As an advanced device for observing atmospheric winds,the spaceborne Doppler Asymmetric Spatial Heterodyne(DASH)interferometer also encounters challenges associated with phase distortion,par-ticularly in limb sounding...As an advanced device for observing atmospheric winds,the spaceborne Doppler Asymmetric Spatial Heterodyne(DASH)interferometer also encounters challenges associated with phase distortion,par-ticularly in limb sounding scenarios.This paper discusses interferogram modeling and phase distortion cor-rection techniques for spaceborne DASH interferometers.The modeling of phase distortion interferograms with and without Doppler shift for limb observation was conducted,and the effectiveness of the analytical expression was verified through numerical simulation.The simulation results indicate that errors propagate layer by layer while using the onion-peeling inversion algorithm to handle phase-distorted interferograms.In contrast,the phase distortion correction algorithm can achieve effective correction.This phase correction method can be successfully applied to correct phase distortions in the interferograms of the spaceborne DASH interferometer,providing a feasible solution to enhance its measurement accuracy.展开更多
The swelling behavior and stability in solid electrolyte interphase(SEI)have been proved to determine the battery cycle life.A high swollen,unstable SEI shows a high permeability to electrolyte,which results in the ra...The swelling behavior and stability in solid electrolyte interphase(SEI)have been proved to determine the battery cycle life.A high swollen,unstable SEI shows a high permeability to electrolyte,which results in the rapid battery performance degradation.Here,we customize two SEIs with different spatial structures(bilayer and mosaic)by simply regulating the proportion of additive fluoroethylene carbonate.Surprisingly,due to the uniform distribution of dense inorganic nano-crystals in the inner,the bilayer SEI exhibits low-swelling and excellent mechanical properties,so the undesirable side reactions of the electrolyte are effectively suppressed.In addition,we put forward the growth rate of swelling ratio(GSR)as a key indicator to reveal the swelling change in SEI.The GSR of bilayer SEI merely increases from1.73 to 3.16 after the 300th cycle,which enables the corresponding graphite‖Li battery to achieve longer cycle stability.The capacity retention is improved by 47.5% after 300 cycles at 0.5 C.The correlation among SEI spatial structure,swelling behavior,and battery performance provides a new direction for electrolyte optimization and interphase structure design of high energy density batteries.展开更多
Carbon emissions resulting from energy consumption have become a pressing issue for governments worldwide.Accurate estimation of carbon emissions using satellite remote sensing data has become a crucial research probl...Carbon emissions resulting from energy consumption have become a pressing issue for governments worldwide.Accurate estimation of carbon emissions using satellite remote sensing data has become a crucial research problem.Previous studies relied on statistical regression models that failed to capture the complex nonlinear relationships between carbon emissions and characteristic variables.In this study,we propose a machine learning algorithm for carbon emissions,a Bayesian optimized XGboost regression model,using multi-year energy carbon emission data and nighttime lights(NTL)remote sensing data from Shaanxi Province,China.Our results demonstrate that the XGboost algorithm outperforms linear regression and four other machine learning models,with an R^(2)of 0.906 and RMSE of 5.687.We observe an annual increase in carbon emissions,with high-emission counties primarily concentrated in northern and central Shaanxi Province,displaying a shift from discrete,sporadic points to contiguous,extended spatial distribution.Spatial autocorrelation clustering reveals predominantly high-high and low-low clustering patterns,with economically developed counties showing high-emission clustering and economically relatively backward counties displaying low-emission clustering.Our findings show that the use of NTL data and the XGboost algorithm can estimate and predict carbon emissionsmore accurately and provide a complementary reference for satellite remote sensing image data to serve carbon emission monitoring and assessment.This research provides an important theoretical basis for formulating practical carbon emission reduction policies and contributes to the development of techniques for accurate carbon emission estimation using remote sensing data.展开更多
Elucidating the complex dynamic cellular organization in the hypothalamus is critical for understanding its role in coordinating fundamental body functions. Over the past decade, single-cell and spatial omics technolo...Elucidating the complex dynamic cellular organization in the hypothalamus is critical for understanding its role in coordinating fundamental body functions. Over the past decade, single-cell and spatial omics technologies have significantly evolved, overcoming initial technical challenges in capturing and analyzing individual cells. These high-throughput omics technologies now offer a remarkable opportunity to comprehend the complex spatiotemporal patterns of transcriptional diversity and cell-type characteristics across the entire hypothalamus. Current single-cell and single-nucleus RNA sequencing methods comprehensively quantify gene expression by exploring distinct phenotypes across various subregions of the hypothalamus. However, single-cell/single-nucleus RNA sequencing requires isolating the cell/nuclei from the tissue, potentially resulting in the loss of spatial information concerning neuronal networks. Spatial transcriptomics methods, by bypassing the cell dissociation, can elucidate the intricate spatial organization of neural networks through their imaging and sequencing technologies. In this review, we highlight the applicative value of single-cell and spatial transcriptomics in exploring the complex molecular-genetic diversity of hypothalamic cell types, driven by recent high-throughput achievements.展开更多
Coking industry is a potential source of heavy metals(HMs)pollution.However,its impacts to the groundwater of surrounding residential areas have not been well understood.This study investigated the pollution character...Coking industry is a potential source of heavy metals(HMs)pollution.However,its impacts to the groundwater of surrounding residential areas have not been well understood.This study investigated the pollution characteristics and health risks of HMs in groundwater nearby a typical coking plant.Nine HMs including Fe,Zn,Mo,As,Cu,Ni,Cr,Pb and Cd were analyzed.The average concentration of total HMswas higher in the nearby area(244.27μg/L)than that of remote area away the coking plant(89.15μg/L).The spatial distribution of pollution indices including heavy metal pollution index(HPI),Nemerow index(NI)and contamination degree(CD),all demonstrated higher values at the nearby residential areas,suggesting coking activity could significantly impact the HMs distribution characteristics.Four sources of HMs were identified by Positive Matrix Factorization(PMF)model,which indicated coal washing and coking emission were the dominant sources,accounted for 40.4%,and 31.0%,respectively.Oral ingestionwas found to be the dominant exposure pathway with higher exposure dose to children than adults.Hazard quotient(HQ)values were below 1.0,suggesting negligible non-carcinogenic health risks,while potential carcinogenic risks were from Pb and Ni with cancer risk(CR)values>10−6.Monte Carlo simulation matched well with the calculated results with HMs concentrations to be the most sensitive parameters.This study provides insights into understanding how the industrial coking activities can impact the HMs pollution characteristics in groundwater,thus facilitating the implement of HMs regulation in coking industries.展开更多
Increased exposure to campus green spaces can make a positive contribution to the healthy development of students.However,understanding of the current supply of campus green space(CGS)and its drivers at different educ...Increased exposure to campus green spaces can make a positive contribution to the healthy development of students.However,understanding of the current supply of campus green space(CGS)and its drivers at different education stages is still limited.A new framework was established to evaluate the spatial heterogeneity and its influencing factors across all education stages(kindergarten,primary school,middle school,college)in 1100 schools at the urban scale of Xi’an,China.The research results show that:1)CGS is lower in the Baqiao district and higher in the Yanta and Xincheng districts of Xi’an City.‘Green wealthy schools are mainly concentrated in the Weiyang,Chang’an and Yanta districts.2)CGS of these schools in descending order is college(31.40%)>kindergarten(18.32%)>middle school(13.56%)>primary school(10.70%).3)Colleges have the most recreation sites(n(number)=2),the best education levels(11.93 yr),and the lowest housing prices(1.18×10^(4) yuan(RMB)/m^(2));middle schools have the highest public expenditures(3.97×10^(9) yuan/yr);primary schools have the highest CGS accessibility(travel time gap(TTG)=31.33).4)Multiscale Geographically Weighted Regression model and Spearman’s test prove that recreation sites have a significant positive impact on college green spaces(0.28–0.35),and education level has a significant positive impact on kindergarten green spaces(0.16–0.24).This research framework provides important insights for the assessment of school greening initiatives aimed at fostering healthier learning environments for future generations.展开更多
