Owing to intensified globalization and informatization,the structures of the urban scale hierarchy and urban networks between cities have become increasingly intertwined,resulting in different spatial effects.Therefor...Owing to intensified globalization and informatization,the structures of the urban scale hierarchy and urban networks between cities have become increasingly intertwined,resulting in different spatial effects.Therefore,this paper analyzes the spatial interaction between urban scale hierarchy and urban networks in China from 2019 to 2023,drawing on Baidu migration data and employing a spatial simultaneous equation model.The results reveal a significant positive spatial correlation between cities with higher hierarchy and those with greater network centrality.Within a static framework,we identify a positive interaction between urban scale hierarchy and urban network centrality,while their spatial cross-effects manifest as negative neighborhood interactions based on geographical distance and positive cross-scale interactions shaped by network connections.Within a dynamic framework,changes in urban scale hierarchy and urban networks are mutually reinforcing,thereby widening disparities within the urban hierarchy.Furthermore,an increase in a city’s network centrality had a dampening effect on the population growth of neighboring cities and network-connected cities.This study enhances understanding of the spatial organisation of urban systems and offers insights for coordinated regional development.展开更多
The suppression of ablative Rayleigh–Taylor instability(ARTI)by a spatially modulated laser in inertial confinement fusion(ICF)is studied through numerical simulations.The results show that in the acceleration phase ...The suppression of ablative Rayleigh–Taylor instability(ARTI)by a spatially modulated laser in inertial confinement fusion(ICF)is studied through numerical simulations.The results show that in the acceleration phase of ICF implosion,the growth of ARTI can be suppressed by using a short-wavelength spatially modulated laser.The ARTI growth rate decreases as the wavelength of the spatially modulated laser decreases,and ARTI is completely suppressed after a certain wavelength has been reached.A spatially uniform laser is introduced to keep the state of motion of the implosion fluid consistent,and it is found that the proportion of the spatially modulated laser required for complete suppression of ARTI decreases as the wavelength continues to decrease.We also optimize the spatial intensity distribution of the spatially modulated laser.In addition,as the duration of the spatially modulated laser decreases,the proportion required for completely suppressing ARTI increases,but the required energy decreases.When the perturbation wavenumber decreases,the wavelength of the spatially modulated laser required for complete suppression of ARTI becomes longer.In the case of multimode perturbation,ARTI can also be significantly suppressed by a spatially modulated laser,and the perturbation amplitude can be reduced to less than 10% of that without a spatially modulated laser.We believe that the conclusions drawn from our simulations can provide the basis for new approaches to control ARTI in ICF.展开更多
Alzheimer’s disease(AD)is the most common form of dementia.In addition to the lack of effective treatments,there are limitations in diagnostic capabilities.The complexity of AD itself,together with a variety of other...Alzheimer’s disease(AD)is the most common form of dementia.In addition to the lack of effective treatments,there are limitations in diagnostic capabilities.The complexity of AD itself,together with a variety of other diseases often observed in a patient’s history in addition to their AD diagnosis,make deciphering the molecular mechanisms that underlie AD,even more important.Large datasets of single-cell RNA sequencing,single-nucleus RNA-sequencing(snRNA-seq),and spatial transcriptomics(ST)have become essential in guiding and supporting new investigations into the cellular and regional susceptibility of AD.However,with unique technology,software,and larger databases emerging;a lack of integration of these data can contribute to ineffective use of valuable knowledge.Importantly,there was no specialized database that concentrates on ST in AD that offers comprehensive differential analyses under various conditions,such as sex-specific,region-specific,and comparisons between AD and control groups until the new Single-cell and Spatial RNA-seq databasE for Alzheimer’s Disease(ssREAD)database(Wang et al.,2024)was introduced to meet the scientific community’s growing demand for comprehensive,integrated,and accessible data analysis.展开更多
While conventional FISH and IHC methods struggle to decode complex tissue heterogeneity and comprehensive molecular diagnosis due to low-throughput spatial information,spatial omics technologies enable high-throughput...While conventional FISH and IHC methods struggle to decode complex tissue heterogeneity and comprehensive molecular diagnosis due to low-throughput spatial information,spatial omics technologies enable high-throughput molecular mapping across tissue microenvironments.These technologies are emerging as transformative tools in molecular diagnostics and medical research.By integrating histopathological morphology with spatial multi-omics profiling(genome,transcriptome,epigenome,and proteome),spatial omics technologies open an avenue for understanding disease progression,therapeutic resistance mechanisms,and precise diagnosis.It particularly enhances tumor microenvironment analysis by mapping immune cell distributions and functional states,which may greatly facilitate tumor molecular subtyping,prognostic assessment,and prediction of the radiotherapy and chemotherapy efficacy.Despite the substantial advancements in spatial omics,the translation of spatial omics into clinical applications remains challenging due to robustness,efficacy,clinical validation,and cost constraints.In this review,we summarize the current progress and prospects of spatial omics technologies,particularly in medical research and diagnostic applications.展开更多
Excessive blasting-induced vibration during drilling-and-blasting excavation of deep tunnels can trigger geological hazards and compromise the stability of both the rock mass and support structures.This study focused ...Excessive blasting-induced vibration during drilling-and-blasting excavation of deep tunnels can trigger geological hazards and compromise the stability of both the rock mass and support structures.This study focused on the deep double-line Sejila Mountain tunnel to systematically analyze the spatial response of blasting-induced vibration and to develop a prediction model through field tests and numerical simulations.The results revealed that the presence of a cross passage significantly altered propagation paths and the spatial distribution of blasting-induced vibration velocity.The peak particle velocity(PPV)at the cross-passage corner was amplified by approximately 1.92 times due to wave reflection and geometric focusing.Blasting-induced vibration waves attenuated non-uniformly across the tunnel cross-section,where PPV on the blast-face side was 1.54–6.56 times higher than that on the opposite side.We propose an improved PPV attenuation model that accounts for the propagation path effect.This model significantly improved fitting accuracy and resolved anomalous parameter(k and a)estimates in traditional equations,thereby improving prediction reliability.Furthermore,based on the observed spatial distribution of blasting-induced vibration,optimal monitoring point placement and targeted vibration control measures for tunnel blasting were discussed.These findings provide a scientific basis for designing blasting schemes and vibration mitigation strategies in deep tunnels.展开更多
The brain's functions are governed by molecular metabolic networks.However,due to the sophisticated spatial organization and diverse activities of the brain,characterizing both the minute and large-scale metabolic...The brain's functions are governed by molecular metabolic networks.However,due to the sophisticated spatial organization and diverse activities of the brain,characterizing both the minute and large-scale metabolic activity across the entire brain and its numerous micro-regions remains incredibly challenging.Here,we offer a high-definition spatially resolved metabolomics technique to better understand the metabolic specialization and interconnection throughout the mouse brain using improved ambient mass spectrometry imaging.This method allows for the simultaneous mapping of thousands of metabolites at a 30 μm spatial resolution across the mouse brain,ranging from structural lipids to functional neurotransmitters.This approach effectively reveals the distribution patterns of delicate microregions and their distinctive metabolic characteristics.Using an integrated database,we annotated 259 metabolites,demonstrating that the metabolome and metabolic pathways are unique to each brain microregion.The distribution of metabolites,closely linked to functionally connected brain regions and their interactions,offers profound insights into the complexity of chemical processes and their roles in brain function.An initial dataset for future metabolomics research might be obtained from the high-definition mouse brain's spatial metabolome atlas.展开更多
