With the need in the global change research project for the land -use/land-cover change information, most international and regional research organization or groups have put amounts of efforts to improve of the dynami...With the need in the global change research project for the land -use/land-cover change information, most international and regional research organization or groups have put amounts of efforts to improve of the dynamics monitoring and database updating techniques. With the pressure on nature environment from increasing population and decreasing farmland be- coming significant more and more in China, the farmland urban dynamics in historical and current times, even the change trends in the future, should be monitored and analyzed serving for regional and national social, economic and environmental sustain- able development in the long future. Based on spatial and temporal series of land -use/land-cover database resources, Chinese Academy of Sciences designed a sampling framework for monitoring farmland and urban area dynamics in regional and national level. In order to test the accuracy of the sampling schema for national and regional level, we took two provinces area into overall covered change detecting process with TM images data through being inter’Preted by digitalization on the screen. The result shows that our stratified random sampling schema is suitable for monitoring land -use/land-cover change at national and regional level with quick response, high accuracy and low expenses. The land-use/land-cover change (LUCC) information can update the LUTEA database for global change research during certain period so that the forecasting process and evaluating analysis on land resources and environment under human and natural driving force will get essential data and produce valuable conclusions.展开更多
基于国际比较的地方空间规划的范围和工具研究An International Comparison of the Scope and Instruments of Local Spatial Planning源自:The TownPlanning Review,2024,95(2):197-217作者:MaciejJNowak,StefanieDühr,Sergio Pe&...基于国际比较的地方空间规划的范围和工具研究An International Comparison of the Scope and Instruments of Local Spatial Planning源自:The TownPlanning Review,2024,95(2):197-217作者:MaciejJNowak,StefanieDühr,Sergio Peña,et al.推荐:申明锐,南京大学建筑与城市规划学院。shenmingr@nju.edu.cn.展开更多
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
Laser wakefield accelerators(LWFAs)offer acceleration gradients up to 1000 times higher than those of conventional radio-frequency accelerators,offering a pathway to significantly more compact and cost-effective accel...Laser wakefield accelerators(LWFAs)offer acceleration gradients up to 1000 times higher than those of conventional radio-frequency accelerators,offering a pathway to significantly more compact and cost-effective accelerator systems.This breakthrough opens up new possibilities for laboratory-scale light sources.All-optical inverse Compton scattering(AOCS)sources driven by LWFAs produce high-brightness,quasimonochromatic X rays with micrometer-scale source sizes,delivering the spatial coherence and resolution required for X-ray phase-contrast imaging(XPCI).These features position AOCS X-ray sources as promising tools for applications in biology,medicine,physics,and materials science.However,previous AOCS-based imaging studies have primarily focused on X-ray absorption imaging.In this work,we report successful experimental demonstrations of edge-enhanced in-line XPCI using energy-tunable,quasi-monochromatic AOCS X rays.With a spatial resolution of~20μm,our results clearly show the potential of high-resolution,AOCS-based XPCI applications.展开更多
Two-dimensional materials for flexible energy storage commonly facehuge challenges in limited active surface and hindered charge transport.Herein,wereport an innovative asymmetric pseudocapacitor based on synergistic ...Two-dimensional materials for flexible energy storage commonly facehuge challenges in limited active surface and hindered charge transport.Herein,wereport an innovative asymmetric pseudocapacitor based on synergistic design of modifiedMXene and graphene,integrating gas-induced rapid expansion technology andprecise surface chemical regulation methods.For graphene modification,rapid vaporizationinduces exfoliation and expansion of graphene oxide layers.Subsequently,pseudocapacitiveoxygen-containing groups were selectively introduced through acid oxidation,yielding expanded-and-oxidized graphene(OEG)for positive porous-nanopaperelectrode.For MXene modification,alkali-treated MXene underwent hydrazine assistance to facilitate gas expansion and-NH_(2)grafting,producing MXene-NH_(2)(NOM)for negative porous-nanopaper electrode.Density functional theory calculations show that-COOH moreeffectively modulate graphene’s electronic structure by inducing charge redistribution and creating active sites,thereby enhancing H^(+)adsorption and ion interactions compared to-OH.Meanwhile,-NH_(2)on MXene enable electron delocalization and dynamic Ti-N-H^(+)interactions,speeding up proton adsorption/desorption and boosting both pseudocapacitance and conductivity.Through collaborativeoptimized spatial architecture and surface properties,flexible OEGB and NOMB exhibited of 333.6 and 500.5 F g^(-1)at high mass loading,respectively.The assembled proton pseudocapacitor readily achieved energy and power densities of 58.9 Wh kg^(-1)and 3802 W kg^(-1),respectively,with excellent stability for potential applications.展开更多