Mineralogical data are presented for the peridotite xenoliths from Miocene(~19 Ma)Qingyuan basalts in the eastern North China Craton(NCC),with the aim of constraining on property of the sub-continental lithospheric ma...Mineralogical data are presented for the peridotite xenoliths from Miocene(~19 Ma)Qingyuan basalts in the eastern North China Craton(NCC),with the aim of constraining on property of the sub-continental lithospheric mantle(SCLM)beneath the northern Tan-Lu fault zone(TLFZ)during the Cenozoic.The Qingyuan peridotites are dominated by spinel lherzolites with moderate-Mg^(#)olivines(89.4 to 91.2),suggesting that the regional SCLM is mainly transitional and fertile.Light rare earth element(LREE)-depleted,slightly depleted and enriched clinopyroxenes(Cpx)are identified in different peridotites.Chemical compositions of the LREE-enriched Cpx and the presence of phlogopite suggest that the Qingyuan SCLM has experienced silicate-related metasomatism.The synthesis of available mineral chemical data of the mantle xenoliths across the NCC confirms the SCLM beneath the NCC is highly heterogeneous in time and space.The Mesozoic–Cenozoic SCLM beneath the TLFZ and neighboring regions are more fertile and thinner than that beneath the region away from the fault zone.The fertile and refractory peridotite xenoliths experienced varying degrees of silicate and carbonatite metasomatism,respectively.The spatial-temporal lithospheric mantle heterogeneity in composition,age and thickness suggest that the trans-lithosphere fault zone played an important role in heterogeneous replacement of refractory cratonic lithospheric mantle.展开更多
The study aims to investigate county-level variations of the COVID-19 disease and vaccination rate. The COVID-19 data was acquired from usafact.org, and the vaccination records were acquired from the Ohio vaccination ...The study aims to investigate county-level variations of the COVID-19 disease and vaccination rate. The COVID-19 data was acquired from usafact.org, and the vaccination records were acquired from the Ohio vaccination tracker dashboard. GIS-based exploratory analysis was conducted to select four variables (poverty, black race, population density, and vaccination) to explain COVID-19 occurrence during the study period. Consequently, spatial statistical techniques such as Moran’s I, Hot Spot Analysis, Spatial Lag Model (SLM), and Spatial Error Model (SEM) were used to explain the COVID-19 occurrence and vaccination rate across the 88 counties in Ohio. The result of the Local Moran’s I analysis reveals that the epicenters of COVID-19 and vaccination followed the same patterns. Indeed, counties like Summit, Franklin, Fairfield, Hamilton, and Medina were categorized as epicenters for both COVID-19 occurrence and vaccination rate. The SEM seems to be the best model for both COVID-19 and vaccination rates, with R2 values of 0.68 and 0.70, respectively. The GWR analysis proves to be better than Ordinary Least Squares (OLS), and the distribution of R2 in the GWR is uneven throughout the study area for both COVID-19 cases and vaccinations. Some counties have a high R2 of up to 0.70 for both COVID-19 cases and vaccinations. The outcomes of the regression analyses show that the SEM models can explain 68% - 70% of COVID-19 cases and vaccination across the entire counties within the study period. COVID-19 cases and vaccination rates exhibited significant positive associations with black race and poverty throughout the study area.展开更多
This study contests the prevalent perception of graffiti writing,especially tagging and bombing,as meaningless vandalism.It contends that graffiti is a form of expression with intrinsic political implications.Leveragi...This study contests the prevalent perception of graffiti writing,especially tagging and bombing,as meaningless vandalism.It contends that graffiti is a form of expression with intrinsic political implications.Leveraging the notion of spatial justice and Jacques Ranciere's philosophy,I demonstrate how graffiti reclaims urban visibility against the commercial monopoly of visibility in public spaces and challenges the inequitable allocation of opportunities for self-expression in modern cities.Despite writers'common denial of political motives,their actions may be interpreted as manifestations of resistance within wider sociospatial conflicts.This study situates grffti within discussions of political art,spatial commodification,and everyday resistance,proposing a normative framework for viewing the art of the urban signature as an activity that redefines"the community that speaks."展开更多
Glial cells play crucial roles in regulating physiological and pathological functions,including sensation,the response to infection and acute injury,and chronic neurodegenerative disorders.Glial cells include astrocyt...Glial cells play crucial roles in regulating physiological and pathological functions,including sensation,the response to infection and acute injury,and chronic neurodegenerative disorders.Glial cells include astrocytes,microglia,and oligodendrocytes in the central nervous system,and satellite glial cells and Schwann cells in the peripheral nervous system.Despite the greater understanding of glial cell types and functional heterogeneity achieved through single-cell and single-nucleus RNA sequencing in animal models,few studies have investigated the transcriptomic profiles of glial cells in the human spinal cord.Here,we used high-throughput single-nucleus RNA sequencing and spatial transcriptomics to map the cellular and molecular heterogeneity of astrocytes,microglia,and oligodendrocytes in the human spinal cord.To explore the conservation and divergence across species,we compared these findings with those from mice.In the human spinal cord,astrocytes,microglia,and oligodendrocytes were each divided into six distinct transcriptomic subclusters.In the mouse spinal cord,astrocytes,microglia,and oligodendrocytes were divided into five,four,and five distinct transcriptomic subclusters,respectively.The comparative results revealed substantial heterogeneity in all glial cell types between humans and mice.Additionally,we detected sex differences in gene expression in human spinal cord glial cells.Specifically,in all astrocyte subtypes,the levels of NEAT1 and CHI3L1 were higher in males than in females,whereas the levels of CST3 were lower in males than in females.In all microglial subtypes,all differentially expressed genes were located on the sex chromosomes.In addition to sex-specific gene differences,the levels of MT-ND4,MT2A,MT-ATP6,MT-CO3,MT-ND2,MT-ND3,and MT-CO_(2) in all spinal cord oligodendrocyte subtypes were higher in females than in males.Collectively,the present dataset extensively characterizes glial cell heterogeneity and offers a valuable resource for exploring the cellular basis of spinal cordrelated illnesses,including chronic pain,amyotrophic lateral sclerosis,and multiple sclerosis.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
By introducing noncanonical vortex pairs to partially coherent beams, spatial correlation singularity (SCS) and orbital angular momenta (OAM) of the resulting beams are studied using the Fraunhofer diffraction integra...By introducing noncanonical vortex pairs to partially coherent beams, spatial correlation singularity (SCS) and orbital angular momenta (OAM) of the resulting beams are studied using the Fraunhofer diffraction integral. The effect of noncanonical strength, off-axis distance and vortex sign on spatial correlation singularities in far field is stressed. Furthermore, far-field OAM spectra and densities are also investigated, and the OAM detection and crosstalk probabilities are discussed. The results show that the number of dislocations of SCS always equals the sum of absolute values of topological charges for canonical or noncanonical vortex pairs. Although the sum of the product of each OAM mode and its power weight equals the algebraic sum of topological charges for canonical vortex pairs, the relationship no longer holds in the noncanonical case except for opposite-charge vortex pairs. The changes of off-axis distance, noncanonical strength or coherence length can lead to a more dominant power in adjacent mode than that in center detection mode, which also indicates that crosstalk probabilities of adjacent modes exceed the center detection probability. This work may provide potential applications in OAM-based optical communication, imaging, sensing and computing.展开更多