Urban spatial morphology(USM)optimization is critical to balancing biodiversity conservation and sustainable urbanization.However,previous studies predominantly focused on the socio-economic efficiency and static ecol...Urban spatial morphology(USM)optimization is critical to balancing biodiversity conservation and sustainable urbanization.However,previous studies predominantly focused on the socio-economic efficiency and static ecological metrics and rarely addressed the dynamic USM optimization across spatial scales.Here,we developed a multi-level ecological network(MEN)framework to resolve the tension between urban expansion and ecological integrity.By integrating the cost-weighted distance analysis with a hierarchical network transmission mechanism,we established a cross-scale spatial optimization system,which coordinated the regional ecological corridors and local habitat patches.Comparative experiments with conventional single-scale approaches and scenario simulations using the PLUS model show that the MEN framework had superior performance in three dimensions:(1)spatial governance:the primary-level network(peri-urban natural reserves)effectively contained urban sprawl,and the secondary-level network(intra-urban green corridors)mitigated habitat fragmentation and improved the built-environment;(2)scenario robustness:the model maintained an optimal compactness-loose balance in multiple development pathways;(3)landscape metrics:patch fragmentation decreased by 18.25%,and the internal landscape richness improved by 10.66%compared to the scenario without USM optimization.The findings provide new insight to establish a hierarchical ecological optimization framework as a nature-based spatial protocol to reconcile metropolitan growth with landscape sustainability.展开更多
Sluggish kinetics coupled with parasitic shuttling reactions are pivotal challenges hindering the performance of lithium-sulfur(Li-S)batteries.Improving areal capacity and cyclability of Li-S batteries can be achieved...Sluggish kinetics coupled with parasitic shuttling reactions are pivotal challenges hindering the performance of lithium-sulfur(Li-S)batteries.Improving areal capacity and cyclability of Li-S batteries can be achieved by addressing these challenges.A composite sulfur host material is synthesized herein by in situ anchoring ultrafine cobalt-iron phosphide nanoparticles(5-7 nm)onto a hollow mesoporous carbon sphere(HMCS)framework.This strategy achieved exceptional spatial restriction and a high density of catalytically active sites through the encapsulation of sulfur within a hollow-structured framework.Specifically,HMCS expedites rapid Li_(2)S nucleation kinetics,while CoFeP facilitates robust Li_(2)S dissolution kinetics by mitigating decomposition barriers.This synergistic integration equips CoFeP@HMCS with robust bi-directional catalytic activity,significantly promoting interracial charge-transfer,facilitate sulfu r multistep catalytic conversion,and inhibiting shuttling.Consequently,the battery exhibits excellent rate performance(991 mA h g^(-1) at 5.0 C)and retains a high areal capacity of 6.06 mA h cm^(-2) after 200 cycles under a high areal sulfur loading of 8.2 mg cm^(-2) but a low electrolyte/sulfur ratio of 4.8μL mg^(-1).This work contributes to enhancing the practical specific capacity of lithium-sulfur batteries and deepens the understanding of catalysts enabling bidirectional electrocatalytic sulfur conversion.展开更多
The spatial offset of bridge has a significant impact on the safety,comfort,and durability of high-speed railway(HSR)operations,so it is crucial to rapidly and effectively detect the spatial offset of operational HSR ...The spatial offset of bridge has a significant impact on the safety,comfort,and durability of high-speed railway(HSR)operations,so it is crucial to rapidly and effectively detect the spatial offset of operational HSR bridges.Drive-by monitoring of bridge uneven settlement demonstrates significant potential due to its practicality,cost-effectiveness,and efficiency.However,existing drive-by methods for detecting bridge offset have limitations such as reliance on a single data source,low detection accuracy,and the inability to identify lateral deformations of bridges.This paper proposes a novel drive-by inspection method for spatial offset of HSR bridge based on multi-source data fusion of comprehensive inspection train.Firstly,dung beetle optimizer-variational mode decomposition was employed to achieve adaptive decomposition of non-stationary dynamic signals,and explore the hidden temporal relationships in the data.Subsequently,a long short-term memory neural network was developed to achieve feature fusion of multi-source signal and accurate prediction of spatial settlement of HSR bridge.A dataset of track irregularities and CRH380A high-speed train responses was generated using a 3D train-track-bridge interaction model,and the accuracy and effectiveness of the proposed hybrid deep learning model were numerically validated.Finally,the reliability of the proposed drive-by inspection method was further validated by analyzing the actual measurement data obtained from comprehensive inspection train.The research findings indicate that the proposed approach enables rapid and accurate detection of spatial offset in HSR bridge,ensuring the long-term operational safety of HSR bridges.展开更多
Ensuring national food security amidst rapid population growth and increasing extreme weather events remains a critical global challenge.However,the extent to which agricultural modernization in China enhances grain y...Ensuring national food security amidst rapid population growth and increasing extreme weather events remains a critical global challenge.However,the extent to which agricultural modernization in China enhances grain yield and contributes to food security remains unclear.Therefore,using panel data from 327 Chinese cities(2013–2021),this study employs spatial econometric models to analyze the spatial spillover effects of agricultural modernization level(AML)on grain yield and to reveal regional heterogeneity across nine major agricultural zones.The results showed a cumulative grain yield increase of 23.7 million tons,with peak productivity concentrated along the Hu Line and declining eastward and westward.AML also exhibited a steady increase but a clear spatial gradient,decreasing from coastal to inland regions,with the highest level observed in Southern China(SC).A key finding was that a 1%increase in AML directly raised local grain yield by an average of 4.185%,accompanied by significant positive spillover effects on neighboring regions.Regional variations revealed distinct patterns:the direct effects of AML were more pronounced in southern and eastern zones,while spillover effects dominated in northern and western zones.The largest positive direct impact of AML on grain yield was observed in the SC(8.499%),while Middle-Lower Yangtze Plain ranked second but exhibited the strongest positive spatial spillover effect(4.534%).These findings highlight the critical role of agricultural modernization in promoting grain production and provide a solid basis for optimizing regional agricultural systems,ensuring food security,and advancing sustainable agriculture.展开更多
Successful ex situ conservation of plant populations requires a high degree of genetic representativeness.However,spatially biased sampling in ex situ conservation efforts may fail to capture all wild genetic clusters...Successful ex situ conservation of plant populations requires a high degree of genetic representativeness.However,spatially biased sampling in ex situ conservation efforts may fail to capture all wild genetic clusters for species with range-wide genetic structure.To investigate the extent of spatially biased sampling in living collections and the coverage of wild genetic clusters in plant populations under ex situ conservation worldwide,we combined a global synthesis of ex situ conservation efforts with a case study of an endangered riparian plant species,Myricaria laxiflora.Our analysis of ex situ conservation worldwide revealed that the majority(82.6%)of ex situ populations fail to cover all wild genetic clusters,largely due to spatially biased sampling with low geographic coverage.Our case study of M.laxiflora showed that genetic diversity differed between the ex situ and upstream populations,while it was comparable between ex situ populations and other wild populations.However,current ex situ populations did not cover all wild genetic clusters,as the upstream genetic cluster was previously uncollected.Our study suggests that the failure to cover all wild genetic clusters in ex situ populations is a widespread issue,and ex situ populations with high genetic diversity can also fail to cover all wild genetic clusters.In future ex situ conservation programs,both the importance of high genetic diversity and the high coverage of wild genetic clusters should be prioritized.展开更多