Endowed with opportunities from both land and ocean,coastal areas attract expanding human populations and economic activities.At the same time,they face growing societal and environmental pressures from both the above...Endowed with opportunities from both land and ocean,coastal areas attract expanding human populations and economic activities.At the same time,they face growing societal and environmental pressures from both the above river catchments and the bordering sea due to climate change,ecosystem degradation,and expansion of built-up areas.Despite the accumulation of human population,economic activities,and environmental impacts,we lack social-ecological systems analysis on water-related risks to world’s coastal human population.To address this research gap,we analyze the spatial extent of six globally important water stressors to people within the world’s coastal zone(100 km from the coastal line)and classify this zone globally into 12 groups by distance from the coastline and elevation from the mean sea level.Adopting the approaches of the UN Sendai Framework and IPCC,we produce risk maps from the stressor maps by multiplying them with population exposure and vulnerability.For most risks,geographical hotspots are the Chinese coast,Bay of Bengal,Gujarat,and the Island of Java.The analysis reveals fundamental differences between water stressors and related risks,often mixed in scholarly literature.Both manifest specific geographic patterns and latitudinal profiles.Our study highlights the importance of high-resolution spatial analysis of vulnerability,exposure,and risks posed by water related stressors in the world’s coastal zone,in a manner prompted by key policy bodies to promote policy design and shared responsibility for managing stress-prone areas.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
Background and Objectives:The perception of sound in the vertical plane supports spatial hearing by enabling listeners to detect sources located above and below.Sounds originating from both the front and back elevatio...Background and Objectives:The perception of sound in the vertical plane supports spatial hearing by enabling listeners to detect sources located above and below.Sounds originating from both the front and back elevations along the mid-sagittal plane further contribute to a three-dimensional auditory experience.This study aimed to characterize the variability in vertical sound localization abilities among normal-hearing(NH)individuals using spatialized audio.Materials and Methods:Fifty-one NH participants(aged 18 to 35 years)completed three vertical localization tasks under headphones as part of a single-group,within-subject experimental study.These tasks included two-plane identification:(1)top-down localization,(2)front-back localization,and one discrimination task in the front plane.Hierarchical Cluster Analysis(HCA)was employed to identify distinct patterns in spatial localization profiles specific to the vertical-median plane.Fisher's Discriminant Function Analysis(FDA)was used to validate the accuracy of HCA and estimate classification error.Results:HCA revealed three distinct listener clusters:(1)cluster 1 with good performance across all three tasks,(2)cluster 2 with selective impairment in top-bottom identification,and(3)cluster 3 with selective deficits in front-back identification.FDA validated group membership of the clusters identified by the HCA,with a prediction accuracy of 98%.Conclusions:Individuals with clinically NH exhibited three distinct vertical localization profiles:uniform performers,those impaired in top-bottom identification,and those impaired in front-back identification.These profiles may be linked to the interplay between acoustic and non-acoustic perceptual factors.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
Understanding the spatial distributions and corresponding variation mechanisms of key soil nutrients in fragile karst ecosystems can assist in promoting sustainable development.However,due to the implementation of eco...Understanding the spatial distributions and corresponding variation mechanisms of key soil nutrients in fragile karst ecosystems can assist in promoting sustainable development.However,due to the implementation of ecological restoration initiatives such as land-use conversions,novel changes in the spatial characteristics of soil nutrients remain unknown.To address this gap,we explored nutrient variations and the drivers of the variation in the 0–15 cm topsoil layer using a regional-scale sampling method in a typical karst area in northwest Guangxi Zhuang Autonomous Region,Southwest China.Descriptive statistics,geostatistics,and spatial analysis were used to assess the soil nutrient variability.The results indicated that soil organic carbon(SOC),total nitrogen(TN),total phosphorus(TP),and total potassium(TK)concentrations showed moderate variations,with coefficients of variance being 0.60,0.60,0.71,and 0.72,respectively.Moreover,they demonstrated positive spatial autocorrelations,with global Moran's indices being 0.68,0.77,0.64,and 0.68,respectively.However,local Moran's index values were low,indicating large spatial variations in soil nutrients.The best-fitting semi-variogram models for SOC,TN,TP,and TK concentrations were spherical,Gaussian,exponential,and exponential,respectively.According to the classification criteria of the Second National Soil Census in China,SOC and TN concentrations were relatively sufficient,with the proportions of rich and very rich levels being up to 90.9 and 96.0%,respectively.TP concentration was in the mediumdeficient level,with the areas of medium and deficient levels accounting for 33.7 and 30.1%of the total,respectively.TK concentration was deficient,with the cumulative area of extremely deficient,very deficient,and deficient levels accounting for 87.6%of the total area.Consequently,the terrestrial ecosystems in the study area were more vulnerable to soil P and K than soil N deficiencies.Furthermore,variance partitioning analysis of the influencing factors showed that,except for the interactions,the single effect of other soil properties accounted more for soil nutrient variations than spatial and environmental variables.These results will aid in the future management of terrestrial ecosystems.展开更多