The exploration of the variability of spatial spillovers of ecosystem services(ESs)across scales is essential for sustainable regional development.Using advanced models such as In VEST,Geodetector,MGWR,and SLM/SEM/SDB...The exploration of the variability of spatial spillovers of ecosystem services(ESs)across scales is essential for sustainable regional development.Using advanced models such as In VEST,Geodetector,MGWR,and SLM/SEM/SDB,this study investigates spatial heterogeneity and cross-regional effects on ESs at the raster and county scales.Key findings from 2000 to 2020 include an upward trend in ESs,with pronounced regional variations.The southern Yellow River Basin(YRB)shows higher levels of water yield,carbon sequestration,soil retention,and habitat quality,while the northern areas score lower,except for food provisioning in central and lower regions.The overall ES index has risen,particularly in the southern part,aligning with China's ecological patterns and showing significant cross-regional benefits.At various scales,natural elements,landscape configurations,and human influences significantly impact ESI,with different cross-regional effects.While natural and landscape indices demonstrate substantial cross-regional impacts at the raster scale,human influence is more apparent at the county scale.The identified cross-regional impacts underscore the interconnectedness of regional ES and sustainability,extending to nearby areas.Spatial management and planning may be limited by zoning and regulations.This study underscores regional ecosystem spatial spillovers and cross-scale knowledge differences and linkages,introducing new perspectives and methods for spatial planning in watersheds to support sustainable ecosystem optimisation.展开更多
This study focuses on urgent research on restoring and enhancing carbon storage capacity in the Beibu Gulf Urban Agglomer-ation of China,a key area in the‘Belt and Road’Initiative,which aligns with carbon peaking an...This study focuses on urgent research on restoring and enhancing carbon storage capacity in the Beibu Gulf Urban Agglomer-ation of China,a key area in the‘Belt and Road’Initiative,which aligns with carbon peaking and neutrality goals.This research ana-lyzes the spatial characteristics of carbon metabolism from 2000 to 2020 and uses models to identify stable carbon sink areas,positive carbon flow corridors,and carbon sequestration nodes.The goal is to construct a carbon metabolism spatial security pattern(CMSSP)and propose territorial ecological restoration strategies under different development demand scenarios.The results show the following:1)in 2020,the study area’s carbon sink decreased by 8.29×10^(4) t C/yr compared with that in 2010 and by 10.83×10^(4) t C/yr compared with that in 2000.High-carbon sinks were found mainly in mountainous areas,whereas low-carbon sinks are concentrated in urban con-struction land,rural residential areas,and land margins.2)From 2000 to 2020,the spatial security pattern of carbon metabolism tended to be‘high in the middle of the east and west and low in the gulf.’In 2000,2010,and 2020,16 stable carbon sinks were identified.The carbon energy flow density in Guangxi was greater than that in Guangdong and Hainan,with positive carbon flow corridors located primarily in Guangxi and Guangdong.The number of carbon sequestration nodes remained stable at approximately 15,mainly in Guangxi and Hainan.3)Scenario simulations revealed that under the Nature-based mild restoration scenario,the carbon sink rate will reach 611.85×10^(4) t C/yr by 2030 and increase to 612.45×10^(4) t C/yr by 2060,with stable carbon sinks increasing to 18.In the restora-tion scenario based on Anti-globalization,the carbon sink will decrease from 610.24×10^(4) t C/yr in 2030 to 605.19×10^(4) t C/yr in 2060,with the disappearance of some positive carbon flow corridors and stable carbon sinks.Under the Human-based sustainable restoration scenario,the carbon sink area will decrease from 607.00×10^(4) t C/yr in 2030 to 596.39×10^(4) t C/yr in 2060,with carbon sink areas frag-menting and positive carbon flow corridors becoming less dense.4)On the basis of the current and predicted CMSSPs,this study ex-plores spatial ecological restoration strategies for high-carbon storage areas in bay urban agglomerations at four levels:the land control region,urban agglomeration structure system,carbon sink structure and bay structure control region.展开更多
This study investigates the spatial courting between digital economic signs and local monetary overall performance throughout ten provinces in Sumatra,Indonesia,from 2019 to 2022.As digitalization hastens economic and...This study investigates the spatial courting between digital economic signs and local monetary overall performance throughout ten provinces in Sumatra,Indonesia,from 2019 to 2022.As digitalization hastens economic and business sports,devices together with fintech lending,e-cash,debit card usage,and e-commerce are increasingly more diagnosed as capability drivers of regional increase.But,the unequal distribution of digital infrastructure and monetary literacy across regions raises issues approximately the inclusivity of these benefits.constructing upon current findings by using Miranti et al.(2024),this research employs spatial econometric fashions-particularly the Spatial Lag model(SLM)and Spatial mistakes model(SEM)-to evaluate how digital variables influence provincial financial overall performance while accounting for spatial spillover consequences.The results reveal that fintech lending and debit card usage exert a positive and significant impact on economic growth,whereas the effect of e-money is negative,suggesting potential substitution effects or access constraints.Spatial dependency is also evident,as demonstrated by the significant lambda coefficient in the SEM model.These findings highlight the importance of spatially coordinated digital policies,particularly in addressing disparities and enhancing digital financial inclusion.The study concludes with policy recommendations aimed at fostering inclusive and spatially balanced digital economic development in Sumatra.展开更多
Cities are important carriers of green innovation.The foundation for accelerating China's ecological civilization construction and fostering regionally coordinated and sustainable development is quantitative analy...Cities are important carriers of green innovation.The foundation for accelerating China's ecological civilization construction and fostering regionally coordinated and sustainable development is quantitative analysis of the spatial evolution pattern and influencing factors of urban green innovation,as well as revealing the development differences between regions.This study's research object includes 284 Chinese cities that are at the prefecture level or above,excluding Xizang,Hong Kong,Macao,and Taiwan of China due to incomplete data.The spatial evolution characteristics of urban green innovation in China between 2005 and 2021 are comprehensively described using the gravity center model and boxplot analysis.The factors that affect urban green innovation are examined using the spatial Durbin model(SDM).The findings indicate that:1)over the period of the study,the gravity center of urban green innovation in China has always been distributed in the Henan-Anhui border region,showing a migration characteristic of‘initially shifting northeast,subsequently southeast',and the migration speed has gradually increased.2)Although there are also noticeable disparities in east-west,the north-south gap is the main cause of the shift in China's urban green innovation gravity center.The primary areas of urban green innovation in China are the cities with green innovation levels higher than the median.3)The main influencing factor of urban green innovation is the industrial structure level.The effect of the financial development level,the government intervention level,and the openness to the outside world degree on urban green innovation is weakened in turn.The environmental regulation degree is not truly influencing urban green innovation.The impact of various factors on green innovation across cities of different sizes,exhibiting heterogeneity.This study is conducive to broadening the academic community's comprehension of the spatial evolution characteristics of urban green innovation and offering a theoretical framework for developing policies for the all-encompassing green transformation of social and economic growth.展开更多
