
文摘AP(Ammonium Perchlorate)and HMX(Octogen)are the two oxidizers most often used in Nitrate-Ester-Plasticized Polyether(NEPE)rocket propellants.How the AP–HMX ratio influences the agglomeration of NEPE propellants remains unclear.We experimentally investigated the effect of the AP–HMX ratio on the combustion and agglomeration of NEPE propellants using burning rate test,quenched surface analysis,microscopic observations,and the collection of condensed combustion products.It was found that with the decrease in AP content from 40wt%to 10wt%,the burning rate decreased from 14.2 mm/s to 9.2 mm/s because the adiabatic flame temperature of NEPE propellants decreased from 3828 K to 3736 K.Pockets bounded by AP particles appeared on the surface when AP content was 40wt%;however,the accumulations grew and covered the burning surface eventually as the AP–HMX ratio decreased.The time required for the accumulation to coalesce into agglomerates increased with decreasing AP content.Even with similar agglomerate sizes,the coalescence time increased by 83%when the AP content decreased from 40wt%to 30wt%.The agglomerate size in the Condensed Combustion Products(CCPs)increased from 100μm to 200μm,and the fraction of large agglomerations increased from 6.4%to 24.7%when the AP content decreased from 40wt%to 10wt%.Overall,the high flame temperature of the AP particles enhanced the decomposition of the surrounding binder,resulting in the rapid ejection of the aluminum particles into the gas,which had a separating effect on the accumulation,thus weakening the agglomeration.
基金National Natural Science Foundation of China,No.42171216,No.71733001Key R&D Program of Beijing Municipal Education Commission,No.KZ202210038047Tsinghua University Initiative Scientific Research Program,No.2022THZWJC15。
文摘Research on urban health constitutes an important issue in the field of health geography and also a strong propeller of the Healthy China Initiative.As the main form that realizes new-type urbanization,urban agglomerations should become the primal sites for the construction of a“Healthy China”.The evaluation of healthy cities’development in urban agglomerations has both theoretical and practical values.Based on the concept of urban health and its evaluation models,this paper developed an evaluation framework for healthy cities that involved multiple data sources.With 19 urban agglomerations in China as the research subjects,we used CRITIC weighting and geographical detectors to examine the geographies of healthy cities and their influencing factors in 2010 and 2020.The results were fourfold.Firstly,the urban health level of China significantly increased from 2010 to 2020,and the comprehensive health index developed towards a positive skewed distribution,along with a shift from“low in the hinterland-high in the coastal areas”to a“multipolar”pattern led by the coastal and southwest urban agglomerations.Secondly,among various dimensions of urban health,the healthy environment index became improved with narrowed regional differences;while the health services index was still polarized;health collaboration was upgraded with a strengthened intercity health network;the healthy population index slightly declined and converged to the middle.Thirdly,urban health in China has initially demonstrated the characteristics of a H-H pattern in the Yangtze River Delta and ChengduChongqing regions,as well as L-L clusters in the northern urban agglomerations,the narrowed regional differences,and increasing coordination within each urban agglomeration.Fourthly,the geographical detector found that economy,urbanization and the human capital were significant external factors that affected urban health development.The explanatory power of technological innovation and opening to the outside world were also increasing.The development of healthy cities is yet to be transformed into regional health integration.