To enhance the accuracy of short-term photovoltaic power output prediction and address issues such as insufficient spatial resolution of meteorological forecast data and weak generalization ability of models,this pape...To enhance the accuracy of short-term photovoltaic power output prediction and address issues such as insufficient spatial resolution of meteorological forecast data and weak generalization ability of models,this paper proposes a prediction method that integrates spatial downscaling meteorological data with a convolutional neural network(CNN)-iTransformer-long short-term memory(LSTM)model.First,the rime-optimized random forest regression algorithm(RIME-RF)is employed to perform spatial downscaling on numerical weather prediction(NWP)data,thereby improving its local applicability.Second,a CNN-iTransformer-LSTM hybrid prediction model is constructed.This model utilizes a CNN as a spatial feature extractor to capture local patterns in meteorological data,employs an iTransformer to model the global dependencies among multiple variables,and leverages an LSTM to enhance the learning of short-term temporal dynamic features,thereby achieving efficient collaborative mining of multi-scale features.Finally,experiments are conducted using actual data from a photovoltaic power station in Hebei,China,during various seasons and weather conditions.The results show that the proposed model outperforms the comparison models in terms of the root mean square error(RMSE),mean absolute error(MAE),and R2,maintaining high prediction accuracy and stability even under complex weather conditions such as overcast and rainy days.The downscaling process further enhances the prediction performance,verifying the effectiveness and practicality of this method.展开更多
The northern segment of the North-South Seismic Belt is characterized by intense crustal deformation,well-developed active tectonics,and frequent occurrences of strong earthquakes.Therefore,conducting a Probabilistic ...The northern segment of the North-South Seismic Belt is characterized by intense crustal deformation,well-developed active tectonics,and frequent occurrences of strong earthquakes.Therefore,conducting a Probabilistic Seismic Hazard Analysis(PSHA)for this region is of significant importance for supporting seismic fortification in major engineering projects and formulating disaster prevention and mitigation policies.In this study,a composite seismic source model was constructed by integrating data on historical earthquakes,active faults,and paleoseismicity.Furthermore,a logic tree framework was employed to quantify epistemic uncertainties,enabling a systematic seismic hazard assessment of the region.To more accurately characterize the spatial heterogeneity of seismic activity,improvements were made to both the Circular Spatial Smoothing Model(CSSM)with a fixed radius and the Adaptive Spatial Smoothing Model(ASSM),with full consideration given to the spatiotemporal completeness of historical earthquake magnitudes.Regarding the CSSM,for scenarios involving small sample sizes in earthquake catalogs,the cross-validation method proposed in this study demonstrated higher robustness than the maximum likelihood method in determining the optimal correlation distance.Performance evaluation results indicate that while both models effectively characterize seismic activity,the ASSM exhibits superior overall predictive performance compared to the CSSM,owing to its ability to adaptively adjust the smoothing radius according to seismic density.Significant discrepancies were observed in the Peak Ground Acceleration(PGA)results calculated with a 10%probability of exceedance in 50 years across different combinations of seismic source models.The single spatially smoothed point-source model yielded a maximum PGA of approximately 0.52 g,with high-value areas concentrated near historical epicenters,thereby significantly underestimating the hazard associated with major fault zones.When combined with the simple fault-source model,the maximum PGA increased to 0.8 g,with high-value zones exhibiting a zonal distribution along faults;however,the risk remained underestimated for faults with low slip rates that are nevertheless approaching their recurrence cycles.Following the introduction of the time-dependent characteristic fault-source model,local PGA values for faults in the middle-to-late stages of their recurrence cycles increased by a factor of 2 to 7 compared to the single model.These results demonstrate that the characteristic fault-source model reasonably delineates the time-dependence of large earthquake recurrence,thereby providing a more accurate assessment of imminent seismic risks.By comprehensively applying the improved spatially smoothed pointsource model,the simple fault-source model,and the characteristic fault-source model,the following faults within the region were identified as having high seismic hazard:the Huangxianggou,Zhangxian,and Tianshui segments of the Xiqinling northern edge fault;the Maqin-Maqu segment of the Dongkunlun fault;the Longriqu fault;the Maoergai fault;the Elashan fault;the Riyueshan fault;the eastern segment of the Lenglongling fault;the Maxianshan segment of the Maxianshan northern Margin fault;and the Maomaoshan-Jinqianghe segment of the Laohushan-Maomaoshan fault.As these faults are located within seismic gaps or are approaching the recurrence periods of large earthquakes,they should be prioritized for current and future seismic monitoring as well as disaster prevention and mitigation efforts.展开更多
Rapid urbanization in China has led to spatial antagonism between urban development and farmland protection and ecological security maintenance.Multi-objective spatial collaborative optimization is a powerful method f...Rapid urbanization in China has led to spatial antagonism between urban development and farmland protection and ecological security maintenance.Multi-objective spatial collaborative optimization is a powerful method for achieving sustainable regional development.Previous studies on multi-objective spatial optimization do not involve spatial corrections to simulation results based on the natural endowment of space resources.This study proposes an Ecological Security-Food Security-Urban Sustainable Development(ES-FS-USD)spatial optimization framework.This framework combines the non-dominated sorting genetic algorithm II(NSGA-II)and patch-generating land use simulation(PLUS)model with an ecological protection importance evaluation,comprehensive agricultural productivity evaluation,and urban sustainable development potential assessment and optimizes the territorial space in the Yangtze River Delta(YRD)region in 2035.The proposed sustainable development(SD)scenario can effectively reduce the destruction of landscape patterns of various land-use types while considering both ecological and economic benefits.The simulation results were further revised by evaluating the land-use suitability of the YRD region.According to the revised spatial pattern for the YRD in 2035,the farmland area accounts for 43.59%of the total YRD,which is 5.35%less than that in 2010.Forest,grassland,and water area account for 40.46%of the total YRD—an increase of 1.42%compared with the case in 2010.Construction land accounts for 14.72%of the total YRD—an increase of 2.77%compared with the case in 2010.The ES-FS-USD spatial optimization framework ensures that spatial optimization outcomes are aligned with the natural endowments of land resources,thereby promoting the sustainable use of land resources,improving the ability of spatial management,and providing valuable insights for decision makers.展开更多
Establishing a Regional Marine Innovation Ecosystem(RMIE)is crucial for advancing China’s maritime power strategy.Concurrently,developing a competitive RMIE serves as a strategic lever to enhance the global competiti...Establishing a Regional Marine Innovation Ecosystem(RMIE)is crucial for advancing China’s maritime power strategy.Concurrently,developing a competitive RMIE serves as a strategic lever to enhance the global competitiveness of China’s marine science sector.However,research on the competitiveness of RMIE is limited.To this end,this study constructs an evaluation index system based on ecological niche theory to assess the competitiveness of RMIE in China from 2008 to 2020.The findings indicate generally fluctuating upward trends in RMIE’s competitiveness,with Shandong,Jiangsu,and Guangdong showing relatively strong positions.Notably,there are significant intra-regional imbalances and inter-regional asynchrony in RMIE’s competitiveness across China’s three major marine economic circles.Recognizing that forecasting RMIE competitiveness can inform policy formulation,this paper proposes a systematic multivariate grey interval prediction model that incorporates spatial proximity effects.This model effectively captures the interval and uncertainty characteristics of RMIE’s competitiveness while considering spatial relationships among regions.Results from comparative analysis,robustness tests,and sensitivity analysis demonstrate its superior applicability and forecasting accuracy.Additionally,interval forecasts and scenario analyses suggest that RMIE competitiveness will maintain stable growth,although unbalanced and unsynchronized development is likely to persist.Overall,the approach developed for evaluating and forecasting RMIE competitiveness offers valuable insights for effective policy formulation.展开更多