Located in Nanhai Town,Songzi City,Hubei Province,Xiaonanhai Lake is the largest natural lake in Songzi.It was once severely polluted due to the discharge of urban and rural domestic sewage,disorderly development of a...Located in Nanhai Town,Songzi City,Hubei Province,Xiaonanhai Lake is the largest natural lake in Songzi.It was once severely polluted due to the discharge of urban and rural domestic sewage,disorderly development of agricultural planting,unregulated aquaculture,and poultry farming.However,relevant esti-mations of the pollutant content in its sediment have not been carried out.This study analyzed the spatial patterns of heavy metal pollution and eutrophication at 36 water sampling sites in the Xiaonanhai Lake area,focusing on eight heavy metals:Cd,Cr,Cu,Ni,As,Pb,Hg,and Zn.The nutrient status of the lake area was evaluated using the nitrogen-phosphorus comprehensive pollution index,and heavy metal pollution status of the lake area was evaluated using geo-accumulation and the potential ecological risk index.Spatial autocorrelation analysis revealed the spatial correlation and aggregation of eutrophication levels in Xiaonanhai Lake.The results showed that the overall trophic state of the Xiaonanhai Lake area was moderate eutrophication,with a gradually decreasing eutrophication level from north to south.The Chengnan Wastewater Treatment Plant in the northern part of the lake area and surface source pollution from aquaculture were the main nitrogen and phosphorus sources.The overall eco-logical risk index of heavy metal pollution was medium and gradually weakened from north to south,consistent with the thickness of the bottom mud.The heavy metal pollution load was mainly precipitated from the bottom mud in the lake area.The eutrophication and heavy metal pollution levels in the lake area showed significant positive spatial autocorrelation,the influence range of the regional eutrophication level was small,and the spatial heterogeneity of the eutrophication and heavy metal pollution levels in Xiaonanhai Lake was relatively high.The northern part of the lake was a hotspot(high/high aggregation)of eutrophication(p<0.01)while the southern part was a cold spot(low/low concentration;p<0.05).The middle and northern part of the lake area was the hot spot(high/high concentration)of heavy metal pollution level(p<0.1)while the southern part was the cold spot(low/low concentration;p<0.1).Therefore,when carrying out water environment management in Xiaonanhai Lake,the northern area and the middle area should be prioritized for eutrophication prevention and control and dredging.展开更多
In view of the weak ability of the convolutional neural networks to explicitly learn spatial invariance and the probabilistic loss of discriminative features caused by occlusion and background interference in pedestri...In view of the weak ability of the convolutional neural networks to explicitly learn spatial invariance and the probabilistic loss of discriminative features caused by occlusion and background interference in pedestrian re-identification tasks,a person re-identification method combining spatial feature learning and multi-granularity feature fusion was proposed.First,an attention spatial transformation network(A-STN)is proposed to learn spatial features and solve the problem of misalignment of pedestrian spatial features.Then the network was divided into a global branch,a local coarse-grained fusion branch,and a local fine-grained fusion branch to extract pedestrian global features,coarse-grained fusion features,and fine-grained fusion features,respectively.Among them,the global branch enriches the global features by fusing different pooling features.The local coarse-grained fusion branch uses an overlay pooling to enhance each local feature while learning the correlation relationship between multi-granularity features.The local fine-grained fusion branch uses a differential pooling to obtain the differential features that were fused with global features to learn the relationship between pedestrian local features and pedestrian global features.Finally,the proposed method was compared on three public datasets:Market1501,DukeMTMC-ReID and CUHK03.The experimental results were better than those of the comparative methods,which verifies the effectiveness of the proposed method.展开更多
To reduce the spatial simulation error generated by the finite difference method,previous researchers compute the optimal finite-difference weights always by minimizing the error of spatial dispersion relation.However...To reduce the spatial simulation error generated by the finite difference method,previous researchers compute the optimal finite-difference weights always by minimizing the error of spatial dispersion relation.However,we prove that the spatial simulation error of the finite difference method is associated with the dot product of the spatial dispersion relation of the finite-difference weights and the spectrum of the seismic wavefield.Based on the dot product relation,we construct a L_(2) norm cost function to minimize spatial simulation error.For solving this optimization problem,the seismic wavefield infor-mation in wavenumber region is necessary.Nevertheless,the seismic wavefield is generally obtained by costly forward modeling techniques.To reduce the computational cost,we substitute the spectrum of the seismic wavelet for the spectrum of the seismic wavefield,as the seismic wavelet plays a key role in determining the seismic wavefield.In solving the optimization problem,we design an exhaustive search method to obtain the solution of the L_(2) norm optimization problem.After solving the optimization problem,we are able to achieve the finite-difference weights that minimize spatial simulation error.In theoretical error analyses,the finite-difference weights from the proposed method can output more accurate simulation results compared to those from previous optimization algorithms.Furthermore,we validate our method through numerical tests with synthetic models,which encompass homogenous/inhomogeneous media as well as isotropic and anisotropic media.展开更多
Latitudinal patterns of treeβ-diversity reveal important insights into the biogeographical processes that influence forest ecosystems.Although previous studies have extensively documentedβ-diversity within relativel...Latitudinal patterns of treeβ-diversity reveal important insights into the biogeographical processes that influence forest ecosystems.Although previous studies have extensively documentedβ-diversity within relatively small spatial extents,the potential drivers ofβ-diversity along latitudinal gradients are still not well understood at larger spatial extents.In this study,we determined whether treeβ-diversity is correlated with latitude in forests of southeastern China,and if so,what ecological processes contribute to these patterns of treeβ-diversity.We specifically aimed to disentangle the relative contributions from interspecific aggregation and environmental filtering across various spatial extents.We delineated regional communities comprising multiple nearby national forest inventory(NFI)plots around random focal plots.The number of NFI plots in a regional community served as a surrogate for spatial extent.We also used a null model to simulate randomly assembled communities and quantify the deviation(β-deviation)between observed and expectedβ-diversity.We found thatβ-diversity decreased along a latitudinal gradient and that this pattern was clearer at larger spatial extents.In addition,latitudinal patterns ofβ-deviation were explained by the degree of species spatial aggregation.We also identified environmental factors that driveβ-deviation in these forests,including precipitation,seasonality,and temperature variation.At larger spatial extents,these environmental variables explained up to 84%of theβ-deviation.Our results reinforce that ecological processes are scale-dependent and collectively contribute to theβ-gradient in subtropical forests.We recommend that conservation efforts maintain diverse forests and heterogeneous environments at multiple spatial extents to mitigate the adverse effects of climate change.展开更多
文摘As an advanced device for observing atmospheric winds,the spaceborne Doppler Asymmetric Spatial Heterodyne(DASH)interferometer also encounters challenges associated with phase distortion,par-ticularly in limb sounding scenarios.This paper discusses interferogram modeling and phase distortion cor-rection techniques for spaceborne DASH interferometers.The modeling of phase distortion interferograms with and without Doppler shift for limb observation was conducted,and the effectiveness of the analytical expression was verified through numerical simulation.The simulation results indicate that errors propagate layer by layer while using the onion-peeling inversion algorithm to handle phase-distorted interferograms.In contrast,the phase distortion correction algorithm can achieve effective correction.This phase correction method can be successfully applied to correct phase distortions in the interferograms of the spaceborne DASH interferometer,providing a feasible solution to enhance its measurement accuracy.