The Chinese Giant Solar Telescope(CGST)low-dispersion spectrograph requires a large field-of-view(FOV)and high spatial resolution,which can be addressed by a carefully designed image slicer system.Our proposed design ...The Chinese Giant Solar Telescope(CGST)low-dispersion spectrograph requires a large field-of-view(FOV)and high spatial resolution,which can be addressed by a carefully designed image slicer system.Our proposed design divides the rectangular 50″×20″FOV at the telescope focal plane into four 50″×5″subfields.Each subfield undergoes optical reconstruction using its independent collimator-camera system(F/36-F/25.79),achieving vertical alignment and focal reduction of subfields to form a pseudo-slit.Using tilt mirrors for scanning allows simultaneous acquisition of spectral data with both a large FOV and a high angular resolution of 0.05″.This resolves manufacturing challenges for an image slicer,avoiding the requirement for hundreds of elements,multi-angle configurations,and compact dimensions,and also provides effective technical support for engineering work on the CGST.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
Central Asia is characterized by an arid climate and widespread desert distribution,with its sustainable development severely constrained by dust events.An objective understanding of the spatiotemporal patterns and dr...Central Asia is characterized by an arid climate and widespread desert distribution,with its sustainable development severely constrained by dust events.An objective understanding of the spatiotemporal patterns and driving forces of dust weather is highly important in this area.Based on the meteorological observations from 2000 to 2020,we examined the spatiotemporal characteristics of dust weather in the five Central Asian countries(Kazakhstan,Uzbekistan,Kyrgyzstan,Turkmenistan,and Tajikistan)via Theil-Sen trend analysis and Geodetector modeling method,quantitatively revealing the influence of environmental factors,such as temperature,precipitation,and vegetation,on the frequency of dust weather.The results showed that:(1)dust weather in Central Asia was mainly distributed in a large''dust belt''extending from west to east from northern part of the Caspian lowland desert,and concentrated in basins,plains,and other low-altitude areas.Strong dust weather mainly occurred in northern areas of the Aral Sea and southern edge of Central Asia,with a maximum annual frequency of 21.9%;(2)strong dust weather in Central Asia has fluctuated and slightly decreased since 2001.The highest frequency(1.1%)occurred in spring(from March to June);(3)from 2000 to 2020,changes such as spot shifting and shrinking occurred in the four main source areas(north of the Aral Sea,Kyzylkum Desert,Karakum Desert,and Garabogazköl Bay region),where sandstorms occurred in Central Asia,and northern Caspian lowland desert became the most important low-emission dust source in Central Asia;and(4)the combined effect of soil moisture and air temperature has the most significant influence on dust weather in Central Asia.This study provides a theoretical basis for sand prevention and sand control in Central Asia.In the future,Central Asia should focus on the rational utilization of land and water resources,and implement human interventions such as vegetation restoration and optimization of irrigation methods to curb further desertification in this area.展开更多
In floodplain wetlands,alterations in hydrological patterns resulting from climate change and human activities could potentially diminish the carbon sequestration capacity of the soils,thereby having a negative impact...In floodplain wetlands,alterations in hydrological patterns resulting from climate change and human activities could potentially diminish the carbon sequestration capacity of the soils,thereby having a negative impact on global climate change.However,the magnitude of the influence of hydrological regime change on soil carbon remains inadequately monitored.To address this research gap,we collected 306 upper layer(0–20 cm)soil samples from the Dongting Lake floodplain between 2013 and 2022.The random forest(RF)algorithm was used to analyze the spatial distribution of soil organic carbon(SOC)in the upper soil layer of Dongting Lake floodplain and the impact of climate and hydrological changes in the past decade on surface SOC in the East Dongting Lake area was studied.In 2022,the SOC concentration of the Dongting Lake floodplain upper layer soil ranged from 3.34 to 17.67 g kg^(-1),averaging 10.43 g kg^(-1),with a corresponding SOC density of(2.65±0.49)kg m^(-2) and total SOC stock of 6.82 Tg C(2.87–13.48 Tg C).From 2013 to 2022,the SOC concentration of the upper soil layer of the East Dongting Lake area decreased from 18.37 to 10.82 g kg^(-1).This reduction could be attributed to climate and hydrological changes which reduce SOC input by reducing vegetation growth and accelerating SOC decomposition.Above 21.4 m elevation,the amount of SOC loss increased with elevation,the loss being related to the decline in Miscanthus community biomass and greater susceptibility of higher altitude areas to climate and hydrological changes.Our results highlight the need for strengthening wetland SOC management to increase SOC in the soils to help combat climate change.展开更多