Precipitation events,which follow a life cycle of initiation,development,and decay,represent the fundamental form of precipitation.Comprehensive and accurate detection of these events is crucial for effective water re...Precipitation events,which follow a life cycle of initiation,development,and decay,represent the fundamental form of precipitation.Comprehensive and accurate detection of these events is crucial for effective water resource management and flood control.However,current investigations on their spatio-temporal patterns remain limited,largely because of the lack of systematic detection indices that are specifically designed for precipitation events,which constrains event-scale research.In this study,we defined a set of precipitation event detection indices(PEDI)that consists of five conventional and fourteen extreme indices to characterize precipitation events from the perspectives of intensity,duration,and frequency.Applications of the PEDI revealed the spatial patterns of hourly precipitation events in China and its first-and second-order river basins from 2008 to 2017.Both conventional and extreme precipitation events displayed spatial distribution patterns that gradually decreased in intensity,duration,and frequency from southeast to northwest China.Compared with those in northwest China,the average values of most PEDIs in southeast China were usually 2-10 times greater for first-order river basins and 3-15 times greater for second-order basins.The PEDI could serve as a reference method for investigating precipitation events at global,regional,and basin scales.展开更多
Osteoarthritis(OA)is a degenerative skeletal condition marked by the loss of articular cartilage and changes to subchondral bone homeostasis.Treatments for OA beyond full joint replacement are lacking primarily due to...Osteoarthritis(OA)is a degenerative skeletal condition marked by the loss of articular cartilage and changes to subchondral bone homeostasis.Treatments for OA beyond full joint replacement are lacking primarily due to gaps in molecular knowledge of the biological drivers of disease.Mass Spectrometry Imaging(MSI)enables molecular spatial mapping of the proteomic landscape of tissues.Histologic sections of human tibial plateaus from knees of human OA patients and cadaveric controls were treated with collagenase III to target extracellular matrix(ECM)proteins prior to MS Imaging of bone and cartilage proteins.Spatial MS imaging of the knee identified distinct areas of joint damage to the subchondral bone underneath areas of lost cartilage.This damaged bone signature extended underneath remaining cartilage in OA joints,indicating subchondral bone remodeling could occur before full thickness cartilage loss in OA.Specific ECM peptide markers from OA-affected medial tibial plateaus were compared to their healthier lateral halves from the same patient,as well as to healthy,age-matched cadaveric knees.Overall,31 peptide candidates from ECM proteins,including Collagen alpha-1(Ⅰ),Collagen alpha-1(Ⅲ),and surprisingly,Collagen alpha-1(Ⅵ)and Collagen alpha-3(Ⅵ),exhibited significantly elevated abundance in diseased tissues.Additionally,highly specific hydroxyproline-containing collagen peptides,mainly from collagen typeⅠ,dominated OA subchondral bone directly under regions of lost cartilage but not areas where cartilage remained intact.A separate analysis of synovial fluid from a second cohort of OA patients found similar regulation of collagens and ECM proteins via LC-MS/MS demonstrating that markers of subchondral bone remodeling discovered by MALDI-MS may be detectable as biomarkers in biofluid samples.The identification of specific protein markers for subchondral bone remodeling in OA advances our molecular understanding of disease progression in OA and provides potential new biomarkers for OA detection and disease grading.展开更多
Under the background of‘the Belt and Road’and‘China-Mongolia-Russia Economic Corridor’initiatives,this paper studied the urban accessibility level,regional accessibility pattern and regional spatial effects along ...Under the background of‘the Belt and Road’and‘China-Mongolia-Russia Economic Corridor’initiatives,this paper studied the urban accessibility level,regional accessibility pattern and regional spatial effects along the Primorsky No.1 and No.2 transportation corridors.First,the evaluation of urban accessibility level with and without Primorsky No.1 and No.2 high-speed rails(HSRs)opening was conducted with two indicators,i.e.,the weighted average travel time,and the economic potential.After the evaluation,the spatial differentiation pattern of the accessibility changes with and without Primorsky No.1 and No.2 HSRs opening was performed respectively using ArcGIS.On these bases,the regional spatial effects brought by Primorsky No.1 and No.2 HSRs opening were studied.The results are as following.First,the urban accessibility level will be greatly improved by the opening of Primorsky No.1 and No.2 HSRs.All adjacent cities will be integrated into‘1 h HSR communication circle’and the whole journey will be integrated into‘4 h HSR communication circle’along Primorsky No.1 and No.2 corridors,respectively.The HSR accessibility of Primorsky No.1 corridor is stronger than that of Primorsky No.2 corridor.But the HSR accessibility improvement degree of Primorsky No.1 corridor is weaker than that of Primorsky No.2 corridor.Second,spatially,along Primorsky No.1 and No.2 corridors,the HSR accessibility level of the cities which are located in China is stronger than those cities located in Russia,showing the‘High West,Low East’patterns.The HSR accessibility improvement degree of the cities which are located in Russia and Sino-Russian border is stronger than those cities located in China,showing the‘High East,Low West’patterns.Third,Primorsky No.1 and No.2 corridors could connect the China’s‘Heilongjiang Land Sea Silk Road Economic Belt’and‘Changchun-Jilin-Tumen Development Pilot Zone’respectively,gradually involving into the development of China’s Harbin-Changchun Megalopolis.Relying on Harbin(China)and Changchun(China),Primorsky No.1 and No.2 HSRs could connect Northeast China-Beijing HSR,accelerating the diffusion of population,economy and other flows from China’s Beijing-Tianjin-Hebei Urban Agglomeration to Northeast China,and then to Russia’s Far East Federal District.Relying on Suifenhe(China)and Hunchun(China),Primorsky No.1 and No.2 HSRs could be conducive to the development of the second largest sea channels for Northeast China,creating the Northeast Asian Urban Belt,and new sea-rail intermodal pattern among China,Russia,Democratic People’s Republic of Korea,Japan and Republic of Korea.Relying on Vladivostok(Russia)and Zarubino(Russia),Primorsky No.1 and No.2 corridors could connect the‘Ice Silk Road’,building the‘Sino-Russian Northern Maritime Corridor’and‘Sino-Russian Arctic Blue Economic Areas’.展开更多
The word“spatial”fundamentally relates to human existence,evolution,and activity in terrestrial and even celestial spaces.After reviewing the spatial features of many areas,the paper describes basics of high level m...The word“spatial”fundamentally relates to human existence,evolution,and activity in terrestrial and even celestial spaces.After reviewing the spatial features of many areas,the paper describes basics of high level model and technology called Spatial Grasp for dealing with large distributed systems,which can provide spatial vision,awareness,management,control,and even consciousness.The technology description includes its key Spatial Grasp Language(SGL),self-evolution of recursive SGL scenarios,and implementation of SGL interpreter converting distributed networked systems into powerful spatial engines.Examples of typical spatial scenarios in SGL include finding shortest path tree and shortest path between network nodes,collecting proper information throughout the whole world,elimination of multiple targets by intelligent teams of chasers,and withstanding cyber attacks in distributed networked systems.Also this paper compares Spatial Grasp model with traditional algorithms,confirming universality of the former for any spatial systems,while the latter just tools for concrete applications.展开更多
基金Under the auspices of the National Natural Science Foundation of China(No.42371222,41971167)Fundamental Scientific Research Funds of Central China Normal University(No.CCNU24ZZ120)。
文摘Owing to intensified globalization and informatization,the structures of the urban scale hierarchy and urban networks between cities have become increasingly intertwined,resulting in different spatial effects.Therefore,this paper analyzes the spatial interaction between urban scale hierarchy and urban networks in China from 2019 to 2023,drawing on Baidu migration data and employing a spatial simultaneous equation model.The results reveal a significant positive spatial correlation between cities with higher hierarchy and those with greater network centrality.Within a static framework,we identify a positive interaction between urban scale hierarchy and urban network centrality,while their spatial cross-effects manifest as negative neighborhood interactions based on geographical distance and positive cross-scale interactions shaped by network connections.Within a dynamic framework,changes in urban scale hierarchy and urban networks are mutually reinforcing,thereby widening disparities within the urban hierarchy.Furthermore,an increase in a city’s network centrality had a dampening effect on the population growth of neighboring cities and network-connected cities.This study enhances understanding of the spatial organisation of urban systems and offers insights for coordinated regional development.