基金supported by the National Natural Science Foundation of China(22369011)the Gansu Key Research and Development Program(23YFGA0053 and 24YFGA025)the Hongliu Outstanding Youth Talent Support Program of Lanzhou University of Technology and Postgraduate research exploration project of Lanzhou University of Technology(256017)。
文摘The swelling behavior and stability in solid electrolyte interphase(SEI)have been proved to determine the battery cycle life.A high swollen,unstable SEI shows a high permeability to electrolyte,which results in the rapid battery performance degradation.Here,we customize two SEIs with different spatial structures(bilayer and mosaic)by simply regulating the proportion of additive fluoroethylene carbonate.Surprisingly,due to the uniform distribution of dense inorganic nano-crystals in the inner,the bilayer SEI exhibits low-swelling and excellent mechanical properties,so the undesirable side reactions of the electrolyte are effectively suppressed.In addition,we put forward the growth rate of swelling ratio(GSR)as a key indicator to reveal the swelling change in SEI.The GSR of bilayer SEI merely increases from1.73 to 3.16 after the 300th cycle,which enables the corresponding graphite‖Li battery to achieve longer cycle stability.The capacity retention is improved by 47.5% after 300 cycles at 0.5 C.The correlation among SEI spatial structure,swelling behavior,and battery performance provides a new direction for electrolyte optimization and interphase structure design of high energy density batteries.
基金supported by the Key Research and Development Program in Shaanxi Province,China(No.2022ZDLSF07-05)the Fundamental Research Funds for the Central Universities,CHD(No.300102352901)。
文摘Carbon emissions resulting from energy consumption have become a pressing issue for governments worldwide.Accurate estimation of carbon emissions using satellite remote sensing data has become a crucial research problem.Previous studies relied on statistical regression models that failed to capture the complex nonlinear relationships between carbon emissions and characteristic variables.In this study,we propose a machine learning algorithm for carbon emissions,a Bayesian optimized XGboost regression model,using multi-year energy carbon emission data and nighttime lights(NTL)remote sensing data from Shaanxi Province,China.Our results demonstrate that the XGboost algorithm outperforms linear regression and four other machine learning models,with an R^(2)of 0.906 and RMSE of 5.687.We observe an annual increase in carbon emissions,with high-emission counties primarily concentrated in northern and central Shaanxi Province,displaying a shift from discrete,sporadic points to contiguous,extended spatial distribution.Spatial autocorrelation clustering reveals predominantly high-high and low-low clustering patterns,with economically developed counties showing high-emission clustering and economically relatively backward counties displaying low-emission clustering.Our findings show that the use of NTL data and the XGboost algorithm can estimate and predict carbon emissionsmore accurately and provide a complementary reference for satellite remote sensing image data to serve carbon emission monitoring and assessment.This research provides an important theoretical basis for formulating practical carbon emission reduction policies and contributes to the development of techniques for accurate carbon emission estimation using remote sensing data.
基金supported by the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI)the Ministry of Health&Welfare,Republic of Korea (HR22C1734)+2 种基金the National Research Foundation (NRF) of Korea (2020R1A6A1A03043539,2020M3A9D8037604,2022R1C1C1004756)(to SBL)the NRF of Korea (2022R1C1C1005741 and RS-2023-00217595)the new faculty research fund of Ajou University School of Medicine (to EJL)。
文摘Elucidating the complex dynamic cellular organization in the hypothalamus is critical for understanding its role in coordinating fundamental body functions. Over the past decade, single-cell and spatial omics technologies have significantly evolved, overcoming initial technical challenges in capturing and analyzing individual cells. These high-throughput omics technologies now offer a remarkable opportunity to comprehend the complex spatiotemporal patterns of transcriptional diversity and cell-type characteristics across the entire hypothalamus. Current single-cell and single-nucleus RNA sequencing methods comprehensively quantify gene expression by exploring distinct phenotypes across various subregions of the hypothalamus. However, single-cell/single-nucleus RNA sequencing requires isolating the cell/nuclei from the tissue, potentially resulting in the loss of spatial information concerning neuronal networks. Spatial transcriptomics methods, by bypassing the cell dissociation, can elucidate the intricate spatial organization of neural networks through their imaging and sequencing technologies. In this review, we highlight the applicative value of single-cell and spatial transcriptomics in exploring the complex molecular-genetic diversity of hypothalamic cell types, driven by recent high-throughput achievements.
基金supported by the National Key Research and Development Program of China(No.2019YFC1804501)the National Natural Science Foundation of China(Nos.42122056 and U1901210)+2 种基金Guangdong Basic and Applied Basic Research Foundation(No.2021B1515020063)the Key Research and Development Program of Guangdong Province(No.2021B1111380003)the Local Innovative and Research Teams Project of Guangdong Pearl River Talents Program(No.2017BT01Z032).
文摘Coking industry is a potential source of heavy metals(HMs)pollution.However,its impacts to the groundwater of surrounding residential areas have not been well understood.This study investigated the pollution characteristics and health risks of HMs in groundwater nearby a typical coking plant.Nine HMs including Fe,Zn,Mo,As,Cu,Ni,Cr,Pb and Cd were analyzed.The average concentration of total HMswas higher in the nearby area(244.27μg/L)than that of remote area away the coking plant(89.15μg/L).The spatial distribution of pollution indices including heavy metal pollution index(HPI),Nemerow index(NI)and contamination degree(CD),all demonstrated higher values at the nearby residential areas,suggesting coking activity could significantly impact the HMs distribution characteristics.Four sources of HMs were identified by Positive Matrix Factorization(PMF)model,which indicated coal washing and coking emission were the dominant sources,accounted for 40.4%,and 31.0%,respectively.Oral ingestionwas found to be the dominant exposure pathway with higher exposure dose to children than adults.Hazard quotient(HQ)values were below 1.0,suggesting negligible non-carcinogenic health risks,while potential carcinogenic risks were from Pb and Ni with cancer risk(CR)values>10−6.Monte Carlo simulation matched well with the calculated results with HMs concentrations to be the most sensitive parameters.This study provides insights into understanding how the industrial coking activities can impact the HMs pollution characteristics in groundwater,thus facilitating the implement of HMs regulation in coking industries.