The field of artificial intelligence has advanced significantly in recent years,but achieving a human-like or Artificial General Intelligence(AGI)remains a theoretical challenge.One hypothesis suggests that a key issu...The field of artificial intelligence has advanced significantly in recent years,but achieving a human-like or Artificial General Intelligence(AGI)remains a theoretical challenge.One hypothesis suggests that a key issue is the formalisation of extracting meaning from information.Meaning emerges through a three-stage interpretative process,where the spectrum of possible interpretations is collapsed into a singular outcome by a particular context.However,this approach currently lacks practical grounding.In this research,we developed a model based on contexts,which applies interpretation principles to the visual information to address this gap.The field of computer vision and object recognition has progressed essentially with artificial neural networks,but these models struggle with geometrically transformed images,such as those that are rotated or shifted,limiting their robustness in real-world applications.Various approaches have been proposed to address this problem.Some of them(Hu moments,spatial transformers,capsule networks,attention and memory mechanisms)share a conceptual connection with the contextual model(CM)discussed in this study.This paper investigates whether CM principles are applicable for interpreting rotated images from the MNIST and Fashion MNIST datasets.The model was implemented in the Rust programming language.It consists of a contextual module and a convolutional neural network(CNN).The CMwas trained on the rotated Mono Icons dataset,which is significantly different from the testing datasets.The CNN module was trained on the original MNIST and Fashion MNIST datasets for interpretation recognition.As a result,the CM was able to recognise the original datasets but encountered rotated images only during testing.The findings show that the model effectively interpreted transformed images by considering them in all available contexts and restoring their original form.This provides a practical foundation for further development of the contextual hypothesis and its relation to theAGI domain.展开更多
Great Lakes Regions(GLRs)in China often confront landscape fragmentation,wetland degradation,and ecological resilience(ER)losses owing to extensive and intensive urbanization.In GLRs,however,the ER responses to urbani...Great Lakes Regions(GLRs)in China often confront landscape fragmentation,wetland degradation,and ecological resilience(ER)losses owing to extensive and intensive urbanization.In GLRs,however,the ER responses to urbanization remain unclear.This study explored the spatiotemporal evolution of ER and urbanization in five GLRs in China to analyze the ER dynamic patterns along center−lakeside−periphery gradient.The Spatial Durbin Model(SDM)and Panel Threshold Model(PTM)were combined to reveal the spillover and threshold effects of urbanization in five GLRs.The results indicate that the ER in five GLRs declined with a rate of 21%from 2000 to 2020.There was a clear“center-periphery”contraction trend with low ER areas primarily spreading to human activity-concentrated regions such as lakesides,riversides,and road networks.Driven by economic and land urbanization,the average urbanization level increased from 0.06 to 0.13,where lakesides,riversides,and road networks were key areas undergoing expansion.The urbanization showed a noticeable negative spatial spillover effect on ER.Away from central lakes,the negative impacts on ER exhibited a two-phase decrease with the threshold of 81 km.This study contributes to the understanding of human-environment interactions by examining the ecological resilience response process of GLRs under the impact of urbanization.Based on a multidimensional“center−lakeside−periphery”analytical model,this study provides a strategic framework for ecological construction in GLRs in China,promoting sustainable development and adaptive capacity in vulnerable areas.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
The Qingtongxia Irrigation District in Ningxia is an important hydrological and ecological region.To assess its ecological environment quality from 2001 to 2021 across multiple scales and identify driving factors,a mo...The Qingtongxia Irrigation District in Ningxia is an important hydrological and ecological region.To assess its ecological environment quality from 2001 to 2021 across multiple scales and identify driving factors,a modified remote sensing ecological index(MRSEI)was developed by incorporating evapotranspiration.Spatial and temporal patterns were analyzed using the coefficient of variation,spatial autocorrelation,and semi-variogram methods,while influencing factors were explored via the optimal parameter geographical detector model.The MRSEI’s first principal component loadings and rankings aligned with those of RSEI(average contribution:81.31%),effectively reflecting spatiotemporal variations.At sub-irrigation district and landscape scales,ecological quality was slightly lower than at the district level but remained stable.Moderate and good ecological grades accounted for 36.28%and 33.38%of the area,respectively,at the district scale,and the moderate grade reached 70.48%on smaller scales.Spatial heterogeneity intensified with decreasing scale,and human activity lost explanatory power below a 5 km range.Human factors mainly drove ecological differentiation at the district scale,while natural factors dominated at finer scales.The MRSEI offers a novel tool for ecological assessment in arid/semi-arid areas and supports scale-adapted ecological protection strategies.展开更多
基金the auspices of the national key project(96-802-01).