基金supported by the National Natural Science Foundation of China(NSFC)(Nos.12074399,12204500,and 12004403)the Key Projects of Intergovernmental International Scientific and Technological Innovation Cooperation(No.2021YFE0116700)+1 种基金the Shanghai Natural Science Foundation(No.20ZR1464400)the Shanghai Sailing Program(No.22YF1455300).
文摘The suppression of ablative Rayleigh–Taylor instability(ARTI)by a spatially modulated laser in inertial confinement fusion(ICF)is studied through numerical simulations.The results show that in the acceleration phase of ICF implosion,the growth of ARTI can be suppressed by using a short-wavelength spatially modulated laser.The ARTI growth rate decreases as the wavelength of the spatially modulated laser decreases,and ARTI is completely suppressed after a certain wavelength has been reached.A spatially uniform laser is introduced to keep the state of motion of the implosion fluid consistent,and it is found that the proportion of the spatially modulated laser required for complete suppression of ARTI decreases as the wavelength continues to decrease.We also optimize the spatial intensity distribution of the spatially modulated laser.In addition,as the duration of the spatially modulated laser decreases,the proportion required for completely suppressing ARTI increases,but the required energy decreases.When the perturbation wavenumber decreases,the wavelength of the spatially modulated laser required for complete suppression of ARTI becomes longer.In the case of multimode perturbation,ARTI can also be significantly suppressed by a spatially modulated laser,and the perturbation amplitude can be reduced to less than 10% of that without a spatially modulated laser.We believe that the conclusions drawn from our simulations can provide the basis for new approaches to control ARTI in ICF.
文摘Alzheimer’s disease(AD)is the most common form of dementia.In addition to the lack of effective treatments,there are limitations in diagnostic capabilities.The complexity of AD itself,together with a variety of other diseases often observed in a patient’s history in addition to their AD diagnosis,make deciphering the molecular mechanisms that underlie AD,even more important.Large datasets of single-cell RNA sequencing,single-nucleus RNA-sequencing(snRNA-seq),and spatial transcriptomics(ST)have become essential in guiding and supporting new investigations into the cellular and regional susceptibility of AD.However,with unique technology,software,and larger databases emerging;a lack of integration of these data can contribute to ineffective use of valuable knowledge.Importantly,there was no specialized database that concentrates on ST in AD that offers comprehensive differential analyses under various conditions,such as sex-specific,region-specific,and comparisons between AD and control groups until the new Single-cell and Spatial RNA-seq databasE for Alzheimer’s Disease(ssREAD)database(Wang et al.,2024)was introduced to meet the scientific community’s growing demand for comprehensive,integrated,and accessible data analysis.
基金supported by the National Natural Science Foundation of China(32171022,32221005,and 32401246).
文摘While conventional FISH and IHC methods struggle to decode complex tissue heterogeneity and comprehensive molecular diagnosis due to low-throughput spatial information,spatial omics technologies enable high-throughput molecular mapping across tissue microenvironments.These technologies are emerging as transformative tools in molecular diagnostics and medical research.By integrating histopathological morphology with spatial multi-omics profiling(genome,transcriptome,epigenome,and proteome),spatial omics technologies open an avenue for understanding disease progression,therapeutic resistance mechanisms,and precise diagnosis.It particularly enhances tumor microenvironment analysis by mapping immune cell distributions and functional states,which may greatly facilitate tumor molecular subtyping,prognostic assessment,and prediction of the radiotherapy and chemotherapy efficacy.Despite the substantial advancements in spatial omics,the translation of spatial omics into clinical applications remains challenging due to robustness,efficacy,clinical validation,and cost constraints.In this review,we summarize the current progress and prospects of spatial omics technologies,particularly in medical research and diagnostic applications.
基金financially supported by the National Natural Science Foundation of China(Nos.42577209 and U22A20239)the Key R&D Program of Hunan Province(No.2024WK2004)the Key Technologies for Accurate Diagnosis and Intelligent Prevention and Control of Slope Hazards in Open pit Mines,181 Major R&D projects of Metallurgical Corporation of China Ltd。
文摘Excessive blasting-induced vibration during drilling-and-blasting excavation of deep tunnels can trigger geological hazards and compromise the stability of both the rock mass and support structures.This study focused on the deep double-line Sejila Mountain tunnel to systematically analyze the spatial response of blasting-induced vibration and to develop a prediction model through field tests and numerical simulations.The results revealed that the presence of a cross passage significantly altered propagation paths and the spatial distribution of blasting-induced vibration velocity.The peak particle velocity(PPV)at the cross-passage corner was amplified by approximately 1.92 times due to wave reflection and geometric focusing.Blasting-induced vibration waves attenuated non-uniformly across the tunnel cross-section,where PPV on the blast-face side was 1.54–6.56 times higher than that on the opposite side.We propose an improved PPV attenuation model that accounts for the propagation path effect.This model significantly improved fitting accuracy and resolved anomalous parameter(k and a)estimates in traditional equations,thereby improving prediction reliability.Furthermore,based on the observed spatial distribution of blasting-induced vibration,optimal monitoring point placement and targeted vibration control measures for tunnel blasting were discussed.These findings provide a scientific basis for designing blasting schemes and vibration mitigation strategies in deep tunnels.
基金financial support from the National Natural Science Foundation of China (Nos.82473887 and 21927808)the Scientific and Technological Innovation Program of Shanghai (No.23DZ2202500)the CAMS Innovation Fund for Medical Sciences (No.2021-1-I2M-026)。
文摘The brain's functions are governed by molecular metabolic networks.However,due to the sophisticated spatial organization and diverse activities of the brain,characterizing both the minute and large-scale metabolic activity across the entire brain and its numerous micro-regions remains incredibly challenging.Here,we offer a high-definition spatially resolved metabolomics technique to better understand the metabolic specialization and interconnection throughout the mouse brain using improved ambient mass spectrometry imaging.This method allows for the simultaneous mapping of thousands of metabolites at a 30 μm spatial resolution across the mouse brain,ranging from structural lipids to functional neurotransmitters.This approach effectively reveals the distribution patterns of delicate microregions and their distinctive metabolic characteristics.Using an integrated database,we annotated 259 metabolites,demonstrating that the metabolome and metabolic pathways are unique to each brain microregion.The distribution of metabolites,closely linked to functionally connected brain regions and their interactions,offers profound insights into the complexity of chemical processes and their roles in brain function.An initial dataset for future metabolomics research might be obtained from the high-definition mouse brain's spatial metabolome atlas.