基金Under the auspices of Natural Science Basic Research Plan in Shaanxi Province of China(No.2024JC-YBMS-196)。
文摘Increased exposure to campus green spaces can make a positive contribution to the healthy development of students.However,understanding of the current supply of campus green space(CGS)and its drivers at different education stages is still limited.A new framework was established to evaluate the spatial heterogeneity and its influencing factors across all education stages(kindergarten,primary school,middle school,college)in 1100 schools at the urban scale of Xi’an,China.The research results show that:1)CGS is lower in the Baqiao district and higher in the Yanta and Xincheng districts of Xi’an City.‘Green wealthy schools are mainly concentrated in the Weiyang,Chang’an and Yanta districts.2)CGS of these schools in descending order is college(31.40%)>kindergarten(18.32%)>middle school(13.56%)>primary school(10.70%).3)Colleges have the most recreation sites(n(number)=2),the best education levels(11.93 yr),and the lowest housing prices(1.18×10^(4) yuan(RMB)/m^(2));middle schools have the highest public expenditures(3.97×10^(9) yuan/yr);primary schools have the highest CGS accessibility(travel time gap(TTG)=31.33).4)Multiscale Geographically Weighted Regression model and Spearman’s test prove that recreation sites have a significant positive impact on college green spaces(0.28–0.35),and education level has a significant positive impact on kindergarten green spaces(0.16–0.24).This research framework provides important insights for the assessment of school greening initiatives aimed at fostering healthier learning environments for future generations.
基金supported by funds from the Ministry of Science and Technology of the People's Republic of China(No.2019YFA0708603)NSFC(Nos.41973050,42288201,41930215)the Key Special Project for Introduced Talents Team of Southern Marine Science and Engineering Guangdong Laboratory(Guangzhou)(No.GML2019ZD0202)。
文摘Mineralogical data are presented for the peridotite xenoliths from Miocene(~19 Ma)Qingyuan basalts in the eastern North China Craton(NCC),with the aim of constraining on property of the sub-continental lithospheric mantle(SCLM)beneath the northern Tan-Lu fault zone(TLFZ)during the Cenozoic.The Qingyuan peridotites are dominated by spinel lherzolites with moderate-Mg^(#)olivines(89.4 to 91.2),suggesting that the regional SCLM is mainly transitional and fertile.Light rare earth element(LREE)-depleted,slightly depleted and enriched clinopyroxenes(Cpx)are identified in different peridotites.Chemical compositions of the LREE-enriched Cpx and the presence of phlogopite suggest that the Qingyuan SCLM has experienced silicate-related metasomatism.The synthesis of available mineral chemical data of the mantle xenoliths across the NCC confirms the SCLM beneath the NCC is highly heterogeneous in time and space.The Mesozoic–Cenozoic SCLM beneath the TLFZ and neighboring regions are more fertile and thinner than that beneath the region away from the fault zone.The fertile and refractory peridotite xenoliths experienced varying degrees of silicate and carbonatite metasomatism,respectively.The spatial-temporal lithospheric mantle heterogeneity in composition,age and thickness suggest that the trans-lithosphere fault zone played an important role in heterogeneous replacement of refractory cratonic lithospheric mantle.
文摘The study aims to investigate county-level variations of the COVID-19 disease and vaccination rate. The COVID-19 data was acquired from usafact.org, and the vaccination records were acquired from the Ohio vaccination tracker dashboard. GIS-based exploratory analysis was conducted to select four variables (poverty, black race, population density, and vaccination) to explain COVID-19 occurrence during the study period. Consequently, spatial statistical techniques such as Moran’s I, Hot Spot Analysis, Spatial Lag Model (SLM), and Spatial Error Model (SEM) were used to explain the COVID-19 occurrence and vaccination rate across the 88 counties in Ohio. The result of the Local Moran’s I analysis reveals that the epicenters of COVID-19 and vaccination followed the same patterns. Indeed, counties like Summit, Franklin, Fairfield, Hamilton, and Medina were categorized as epicenters for both COVID-19 occurrence and vaccination rate. The SEM seems to be the best model for both COVID-19 and vaccination rates, with R2 values of 0.68 and 0.70, respectively. The GWR analysis proves to be better than Ordinary Least Squares (OLS), and the distribution of R2 in the GWR is uneven throughout the study area for both COVID-19 cases and vaccinations. Some counties have a high R2 of up to 0.70 for both COVID-19 cases and vaccinations. The outcomes of the regression analyses show that the SEM models can explain 68% - 70% of COVID-19 cases and vaccination across the entire counties within the study period. COVID-19 cases and vaccination rates exhibited significant positive associations with black race and poverty throughout the study area.
文摘This study contests the prevalent perception of graffiti writing,especially tagging and bombing,as meaningless vandalism.It contends that graffiti is a form of expression with intrinsic political implications.Leveraging the notion of spatial justice and Jacques Ranciere's philosophy,I demonstrate how graffiti reclaims urban visibility against the commercial monopoly of visibility in public spaces and challenges the inequitable allocation of opportunities for self-expression in modern cities.Despite writers'common denial of political motives,their actions may be interpreted as manifestations of resistance within wider sociospatial conflicts.This study situates grffti within discussions of political art,spatial commodification,and everyday resistance,proposing a normative framework for viewing the art of the urban signature as an activity that redefines"the community that speaks."
基金supported by the National Natural Science Foundation of China,No.82301403(to DZ)。
文摘Glial cells play crucial roles in regulating physiological and pathological functions,including sensation,the response to infection and acute injury,and chronic neurodegenerative disorders.Glial cells include astrocytes,microglia,and oligodendrocytes in the central nervous system,and satellite glial cells and Schwann cells in the peripheral nervous system.Despite the greater understanding of glial cell types and functional heterogeneity achieved through single-cell and single-nucleus RNA sequencing in animal models,few studies have investigated the transcriptomic profiles of glial cells in the human spinal cord.Here,we used high-throughput single-nucleus RNA sequencing and spatial transcriptomics to map the cellular and molecular heterogeneity of astrocytes,microglia,and oligodendrocytes in the human spinal cord.To explore the conservation and divergence across species,we compared these findings with those from mice.In the human spinal cord,astrocytes,microglia,and oligodendrocytes were each divided into six distinct transcriptomic subclusters.In the mouse spinal cord,astrocytes,microglia,and oligodendrocytes were divided into five,four,and five distinct transcriptomic subclusters,respectively.The comparative results revealed substantial heterogeneity in all glial cell types between humans and mice.Additionally,we detected sex differences in gene expression in human spinal cord glial cells.Specifically,in all astrocyte subtypes,the levels of NEAT1 and CHI3L1 were higher in males than in females,whereas the levels of CST3 were lower in males than in females.In all microglial subtypes,all differentially expressed genes were located on the sex chromosomes.In addition to sex-specific gene differences,the levels of MT-ND4,MT2A,MT-ATP6,MT-CO3,MT-ND2,MT-ND3,and MT-CO_(2) in all spinal cord oligodendrocyte subtypes were higher in females than in males.Collectively,the present dataset extensively characterizes glial cell heterogeneity and offers a valuable resource for exploring the cellular basis of spinal cordrelated illnesses,including chronic pain,amyotrophic lateral sclerosis,and multiple sclerosis.
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.