文摘With the need in the global change research project for the land -use/land-cover change information, most international and regional research organization or groups have put amounts of efforts to improve of the dynamics monitoring and database updating techniques. With the pressure on nature environment from increasing population and decreasing farmland be- coming significant more and more in China, the farmland urban dynamics in historical and current times, even the change trends in the future, should be monitored and analyzed serving for regional and national social, economic and environmental sustain- able development in the long future. Based on spatial and temporal series of land -use/land-cover database resources, Chinese Academy of Sciences designed a sampling framework for monitoring farmland and urban area dynamics in regional and national level. In order to test the accuracy of the sampling schema for national and regional level, we took two provinces area into overall covered change detecting process with TM images data through being inter’Preted by digitalization on the screen. The result shows that our stratified random sampling schema is suitable for monitoring land -use/land-cover change at national and regional level with quick response, high accuracy and low expenses. The land-use/land-cover change (LUCC) information can update the LUTEA database for global change research during certain period so that the forecasting process and evaluating analysis on land resources and environment under human and natural driving force will get essential data and produce valuable conclusions.
文摘基于国际比较的地方空间规划的范围和工具研究An International Comparison of the Scope and Instruments of Local Spatial Planning源自:The TownPlanning Review,2024,95(2):197-217作者:MaciejJNowak,StefanieDühr,Sergio Peña,et al.推荐:申明锐,南京大学建筑与城市规划学院。shenmingr@nju.edu.cn.
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 Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDB0530000)the Discipline Construction Foundation of“Double World-class Project”.
文摘Laser wakefield accelerators(LWFAs)offer acceleration gradients up to 1000 times higher than those of conventional radio-frequency accelerators,offering a pathway to significantly more compact and cost-effective accelerator systems.This breakthrough opens up new possibilities for laboratory-scale light sources.All-optical inverse Compton scattering(AOCS)sources driven by LWFAs produce high-brightness,quasimonochromatic X rays with micrometer-scale source sizes,delivering the spatial coherence and resolution required for X-ray phase-contrast imaging(XPCI).These features position AOCS X-ray sources as promising tools for applications in biology,medicine,physics,and materials science.However,previous AOCS-based imaging studies have primarily focused on X-ray absorption imaging.In this work,we report successful experimental demonstrations of edge-enhanced in-line XPCI using energy-tunable,quasi-monochromatic AOCS X rays.With a spatial resolution of~20μm,our results clearly show the potential of high-resolution,AOCS-based XPCI applications.
基金supported by the National Nature Science Foundation of China(No.52402126)Shaanxi Province Qin Chuangyuan general window four chain integration project(No.2024PT-ZCK-09)+3 种基金Shaanxi Province military-civilian integration project(Shaanxi finance office【2024】22nd)Qinchuangyuan introducing high-level innovation and entrepreneurship talent projects(NO.QCYRCXM-2022-343)the China Postdoctoral Science Foundation(Grant Number:2025M772524)National Nature Science Foundation of China(22508239).
文摘Two-dimensional materials for flexible energy storage commonly facehuge challenges in limited active surface and hindered charge transport.Herein,wereport an innovative asymmetric pseudocapacitor based on synergistic design of modifiedMXene and graphene,integrating gas-induced rapid expansion technology andprecise surface chemical regulation methods.For graphene modification,rapid vaporizationinduces exfoliation and expansion of graphene oxide layers.Subsequently,pseudocapacitiveoxygen-containing groups were selectively introduced through acid oxidation,yielding expanded-and-oxidized graphene(OEG)for positive porous-nanopaperelectrode.For MXene modification,alkali-treated MXene underwent hydrazine assistance to facilitate gas expansion and-NH_(2)grafting,producing MXene-NH_(2)(NOM)for negative porous-nanopaper electrode.Density functional theory calculations show that-COOH moreeffectively modulate graphene’s electronic structure by inducing charge redistribution and creating active sites,thereby enhancing H^(+)adsorption and ion interactions compared to-OH.Meanwhile,-NH_(2)on MXene enable electron delocalization and dynamic Ti-N-H^(+)interactions,speeding up proton adsorption/desorption and boosting both pseudocapacitance and conductivity.Through collaborativeoptimized spatial architecture and surface properties,flexible OEGB and NOMB exhibited of 333.6 and 500.5 F g^(-1)at high mass loading,respectively.The assembled proton pseudocapacitor readily achieved energy and power densities of 58.9 Wh kg^(-1)and 3802 W kg^(-1),respectively,with excellent stability for potential applications.
基金support from the European Research Council(ERC)under the European Union’s Horizon 2020 research and innovation programme(Grant agreement No.819202)the Research Council of Finland’s Flagship Programme and Doctoral Education Pilot under project Digital Waters(Grant No.359248)funded by the Research Council of Finland's Flagship ProgrammeStrategic Research Council(SRC)through project‘Water&Food’(Grant No.365512).