基金National Key Research and Development Program of China,No.2019YFD1101304National Natural Science Foundation of China,No.52278059+1 种基金Natural Science Foundation of Hunan Province of China,No.2024JJ8316Hunan Provincial Innovation Foundation For Postgraduate,No.CX20250634。
文摘Urban spatial morphology(USM)optimization is critical to balancing biodiversity conservation and sustainable urbanization.However,previous studies predominantly focused on the socio-economic efficiency and static ecological metrics and rarely addressed the dynamic USM optimization across spatial scales.Here,we developed a multi-level ecological network(MEN)framework to resolve the tension between urban expansion and ecological integrity.By integrating the cost-weighted distance analysis with a hierarchical network transmission mechanism,we established a cross-scale spatial optimization system,which coordinated the regional ecological corridors and local habitat patches.Comparative experiments with conventional single-scale approaches and scenario simulations using the PLUS model show that the MEN framework had superior performance in three dimensions:(1)spatial governance:the primary-level network(peri-urban natural reserves)effectively contained urban sprawl,and the secondary-level network(intra-urban green corridors)mitigated habitat fragmentation and improved the built-environment;(2)scenario robustness:the model maintained an optimal compactness-loose balance in multiple development pathways;(3)landscape metrics:patch fragmentation decreased by 18.25%,and the internal landscape richness improved by 10.66%compared to the scenario without USM optimization.The findings provide new insight to establish a hierarchical ecological optimization framework as a nature-based spatial protocol to reconcile metropolitan growth with landscape sustainability.
基金financially supported by the Nation Key R&D Program China(2018YFA0703200)the Key Research and Development Program of Hubei Province(2022BAA026)+1 种基金the National Natural Science Foundation of China(51772110)the Open Research Fund(2024JYBKF01)of Key Laboratory of Material Chemistry for Energy Conversion and Storage(HUST),Ministry of Education。
文摘Sluggish kinetics coupled with parasitic shuttling reactions are pivotal challenges hindering the performance of lithium-sulfur(Li-S)batteries.Improving areal capacity and cyclability of Li-S batteries can be achieved by addressing these challenges.A composite sulfur host material is synthesized herein by in situ anchoring ultrafine cobalt-iron phosphide nanoparticles(5-7 nm)onto a hollow mesoporous carbon sphere(HMCS)framework.This strategy achieved exceptional spatial restriction and a high density of catalytically active sites through the encapsulation of sulfur within a hollow-structured framework.Specifically,HMCS expedites rapid Li_(2)S nucleation kinetics,while CoFeP facilitates robust Li_(2)S dissolution kinetics by mitigating decomposition barriers.This synergistic integration equips CoFeP@HMCS with robust bi-directional catalytic activity,significantly promoting interracial charge-transfer,facilitate sulfu r multistep catalytic conversion,and inhibiting shuttling.Consequently,the battery exhibits excellent rate performance(991 mA h g^(-1) at 5.0 C)and retains a high areal capacity of 6.06 mA h cm^(-2) after 200 cycles under a high areal sulfur loading of 8.2 mg cm^(-2) but a low electrolyte/sulfur ratio of 4.8μL mg^(-1).This work contributes to enhancing the practical specific capacity of lithium-sulfur batteries and deepens the understanding of catalysts enabling bidirectional electrocatalytic sulfur conversion.
基金sponsored by the National Natural Science Foundation of China(Grant No.52178100).
文摘The spatial offset of bridge has a significant impact on the safety,comfort,and durability of high-speed railway(HSR)operations,so it is crucial to rapidly and effectively detect the spatial offset of operational HSR bridges.Drive-by monitoring of bridge uneven settlement demonstrates significant potential due to its practicality,cost-effectiveness,and efficiency.However,existing drive-by methods for detecting bridge offset have limitations such as reliance on a single data source,low detection accuracy,and the inability to identify lateral deformations of bridges.This paper proposes a novel drive-by inspection method for spatial offset of HSR bridge based on multi-source data fusion of comprehensive inspection train.Firstly,dung beetle optimizer-variational mode decomposition was employed to achieve adaptive decomposition of non-stationary dynamic signals,and explore the hidden temporal relationships in the data.Subsequently,a long short-term memory neural network was developed to achieve feature fusion of multi-source signal and accurate prediction of spatial settlement of HSR bridge.A dataset of track irregularities and CRH380A high-speed train responses was generated using a 3D train-track-bridge interaction model,and the accuracy and effectiveness of the proposed hybrid deep learning model were numerically validated.Finally,the reliability of the proposed drive-by inspection method was further validated by analyzing the actual measurement data obtained from comprehensive inspection train.The research findings indicate that the proposed approach enables rapid and accurate detection of spatial offset in HSR bridge,ensuring the long-term operational safety of HSR bridges.
基金National Natural Science Foundation of China,No.42471455,No.42230113National Key Research and Development Program of China,No.2022YFC3800804-01。
文摘Ensuring national food security amidst rapid population growth and increasing extreme weather events remains a critical global challenge.However,the extent to which agricultural modernization in China enhances grain yield and contributes to food security remains unclear.Therefore,using panel data from 327 Chinese cities(2013–2021),this study employs spatial econometric models to analyze the spatial spillover effects of agricultural modernization level(AML)on grain yield and to reveal regional heterogeneity across nine major agricultural zones.The results showed a cumulative grain yield increase of 23.7 million tons,with peak productivity concentrated along the Hu Line and declining eastward and westward.AML also exhibited a steady increase but a clear spatial gradient,decreasing from coastal to inland regions,with the highest level observed in Southern China(SC).A key finding was that a 1%increase in AML directly raised local grain yield by an average of 4.185%,accompanied by significant positive spillover effects on neighboring regions.Regional variations revealed distinct patterns:the direct effects of AML were more pronounced in southern and eastern zones,while spillover effects dominated in northern and western zones.The largest positive direct impact of AML on grain yield was observed in the SC(8.499%),while Middle-Lower Yangtze Plain ranked second but exhibited the strongest positive spatial spillover effect(4.534%).These findings highlight the critical role of agricultural modernization in promoting grain production and provide a solid basis for optimizing regional agricultural systems,ensuring food security,and advancing sustainable agriculture.
基金supported by National Key Research and Development Program of China(2024YFF1307400)Hubei Provincial Natural Science Foundation and Three Gorges Innovation Development Joint Fund(Grant No.2023AFD195)China Three Gorges Corporation(NBZZ202300130).
文摘Successful ex situ conservation of plant populations requires a high degree of genetic representativeness.However,spatially biased sampling in ex situ conservation efforts may fail to capture all wild genetic clusters for species with range-wide genetic structure.To investigate the extent of spatially biased sampling in living collections and the coverage of wild genetic clusters in plant populations under ex situ conservation worldwide,we combined a global synthesis of ex situ conservation efforts with a case study of an endangered riparian plant species,Myricaria laxiflora.Our analysis of ex situ conservation worldwide revealed that the majority(82.6%)of ex situ populations fail to cover all wild genetic clusters,largely due to spatially biased sampling with low geographic coverage.Our case study of M.laxiflora showed that genetic diversity differed between the ex situ and upstream populations,while it was comparable between ex situ populations and other wild populations.However,current ex situ populations did not cover all wild genetic clusters,as the upstream genetic cluster was previously uncollected.Our study suggests that the failure to cover all wild genetic clusters in ex situ populations is a widespread issue,and ex situ populations with high genetic diversity can also fail to cover all wild genetic clusters.In future ex situ conservation programs,both the importance of high genetic diversity and the high coverage of wild genetic clusters should be prioritized.