文摘By introducing noncanonical vortex pairs to partially coherent beams, spatial correlation singularity (SCS) and orbital angular momenta (OAM) of the resulting beams are studied using the Fraunhofer diffraction integral. The effect of noncanonical strength, off-axis distance and vortex sign on spatial correlation singularities in far field is stressed. Furthermore, far-field OAM spectra and densities are also investigated, and the OAM detection and crosstalk probabilities are discussed. The results show that the number of dislocations of SCS always equals the sum of absolute values of topological charges for canonical or noncanonical vortex pairs. Although the sum of the product of each OAM mode and its power weight equals the algebraic sum of topological charges for canonical vortex pairs, the relationship no longer holds in the noncanonical case except for opposite-charge vortex pairs. The changes of off-axis distance, noncanonical strength or coherence length can lead to a more dominant power in adjacent mode than that in center detection mode, which also indicates that crosstalk probabilities of adjacent modes exceed the center detection probability. This work may provide potential applications in OAM-based optical communication, imaging, sensing and computing.
基金Jiangsu Funding Program for Excellent Postdoctoral Talent,No.2024ZB454National Natural Science Foundation of China,No.42071229,No.41671174Priority Academic Program Development of Jiangsu Higher Education Institutions,No.164320H116。
文摘The exploration of the variability of spatial spillovers of ecosystem services(ESs)across scales is essential for sustainable regional development.Using advanced models such as In VEST,Geodetector,MGWR,and SLM/SEM/SDB,this study investigates spatial heterogeneity and cross-regional effects on ESs at the raster and county scales.Key findings from 2000 to 2020 include an upward trend in ESs,with pronounced regional variations.The southern Yellow River Basin(YRB)shows higher levels of water yield,carbon sequestration,soil retention,and habitat quality,while the northern areas score lower,except for food provisioning in central and lower regions.The overall ES index has risen,particularly in the southern part,aligning with China's ecological patterns and showing significant cross-regional benefits.At various scales,natural elements,landscape configurations,and human influences significantly impact ESI,with different cross-regional effects.While natural and landscape indices demonstrate substantial cross-regional impacts at the raster scale,human influence is more apparent at the county scale.The identified cross-regional impacts underscore the interconnectedness of regional ES and sustainability,extending to nearby areas.Spatial management and planning may be limited by zoning and regulations.This study underscores regional ecosystem spatial spillovers and cross-scale knowledge differences and linkages,introducing new perspectives and methods for spatial planning in watersheds to support sustainable ecosystem optimisation.
基金Under the auspices of the National Natural Science Foundation of China(No.52268008)。
文摘This study focuses on urgent research on restoring and enhancing carbon storage capacity in the Beibu Gulf Urban Agglomer-ation of China,a key area in the‘Belt and Road’Initiative,which aligns with carbon peaking and neutrality goals.This research ana-lyzes the spatial characteristics of carbon metabolism from 2000 to 2020 and uses models to identify stable carbon sink areas,positive carbon flow corridors,and carbon sequestration nodes.The goal is to construct a carbon metabolism spatial security pattern(CMSSP)and propose territorial ecological restoration strategies under different development demand scenarios.The results show the following:1)in 2020,the study area’s carbon sink decreased by 8.29×10^(4) t C/yr compared with that in 2010 and by 10.83×10^(4) t C/yr compared with that in 2000.High-carbon sinks were found mainly in mountainous areas,whereas low-carbon sinks are concentrated in urban con-struction land,rural residential areas,and land margins.2)From 2000 to 2020,the spatial security pattern of carbon metabolism tended to be‘high in the middle of the east and west and low in the gulf.’In 2000,2010,and 2020,16 stable carbon sinks were identified.The carbon energy flow density in Guangxi was greater than that in Guangdong and Hainan,with positive carbon flow corridors located primarily in Guangxi and Guangdong.The number of carbon sequestration nodes remained stable at approximately 15,mainly in Guangxi and Hainan.3)Scenario simulations revealed that under the Nature-based mild restoration scenario,the carbon sink rate will reach 611.85×10^(4) t C/yr by 2030 and increase to 612.45×10^(4) t C/yr by 2060,with stable carbon sinks increasing to 18.In the restora-tion scenario based on Anti-globalization,the carbon sink will decrease from 610.24×10^(4) t C/yr in 2030 to 605.19×10^(4) t C/yr in 2060,with the disappearance of some positive carbon flow corridors and stable carbon sinks.Under the Human-based sustainable restoration scenario,the carbon sink area will decrease from 607.00×10^(4) t C/yr in 2030 to 596.39×10^(4) t C/yr in 2060,with carbon sink areas frag-menting and positive carbon flow corridors becoming less dense.4)On the basis of the current and predicted CMSSPs,this study ex-plores spatial ecological restoration strategies for high-carbon storage areas in bay urban agglomerations at four levels:the land control region,urban agglomeration structure system,carbon sink structure and bay structure control region.
文摘This study investigates the spatial courting between digital economic signs and local monetary overall performance throughout ten provinces in Sumatra,Indonesia,from 2019 to 2022.As digitalization hastens economic and business sports,devices together with fintech lending,e-cash,debit card usage,and e-commerce are increasingly more diagnosed as capability drivers of regional increase.But,the unequal distribution of digital infrastructure and monetary literacy across regions raises issues approximately the inclusivity of these benefits.constructing upon current findings by using Miranti et al.(2024),this research employs spatial econometric fashions-particularly the Spatial Lag model(SLM)and Spatial mistakes model(SEM)-to evaluate how digital variables influence provincial financial overall performance while accounting for spatial spillover consequences.The results reveal that fintech lending and debit card usage exert a positive and significant impact on economic growth,whereas the effect of e-money is negative,suggesting potential substitution effects or access constraints.Spatial dependency is also evident,as demonstrated by the significant lambda coefficient in the SEM model.These findings highlight the importance of spatially coordinated digital policies,particularly in addressing disparities and enhancing digital financial inclusion.The study concludes with policy recommendations aimed at fostering inclusive and spatially balanced digital economic development in Sumatra.
基金Under the auspices of National Natural Science Foundation of China(No.42371192)Natural Science Foundation of Hunan Province(No.2023JJ30100)Social Science Foundation of Hunan Province(No.23ZDAJ023,23YBA133)。
文摘Cities are important carriers of green innovation.The foundation for accelerating China's ecological civilization construction and fostering regionally coordinated and sustainable development is quantitative analysis of the spatial evolution pattern and influencing factors of urban green innovation,as well as revealing the development differences between regions.This study's research object includes 284 Chinese cities that are at the prefecture level or above,excluding Xizang,Hong Kong,Macao,and Taiwan of China due to incomplete data.The spatial evolution characteristics of urban green innovation in China between 2005 and 2021 are comprehensively described using the gravity center model and boxplot analysis.The factors that affect urban green innovation are examined using the spatial Durbin model(SDM).The findings indicate that:1)over the period of the study,the gravity center of urban green innovation in China has always been distributed in the Henan-Anhui border region,showing a migration characteristic of‘initially shifting northeast,subsequently southeast',and the migration speed has gradually increased.2)Although there are also noticeable disparities in east-west,the north-south gap is the main cause of the shift in China's urban green innovation gravity center.The primary areas of urban green innovation in China are the cities with green innovation levels higher than the median.3)The main influencing factor of urban green innovation is the industrial structure level.The effect of the financial development level,the government intervention level,and the openness to the outside world degree on urban green innovation is weakened in turn.The environmental regulation degree is not truly influencing urban green innovation.The impact of various factors on green innovation across cities of different sizes,exhibiting heterogeneity.This study is conducive to broadening the academic community's comprehension of the spatial evolution characteristics of urban green innovation and offering a theoretical framework for developing policies for the all-encompassing green transformation of social and economic growth.