文摘Endowed with opportunities from both land and ocean,coastal areas attract expanding human populations and economic activities.At the same time,they face growing societal and environmental pressures from both the above river catchments and the bordering sea due to climate change,ecosystem degradation,and expansion of built-up areas.Despite the accumulation of human population,economic activities,and environmental impacts,we lack social-ecological systems analysis on water-related risks to world’s coastal human population.To address this research gap,we analyze the spatial extent of six globally important water stressors to people within the world’s coastal zone(100 km from the coastal line)and classify this zone globally into 12 groups by distance from the coastline and elevation from the mean sea level.Adopting the approaches of the UN Sendai Framework and IPCC,we produce risk maps from the stressor maps by multiplying them with population exposure and vulnerability.For most risks,geographical hotspots are the Chinese coast,Bay of Bengal,Gujarat,and the Island of Java.The analysis reveals fundamental differences between water stressors and related risks,often mixed in scholarly literature.Both manifest specific geographic patterns and latitudinal profiles.Our study highlights the importance of high-resolution spatial analysis of vulnerability,exposure,and risks posed by water related stressors in the world’s coastal zone,in a manner prompted by key policy bodies to promote policy design and shared responsibility for managing stress-prone areas.
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.
文摘Background and Objectives:The perception of sound in the vertical plane supports spatial hearing by enabling listeners to detect sources located above and below.Sounds originating from both the front and back elevations along the mid-sagittal plane further contribute to a three-dimensional auditory experience.This study aimed to characterize the variability in vertical sound localization abilities among normal-hearing(NH)individuals using spatialized audio.Materials and Methods:Fifty-one NH participants(aged 18 to 35 years)completed three vertical localization tasks under headphones as part of a single-group,within-subject experimental study.These tasks included two-plane identification:(1)top-down localization,(2)front-back localization,and one discrimination task in the front plane.Hierarchical Cluster Analysis(HCA)was employed to identify distinct patterns in spatial localization profiles specific to the vertical-median plane.Fisher's Discriminant Function Analysis(FDA)was used to validate the accuracy of HCA and estimate classification error.Results:HCA revealed three distinct listener clusters:(1)cluster 1 with good performance across all three tasks,(2)cluster 2 with selective impairment in top-bottom identification,and(3)cluster 3 with selective deficits in front-back identification.FDA validated group membership of the clusters identified by the HCA,with a prediction accuracy of 98%.Conclusions:Individuals with clinically NH exhibited three distinct vertical localization profiles:uniform performers,those impaired in top-bottom identification,and those impaired in front-back identification.These profiles may be linked to the interplay between acoustic and non-acoustic perceptual factors.
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supported by the National Natural Science Foundation of China(U2344201 and 42101316)the Natural Science Foundation of Hunan Province,China(2022JJ40866)the Outstanding Youth Project of Education Bureau of Hunan Province,China(20B613)。
文摘Understanding the spatial distributions and corresponding variation mechanisms of key soil nutrients in fragile karst ecosystems can assist in promoting sustainable development.However,due to the implementation of ecological restoration initiatives such as land-use conversions,novel changes in the spatial characteristics of soil nutrients remain unknown.To address this gap,we explored nutrient variations and the drivers of the variation in the 0–15 cm topsoil layer using a regional-scale sampling method in a typical karst area in northwest Guangxi Zhuang Autonomous Region,Southwest China.Descriptive statistics,geostatistics,and spatial analysis were used to assess the soil nutrient variability.The results indicated that soil organic carbon(SOC),total nitrogen(TN),total phosphorus(TP),and total potassium(TK)concentrations showed moderate variations,with coefficients of variance being 0.60,0.60,0.71,and 0.72,respectively.Moreover,they demonstrated positive spatial autocorrelations,with global Moran's indices being 0.68,0.77,0.64,and 0.68,respectively.However,local Moran's index values were low,indicating large spatial variations in soil nutrients.The best-fitting semi-variogram models for SOC,TN,TP,and TK concentrations were spherical,Gaussian,exponential,and exponential,respectively.According to the classification criteria of the Second National Soil Census in China,SOC and TN concentrations were relatively sufficient,with the proportions of rich and very rich levels being up to 90.9 and 96.0%,respectively.TP concentration was in the mediumdeficient level,with the areas of medium and deficient levels accounting for 33.7 and 30.1%of the total,respectively.TK concentration was deficient,with the cumulative area of extremely deficient,very deficient,and deficient levels accounting for 87.6%of the total area.Consequently,the terrestrial ecosystems in the study area were more vulnerable to soil P and K than soil N deficiencies.Furthermore,variance partitioning analysis of the influencing factors showed that,except for the interactions,the single effect of other soil properties accounted more for soil nutrient variations than spatial and environmental variables.These results will aid in the future management of terrestrial ecosystems.
基金supported by National Key Research and Development Programme‘Frontier Research on Large Scientific Devices’Key Special Project(2024YFA1612000)Sino-German Science Foundation Program(M-0086)Yunnan Science and Technology Leading Talent Program(202105AB160001).