文摘To enhance the accuracy of short-term photovoltaic power output prediction and address issues such as insufficient spatial resolution of meteorological forecast data and weak generalization ability of models,this paper proposes a prediction method that integrates spatial downscaling meteorological data with a convolutional neural network(CNN)-iTransformer-long short-term memory(LSTM)model.First,the rime-optimized random forest regression algorithm(RIME-RF)is employed to perform spatial downscaling on numerical weather prediction(NWP)data,thereby improving its local applicability.Second,a CNN-iTransformer-LSTM hybrid prediction model is constructed.This model utilizes a CNN as a spatial feature extractor to capture local patterns in meteorological data,employs an iTransformer to model the global dependencies among multiple variables,and leverages an LSTM to enhance the learning of short-term temporal dynamic features,thereby achieving efficient collaborative mining of multi-scale features.Finally,experiments are conducted using actual data from a photovoltaic power station in Hebei,China,during various seasons and weather conditions.The results show that the proposed model outperforms the comparison models in terms of the root mean square error(RMSE),mean absolute error(MAE),and R2,maintaining high prediction accuracy and stability even under complex weather conditions such as overcast and rainy days.The downscaling process further enhances the prediction performance,verifying the effectiveness and practicality of this method.
基金supported by the National Key R&D Program of China(No.2022YFC3003502).
文摘The northern segment of the North-South Seismic Belt is characterized by intense crustal deformation,well-developed active tectonics,and frequent occurrences of strong earthquakes.Therefore,conducting a Probabilistic Seismic Hazard Analysis(PSHA)for this region is of significant importance for supporting seismic fortification in major engineering projects and formulating disaster prevention and mitigation policies.In this study,a composite seismic source model was constructed by integrating data on historical earthquakes,active faults,and paleoseismicity.Furthermore,a logic tree framework was employed to quantify epistemic uncertainties,enabling a systematic seismic hazard assessment of the region.To more accurately characterize the spatial heterogeneity of seismic activity,improvements were made to both the Circular Spatial Smoothing Model(CSSM)with a fixed radius and the Adaptive Spatial Smoothing Model(ASSM),with full consideration given to the spatiotemporal completeness of historical earthquake magnitudes.Regarding the CSSM,for scenarios involving small sample sizes in earthquake catalogs,the cross-validation method proposed in this study demonstrated higher robustness than the maximum likelihood method in determining the optimal correlation distance.Performance evaluation results indicate that while both models effectively characterize seismic activity,the ASSM exhibits superior overall predictive performance compared to the CSSM,owing to its ability to adaptively adjust the smoothing radius according to seismic density.Significant discrepancies were observed in the Peak Ground Acceleration(PGA)results calculated with a 10%probability of exceedance in 50 years across different combinations of seismic source models.The single spatially smoothed point-source model yielded a maximum PGA of approximately 0.52 g,with high-value areas concentrated near historical epicenters,thereby significantly underestimating the hazard associated with major fault zones.When combined with the simple fault-source model,the maximum PGA increased to 0.8 g,with high-value zones exhibiting a zonal distribution along faults;however,the risk remained underestimated for faults with low slip rates that are nevertheless approaching their recurrence cycles.Following the introduction of the time-dependent characteristic fault-source model,local PGA values for faults in the middle-to-late stages of their recurrence cycles increased by a factor of 2 to 7 compared to the single model.These results demonstrate that the characteristic fault-source model reasonably delineates the time-dependence of large earthquake recurrence,thereby providing a more accurate assessment of imminent seismic risks.By comprehensively applying the improved spatially smoothed pointsource model,the simple fault-source model,and the characteristic fault-source model,the following faults within the region were identified as having high seismic hazard:the Huangxianggou,Zhangxian,and Tianshui segments of the Xiqinling northern edge fault;the Maqin-Maqu segment of the Dongkunlun fault;the Longriqu fault;the Maoergai fault;the Elashan fault;the Riyueshan fault;the eastern segment of the Lenglongling fault;the Maxianshan segment of the Maxianshan northern Margin fault;and the Maomaoshan-Jinqianghe segment of the Laohushan-Maomaoshan fault.As these faults are located within seismic gaps or are approaching the recurrence periods of large earthquakes,they should be prioritized for current and future seismic monitoring as well as disaster prevention and mitigation efforts.
基金National Natural Science Foundation of China,No.42301470,No.52270185,No.42171389Capacity Building Program of Local Colleges and Universities in Shanghai,No.21010503300。
文摘Rapid urbanization in China has led to spatial antagonism between urban development and farmland protection and ecological security maintenance.Multi-objective spatial collaborative optimization is a powerful method for achieving sustainable regional development.Previous studies on multi-objective spatial optimization do not involve spatial corrections to simulation results based on the natural endowment of space resources.This study proposes an Ecological Security-Food Security-Urban Sustainable Development(ES-FS-USD)spatial optimization framework.This framework combines the non-dominated sorting genetic algorithm II(NSGA-II)and patch-generating land use simulation(PLUS)model with an ecological protection importance evaluation,comprehensive agricultural productivity evaluation,and urban sustainable development potential assessment and optimizes the territorial space in the Yangtze River Delta(YRD)region in 2035.The proposed sustainable development(SD)scenario can effectively reduce the destruction of landscape patterns of various land-use types while considering both ecological and economic benefits.The simulation results were further revised by evaluating the land-use suitability of the YRD region.According to the revised spatial pattern for the YRD in 2035,the farmland area accounts for 43.59%of the total YRD,which is 5.35%less than that in 2010.Forest,grassland,and water area account for 40.46%of the total YRD—an increase of 1.42%compared with the case in 2010.Construction land accounts for 14.72%of the total YRD—an increase of 2.77%compared with the case in 2010.The ES-FS-USD spatial optimization framework ensures that spatial optimization outcomes are aligned with the natural endowments of land resources,thereby promoting the sustainable use of land resources,improving the ability of spatial management,and providing valuable insights for decision makers.
基金National Social Science Fund of China,No.24BTJ037Significant Project of the National Social Science Foundation of China,No.23&ZD102+1 种基金The Key Research Base for Philosophy and Social Sciences in Hangzhou:ESG and Sustainable Development Research Center,No.25JD053Zhejiang Provincial Statistical Scientific Research Project,No.25TJZZ12。
文摘Establishing a Regional Marine Innovation Ecosystem(RMIE)is crucial for advancing China’s maritime power strategy.Concurrently,developing a competitive RMIE serves as a strategic lever to enhance the global competitiveness of China’s marine science sector.However,research on the competitiveness of RMIE is limited.To this end,this study constructs an evaluation index system based on ecological niche theory to assess the competitiveness of RMIE in China from 2008 to 2020.The findings indicate generally fluctuating upward trends in RMIE’s competitiveness,with Shandong,Jiangsu,and Guangdong showing relatively strong positions.Notably,there are significant intra-regional imbalances and inter-regional asynchrony in RMIE’s competitiveness across China’s three major marine economic circles.Recognizing that forecasting RMIE competitiveness can inform policy formulation,this paper proposes a systematic multivariate grey interval prediction model that incorporates spatial proximity effects.This model effectively captures the interval and uncertainty characteristics of RMIE’s competitiveness while considering spatial relationships among regions.Results from comparative analysis,robustness tests,and sensitivity analysis demonstrate its superior applicability and forecasting accuracy.Additionally,interval forecasts and scenario analyses suggest that RMIE competitiveness will maintain stable growth,although unbalanced and unsynchronized development is likely to persist.Overall,the approach developed for evaluating and forecasting RMIE competitiveness offers valuable insights for effective policy formulation.