基金China Institute of Water Resources and HydropowerResearch(IWHR)Innovative Team for Theoreticaland Technological Research on EcologicalLandscape Construction of Urban and Rural WaterSystems,Grant/Award Number:WE0145B042021。
文摘Located in Nanhai Town,Songzi City,Hubei Province,Xiaonanhai Lake is the largest natural lake in Songzi.It was once severely polluted due to the discharge of urban and rural domestic sewage,disorderly development of agricultural planting,unregulated aquaculture,and poultry farming.However,relevant esti-mations of the pollutant content in its sediment have not been carried out.This study analyzed the spatial patterns of heavy metal pollution and eutrophication at 36 water sampling sites in the Xiaonanhai Lake area,focusing on eight heavy metals:Cd,Cr,Cu,Ni,As,Pb,Hg,and Zn.The nutrient status of the lake area was evaluated using the nitrogen-phosphorus comprehensive pollution index,and heavy metal pollution status of the lake area was evaluated using geo-accumulation and the potential ecological risk index.Spatial autocorrelation analysis revealed the spatial correlation and aggregation of eutrophication levels in Xiaonanhai Lake.The results showed that the overall trophic state of the Xiaonanhai Lake area was moderate eutrophication,with a gradually decreasing eutrophication level from north to south.The Chengnan Wastewater Treatment Plant in the northern part of the lake area and surface source pollution from aquaculture were the main nitrogen and phosphorus sources.The overall eco-logical risk index of heavy metal pollution was medium and gradually weakened from north to south,consistent with the thickness of the bottom mud.The heavy metal pollution load was mainly precipitated from the bottom mud in the lake area.The eutrophication and heavy metal pollution levels in the lake area showed significant positive spatial autocorrelation,the influence range of the regional eutrophication level was small,and the spatial heterogeneity of the eutrophication and heavy metal pollution levels in Xiaonanhai Lake was relatively high.The northern part of the lake was a hotspot(high/high aggregation)of eutrophication(p<0.01)while the southern part was a cold spot(low/low concentration;p<0.05).The middle and northern part of the lake area was the hot spot(high/high concentration)of heavy metal pollution level(p<0.1)while the southern part was the cold spot(low/low concentration;p<0.1).Therefore,when carrying out water environment management in Xiaonanhai Lake,the northern area and the middle area should be prioritized for eutrophication prevention and control and dredging.
基金the Foshan Science and technology Innovation Team Project(No.FS0AA-KJ919-4402-0060)the National Natural Science Foundation of China(No.62263018)。
文摘In view of the weak ability of the convolutional neural networks to explicitly learn spatial invariance and the probabilistic loss of discriminative features caused by occlusion and background interference in pedestrian re-identification tasks,a person re-identification method combining spatial feature learning and multi-granularity feature fusion was proposed.First,an attention spatial transformation network(A-STN)is proposed to learn spatial features and solve the problem of misalignment of pedestrian spatial features.Then the network was divided into a global branch,a local coarse-grained fusion branch,and a local fine-grained fusion branch to extract pedestrian global features,coarse-grained fusion features,and fine-grained fusion features,respectively.Among them,the global branch enriches the global features by fusing different pooling features.The local coarse-grained fusion branch uses an overlay pooling to enhance each local feature while learning the correlation relationship between multi-granularity features.The local fine-grained fusion branch uses a differential pooling to obtain the differential features that were fused with global features to learn the relationship between pedestrian local features and pedestrian global features.Finally,the proposed method was compared on three public datasets:Market1501,DukeMTMC-ReID and CUHK03.The experimental results were better than those of the comparative methods,which verifies the effectiveness of the proposed method.
基金supported by the Marine S&T Fund of Shandong Province for Pilot National Laboratory for Marine Science and Technology(No.2021QNLM020001)the Major Scientific and Technological Projects of Shandong Energy Group(No.SNKJ2022A06-R23)+1 种基金the Funds of Creative Research Groups of China(No.41821002)the Major Scientific and Technological Projects of CNPC(No.ZD2019-183-003).
文摘To reduce the spatial simulation error generated by the finite difference method,previous researchers compute the optimal finite-difference weights always by minimizing the error of spatial dispersion relation.However,we prove that the spatial simulation error of the finite difference method is associated with the dot product of the spatial dispersion relation of the finite-difference weights and the spectrum of the seismic wavefield.Based on the dot product relation,we construct a L_(2) norm cost function to minimize spatial simulation error.For solving this optimization problem,the seismic wavefield infor-mation in wavenumber region is necessary.Nevertheless,the seismic wavefield is generally obtained by costly forward modeling techniques.To reduce the computational cost,we substitute the spectrum of the seismic wavelet for the spectrum of the seismic wavefield,as the seismic wavelet plays a key role in determining the seismic wavefield.In solving the optimization problem,we design an exhaustive search method to obtain the solution of the L_(2) norm optimization problem.After solving the optimization problem,we are able to achieve the finite-difference weights that minimize spatial simulation error.In theoretical error analyses,the finite-difference weights from the proposed method can output more accurate simulation results compared to those from previous optimization algorithms.Furthermore,we validate our method through numerical tests with synthetic models,which encompass homogenous/inhomogeneous media as well as isotropic and anisotropic media.
基金supported by the National Natural Science Foundation of China(42271317)the Innovation Research Team Project of the Natural Science Foundation of Hainan Province(422CXTD515)。
文摘Latitudinal patterns of treeβ-diversity reveal important insights into the biogeographical processes that influence forest ecosystems.Although previous studies have extensively documentedβ-diversity within relatively small spatial extents,the potential drivers ofβ-diversity along latitudinal gradients are still not well understood at larger spatial extents.In this study,we determined whether treeβ-diversity is correlated with latitude in forests of southeastern China,and if so,what ecological processes contribute to these patterns of treeβ-diversity.We specifically aimed to disentangle the relative contributions from interspecific aggregation and environmental filtering across various spatial extents.We delineated regional communities comprising multiple nearby national forest inventory(NFI)plots around random focal plots.The number of NFI plots in a regional community served as a surrogate for spatial extent.We also used a null model to simulate randomly assembled communities and quantify the deviation(β-deviation)between observed and expectedβ-diversity.We found thatβ-diversity decreased along a latitudinal gradient and that this pattern was clearer at larger spatial extents.In addition,latitudinal patterns ofβ-deviation were explained by the degree of species spatial aggregation.We also identified environmental factors that driveβ-deviation in these forests,including precipitation,seasonality,and temperature variation.At larger spatial extents,these environmental variables explained up to 84%of theβ-deviation.Our results reinforce that ecological processes are scale-dependent and collectively contribute to theβ-gradient in subtropical forests.We recommend that conservation efforts maintain diverse forests and heterogeneous environments at multiple spatial extents to mitigate the adverse effects of climate change.