文摘The Chinese Giant Solar Telescope(CGST)low-dispersion spectrograph requires a large field-of-view(FOV)and high spatial resolution,which can be addressed by a carefully designed image slicer system.Our proposed design divides the rectangular 50″×20″FOV at the telescope focal plane into four 50″×5″subfields.Each subfield undergoes optical reconstruction using its independent collimator-camera system(F/36-F/25.79),achieving vertical alignment and focal reduction of subfields to form a pseudo-slit.Using tilt mirrors for scanning allows simultaneous acquisition of spectral data with both a large FOV and a high angular resolution of 0.05″.This resolves manufacturing challenges for an image slicer,avoiding the requirement for hundreds of elements,multi-angle configurations,and compact dimensions,and also provides effective technical support for engineering work on the CGST.
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funded by the National Natural Science Foundation of China(42571311).
文摘Central Asia is characterized by an arid climate and widespread desert distribution,with its sustainable development severely constrained by dust events.An objective understanding of the spatiotemporal patterns and driving forces of dust weather is highly important in this area.Based on the meteorological observations from 2000 to 2020,we examined the spatiotemporal characteristics of dust weather in the five Central Asian countries(Kazakhstan,Uzbekistan,Kyrgyzstan,Turkmenistan,and Tajikistan)via Theil-Sen trend analysis and Geodetector modeling method,quantitatively revealing the influence of environmental factors,such as temperature,precipitation,and vegetation,on the frequency of dust weather.The results showed that:(1)dust weather in Central Asia was mainly distributed in a large''dust belt''extending from west to east from northern part of the Caspian lowland desert,and concentrated in basins,plains,and other low-altitude areas.Strong dust weather mainly occurred in northern areas of the Aral Sea and southern edge of Central Asia,with a maximum annual frequency of 21.9%;(2)strong dust weather in Central Asia has fluctuated and slightly decreased since 2001.The highest frequency(1.1%)occurred in spring(from March to June);(3)from 2000 to 2020,changes such as spot shifting and shrinking occurred in the four main source areas(north of the Aral Sea,Kyzylkum Desert,Karakum Desert,and Garabogazköl Bay region),where sandstorms occurred in Central Asia,and northern Caspian lowland desert became the most important low-emission dust source in Central Asia;and(4)the combined effect of soil moisture and air temperature has the most significant influence on dust weather in Central Asia.This study provides a theoretical basis for sand prevention and sand control in Central Asia.In the future,Central Asia should focus on the rational utilization of land and water resources,and implement human interventions such as vegetation restoration and optimization of irrigation methods to curb further desertification in this area.
基金supported by the National Key Research and Development Program of China(2022YFC3204101 and 2023YFF0807202)the National Natural Science Foundation of China(U22A20570 and U2444221)+4 种基金the Youth Promotion Association of the Chinese Academy of Sciences(2021365)the Changsha Outstanding Innovative Youth Project,China(kq2305035)the Science,Technology and Innovation Platform Plan of Hunan Province,China(2022PT1010)the Major Scientific and Technological Projects of the Ministry of Water Resources,China(SKS-2022081)the Comprehensive Investigation and Potential Evaluation of Natural Resources Carbon Sink in Southern Hilly Region,China(DD20220880)。
文摘In floodplain wetlands,alterations in hydrological patterns resulting from climate change and human activities could potentially diminish the carbon sequestration capacity of the soils,thereby having a negative impact on global climate change.However,the magnitude of the influence of hydrological regime change on soil carbon remains inadequately monitored.To address this research gap,we collected 306 upper layer(0–20 cm)soil samples from the Dongting Lake floodplain between 2013 and 2022.The random forest(RF)algorithm was used to analyze the spatial distribution of soil organic carbon(SOC)in the upper soil layer of Dongting Lake floodplain and the impact of climate and hydrological changes in the past decade on surface SOC in the East Dongting Lake area was studied.In 2022,the SOC concentration of the Dongting Lake floodplain upper layer soil ranged from 3.34 to 17.67 g kg^(-1),averaging 10.43 g kg^(-1),with a corresponding SOC density of(2.65±0.49)kg m^(-2) and total SOC stock of 6.82 Tg C(2.87–13.48 Tg C).From 2013 to 2022,the SOC concentration of the upper soil layer of the East Dongting Lake area decreased from 18.37 to 10.82 g kg^(-1).This reduction could be attributed to climate and hydrological changes which reduce SOC input by reducing vegetation growth and accelerating SOC decomposition.Above 21.4 m elevation,the amount of SOC loss increased with elevation,the loss being related to the decline in Miscanthus community biomass and greater susceptibility of higher altitude areas to climate and hydrological changes.Our results highlight the need for strengthening wetland SOC management to increase SOC in the soils to help combat climate change.