基金National Key Research and Development Program of China,No.2023YFC3206605,No.2021YFC3201102National Natural Science Foundation of China,No.41971035。
文摘Precipitation events,which follow a life cycle of initiation,development,and decay,represent the fundamental form of precipitation.Comprehensive and accurate detection of these events is crucial for effective water resource management and flood control.However,current investigations on their spatio-temporal patterns remain limited,largely because of the lack of systematic detection indices that are specifically designed for precipitation events,which constrains event-scale research.In this study,we defined a set of precipitation event detection indices(PEDI)that consists of five conventional and fourteen extreme indices to characterize precipitation events from the perspectives of intensity,duration,and frequency.Applications of the PEDI revealed the spatial patterns of hourly precipitation events in China and its first-and second-order river basins from 2008 to 2017.Both conventional and extreme precipitation events displayed spatial distribution patterns that gradually decreased in intensity,duration,and frequency from southeast to northwest China.Compared with those in northwest China,the average values of most PEDIs in southeast China were usually 2-10 times greater for first-order river basins and 3-15 times greater for second-order basins.The PEDI could serve as a reference method for investigating precipitation events at global,regional,and basin scales.
文摘Osteoarthritis(OA)is a degenerative skeletal condition marked by the loss of articular cartilage and changes to subchondral bone homeostasis.Treatments for OA beyond full joint replacement are lacking primarily due to gaps in molecular knowledge of the biological drivers of disease.Mass Spectrometry Imaging(MSI)enables molecular spatial mapping of the proteomic landscape of tissues.Histologic sections of human tibial plateaus from knees of human OA patients and cadaveric controls were treated with collagenase III to target extracellular matrix(ECM)proteins prior to MS Imaging of bone and cartilage proteins.Spatial MS imaging of the knee identified distinct areas of joint damage to the subchondral bone underneath areas of lost cartilage.This damaged bone signature extended underneath remaining cartilage in OA joints,indicating subchondral bone remodeling could occur before full thickness cartilage loss in OA.Specific ECM peptide markers from OA-affected medial tibial plateaus were compared to their healthier lateral halves from the same patient,as well as to healthy,age-matched cadaveric knees.Overall,31 peptide candidates from ECM proteins,including Collagen alpha-1(Ⅰ),Collagen alpha-1(Ⅲ),and surprisingly,Collagen alpha-1(Ⅵ)and Collagen alpha-3(Ⅵ),exhibited significantly elevated abundance in diseased tissues.Additionally,highly specific hydroxyproline-containing collagen peptides,mainly from collagen typeⅠ,dominated OA subchondral bone directly under regions of lost cartilage but not areas where cartilage remained intact.A separate analysis of synovial fluid from a second cohort of OA patients found similar regulation of collagens and ECM proteins via LC-MS/MS demonstrating that markers of subchondral bone remodeling discovered by MALDI-MS may be detectable as biomarkers in biofluid samples.The identification of specific protein markers for subchondral bone remodeling in OA advances our molecular understanding of disease progression in OA and provides potential new biomarkers for OA detection and disease grading.
基金Under the auspices of Heilongjiang Provincial Natural Science Foundation of China(No.YQ2024D012),National Natural Science Foundation of China(No.42071162,42101165,42501220)。
文摘Under the background of‘the Belt and Road’and‘China-Mongolia-Russia Economic Corridor’initiatives,this paper studied the urban accessibility level,regional accessibility pattern and regional spatial effects along the Primorsky No.1 and No.2 transportation corridors.First,the evaluation of urban accessibility level with and without Primorsky No.1 and No.2 high-speed rails(HSRs)opening was conducted with two indicators,i.e.,the weighted average travel time,and the economic potential.After the evaluation,the spatial differentiation pattern of the accessibility changes with and without Primorsky No.1 and No.2 HSRs opening was performed respectively using ArcGIS.On these bases,the regional spatial effects brought by Primorsky No.1 and No.2 HSRs opening were studied.The results are as following.First,the urban accessibility level will be greatly improved by the opening of Primorsky No.1 and No.2 HSRs.All adjacent cities will be integrated into‘1 h HSR communication circle’and the whole journey will be integrated into‘4 h HSR communication circle’along Primorsky No.1 and No.2 corridors,respectively.The HSR accessibility of Primorsky No.1 corridor is stronger than that of Primorsky No.2 corridor.But the HSR accessibility improvement degree of Primorsky No.1 corridor is weaker than that of Primorsky No.2 corridor.Second,spatially,along Primorsky No.1 and No.2 corridors,the HSR accessibility level of the cities which are located in China is stronger than those cities located in Russia,showing the‘High West,Low East’patterns.The HSR accessibility improvement degree of the cities which are located in Russia and Sino-Russian border is stronger than those cities located in China,showing the‘High East,Low West’patterns.Third,Primorsky No.1 and No.2 corridors could connect the China’s‘Heilongjiang Land Sea Silk Road Economic Belt’and‘Changchun-Jilin-Tumen Development Pilot Zone’respectively,gradually involving into the development of China’s Harbin-Changchun Megalopolis.Relying on Harbin(China)and Changchun(China),Primorsky No.1 and No.2 HSRs could connect Northeast China-Beijing HSR,accelerating the diffusion of population,economy and other flows from China’s Beijing-Tianjin-Hebei Urban Agglomeration to Northeast China,and then to Russia’s Far East Federal District.Relying on Suifenhe(China)and Hunchun(China),Primorsky No.1 and No.2 HSRs could be conducive to the development of the second largest sea channels for Northeast China,creating the Northeast Asian Urban Belt,and new sea-rail intermodal pattern among China,Russia,Democratic People’s Republic of Korea,Japan and Republic of Korea.Relying on Vladivostok(Russia)and Zarubino(Russia),Primorsky No.1 and No.2 corridors could connect the‘Ice Silk Road’,building the‘Sino-Russian Northern Maritime Corridor’and‘Sino-Russian Arctic Blue Economic Areas’.
文摘The word“spatial”fundamentally relates to human existence,evolution,and activity in terrestrial and even celestial spaces.After reviewing the spatial features of many areas,the paper describes basics of high level model and technology called Spatial Grasp for dealing with large distributed systems,which can provide spatial vision,awareness,management,control,and even consciousness.The technology description includes its key Spatial Grasp Language(SGL),self-evolution of recursive SGL scenarios,and implementation of SGL interpreter converting distributed networked systems into powerful spatial engines.Examples of typical spatial scenarios in SGL include finding shortest path tree and shortest path between network nodes,collecting proper information throughout the whole world,elimination of multiple targets by intelligent teams of chasers,and withstanding cyber attacks in distributed networked systems.Also this paper compares Spatial Grasp model with traditional algorithms,confirming universality of the former for any spatial systems,while the latter just tools for concrete applications.