文摘The field of artificial intelligence has advanced significantly in recent years,but achieving a human-like or Artificial General Intelligence(AGI)remains a theoretical challenge.One hypothesis suggests that a key issue is the formalisation of extracting meaning from information.Meaning emerges through a three-stage interpretative process,where the spectrum of possible interpretations is collapsed into a singular outcome by a particular context.However,this approach currently lacks practical grounding.In this research,we developed a model based on contexts,which applies interpretation principles to the visual information to address this gap.The field of computer vision and object recognition has progressed essentially with artificial neural networks,but these models struggle with geometrically transformed images,such as those that are rotated or shifted,limiting their robustness in real-world applications.Various approaches have been proposed to address this problem.Some of them(Hu moments,spatial transformers,capsule networks,attention and memory mechanisms)share a conceptual connection with the contextual model(CM)discussed in this study.This paper investigates whether CM principles are applicable for interpreting rotated images from the MNIST and Fashion MNIST datasets.The model was implemented in the Rust programming language.It consists of a contextual module and a convolutional neural network(CNN).The CMwas trained on the rotated Mono Icons dataset,which is significantly different from the testing datasets.The CNN module was trained on the original MNIST and Fashion MNIST datasets for interpretation recognition.As a result,the CM was able to recognise the original datasets but encountered rotated images only during testing.The findings show that the model effectively interpreted transformed images by considering them in all available contexts and restoring their original form.This provides a practical foundation for further development of the contextual hypothesis and its relation to theAGI domain.
基金supported by the National Natural Science Foundation of China(Grants No.42301226,42271209 and 42471199)the Fundamental Research Funds for the Central Universities(Grant No.2024CDJXY014)+2 种基金the Natural Science Foundation of Jiangxi Province(Grant No.20242BAB25170)Special Funds for Water Resources in Jiangxi Province(Science and Technology Projects)(Grant No.202425YBKT16)the Young Talent Cultivation and Innovation Fund Project of Nanchang University(Grant No.XX202506030028).
文摘Great Lakes Regions(GLRs)in China often confront landscape fragmentation,wetland degradation,and ecological resilience(ER)losses owing to extensive and intensive urbanization.In GLRs,however,the ER responses to urbanization remain unclear.This study explored the spatiotemporal evolution of ER and urbanization in five GLRs in China to analyze the ER dynamic patterns along center−lakeside−periphery gradient.The Spatial Durbin Model(SDM)and Panel Threshold Model(PTM)were combined to reveal the spillover and threshold effects of urbanization in five GLRs.The results indicate that the ER in five GLRs declined with a rate of 21%from 2000 to 2020.There was a clear“center-periphery”contraction trend with low ER areas primarily spreading to human activity-concentrated regions such as lakesides,riversides,and road networks.Driven by economic and land urbanization,the average urbanization level increased from 0.06 to 0.13,where lakesides,riversides,and road networks were key areas undergoing expansion.The urbanization showed a noticeable negative spatial spillover effect on ER.Away from central lakes,the negative impacts on ER exhibited a two-phase decrease with the threshold of 81 km.This study contributes to the understanding of human-environment interactions by examining the ecological resilience response process of GLRs under the impact of urbanization.Based on a multidimensional“center−lakeside−periphery”analytical model,this study provides a strategic framework for ecological construction in GLRs in China,promoting sustainable development and adaptive capacity in vulnerable areas.
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 Key Research&Development Program of China,No.2021YFC3201201Ningxia Key Research and Development Program(Special Talents),No.2023BSB03021+1 种基金Natural Science Foundation of Ningxia,No.2023AAC05014University First-Class Discipline Construction Project of Ningxia,No.NXYLXK2021A03。
文摘The Qingtongxia Irrigation District in Ningxia is an important hydrological and ecological region.To assess its ecological environment quality from 2001 to 2021 across multiple scales and identify driving factors,a modified remote sensing ecological index(MRSEI)was developed by incorporating evapotranspiration.Spatial and temporal patterns were analyzed using the coefficient of variation,spatial autocorrelation,and semi-variogram methods,while influencing factors were explored via the optimal parameter geographical detector model.The MRSEI’s first principal component loadings and rankings aligned with those of RSEI(average contribution:81.31%),effectively reflecting spatiotemporal variations.At sub-irrigation district and landscape scales,ecological quality was slightly lower than at the district level but remained stable.Moderate and good ecological grades accounted for 36.28%and 33.38%of the area,respectively,at the district scale,and the moderate grade reached 70.48%on smaller scales.Spatial heterogeneity intensified with decreasing scale,and human activity lost explanatory power below a 5 km range.Human factors mainly drove ecological differentiation at the district scale,while natural factors dominated at finer scales.The MRSEI offers a novel tool for ecological assessment in arid/semi-arid areas and supports scale-adapted ecological protection strategies.
