This study analyzed the spatial-temporal heterogeneity of green development efficiency and its influencing factors in the growing Xuzhou Metropolitan Area for the period 2000–2015.The slacks-based measure(SBM)model,s...This study analyzed the spatial-temporal heterogeneity of green development efficiency and its influencing factors in the growing Xuzhou Metropolitan Area for the period 2000–2015.The slacks-based measure(SBM)model,spatial autocorrelation,and the geographically weighted regression(GWR)model were used to conduct the analysis.The conclusions were as follows:first,the overall efficiency of green development of the Xuzhou Metropolitan Area decreased,the regional differences and spatial agglomeration shrunk and differences within the region were the main contributors to the regional differences of green development efficiency.Second,the counties with high-efficiency green development were distributed along the coast,and along the routes of the Beijing-Shanghai and the Eastern Longhai railways.A developing axis of the high-efficiency counties was the main feature of the spatial pattern for green development efficiency.Third,regarding spatial correlation and green development efficiency,the High-High type counties in the Xuzhou Metropolitan Area formed a centralized distribution corridor along the inter-provincial border areas of Henan and Jiangsu,whereas the Low-Low type counties were concentrated in the external,marginal parts of the metropolitan area.Fourth,the major factors(ranked in decreasing order of impact)influencing green development efficiency were innovation,government regulations,the economic development level,energy consumption,and industrial structure.These factors exerted their influence to varying extents;the influence of the same factor had different effects in different regions and obvious spatial differences were observed for the different regions.展开更多
Employing decoupling index and industrial structure characteristic bias index methods, this study analyzed the spatial-temporal characteristics of industrial structure transformations and their resulting carbon emissi...Employing decoupling index and industrial structure characteristic bias index methods, this study analyzed the spatial-temporal characteristics of industrial structure transformations and their resulting carbon emissions in the Xuzhou Metropolitan Area from 2000 to 2014, with a focus on their relationships and driving factors. Our research indicates that carbon emission intensity from industrial structures in the Xuzhou Metropolitan Area at first showed an increasing trend, which then decreased. Furthermore, the relationship between emissions and industrial economic growth has been trending toward absolute decoupling. From the perspective of the center-periphery, the Xuzhou Metropolitan Area formed a concentric pattern, where both progress towards low emissions and the level of technological advancement gradually diminished from the center to the periphery. In terms of variation across provinces, the ISCB index in the eastern Henan has decreased the slowest, followed by the southern Shandong and the northern Anhui, with the northern Jiangsu ranking last. During this period, resource-and labor-intensive industries were the primary growth industries in the northern Anhui and the eastern Henan, while labor-intensive industries dominated the southern Shandong and capital-intensive industries dominated the northern Jiangsu. In terms of city types, the spatial pattern for industrial structure indicates that recession resource-based cities had higher carbon emission intensities than mature resource-based cities, followed by non-resource-based cities and regenerative resource-based cities. Generally, the industrial structure in the Xuzhou Metropolitan Area has transformed from being resource-intensive to capital-intensive, and has been trending toward technology-intensive as resource availability has been exploited to exhaustion and then been regenerated. Industrial structure has been the leading factor causing heterogeneity of carbon emission intensities between metropolitan cities. Therefore, the key to optimizing the industrial structure and layout of metropolitan areas is to promote industrial structure transformation and improve the system controlling collaborative industrial development between cities.展开更多
Land surface evapotranspiration(ET)is a critical component in the hydrological cycle but has not well been understood in data-scarce areas especially in river basins,like Nujiang River(NRB)which is characterized by la...Land surface evapotranspiration(ET)is a critical component in the hydrological cycle but has not well been understood in data-scarce areas especially in river basins,like Nujiang River(NRB)which is characterized by large elevation gradient and different vegetation zones with complex processes of water and energy exchange.The quality of ET from optical remote sensing is constrained by cloud cover which is common in the NRB in the monsoon seasons.To understand factors controlling the spatial-temporal heterogeneity of ET in NRB,we employed the Variable Infiltration Capacity(VIC)hydrological model by parameter optimization with support of quality controlled remote sensing ET product and observed river runoff series in the river.The modeled ET has increased during 1984-2018,which might be one of the reasons for the runoff decrease but precipitation increase in the same period.ET increase and runoff decrease tended to be quicker within altitudinal band of 2000-4000 m than in other areas in NRB.We observed that ET variation in different climatic zones were controlled by different factors.ET is generally positively correlated with precipitation,temperature,and shortwave radiation but negatively with relative humidity.In the Tundra Climate(Et)zone in the upper reach of NRB,ET is controlled by precipitation,while it is controlled by shortwave radiation in the snow climate with dry winter(Dw)zone.ET increase is influenced by the increase of temperature,wind speed,and shortwave radiation in the middle and downstream of NRB with warm temperate climate,fully humid(Cf)and warm temperate climate with dry winter(Cw).展开更多
Drug development for Alzheimer’s disease is extremely challenging,as demonstrated by the repeated failures of amyloid-β-targeted therapeutics and the controversies surrounding the amyloid-βcascade hypothesis.More r...Drug development for Alzheimer’s disease is extremely challenging,as demonstrated by the repeated failures of amyloid-β-targeted therapeutics and the controversies surrounding the amyloid-βcascade hypothesis.More recently,advances in the development of Lecanemab,an anti-amyloid-βmonoclonal antibody,have shown positive results in reducing brain A burden and slowing cognitive decline in patients with early-stage Alzheimer’s disease in the Phase Ⅲ clinical trial(Clarity Alzheimer’s disease).Despite these promising results,side effects such as amyloid-related imaging abnormalities(ARIA)may limit its usage.ARIA can manifest as ARIA-E(cerebral edema or effusions)and ARIA-H(microhemorrhages or superficial siderosis)and is thought to be caused by increased vascular permeability due to inflammatory responses,leading to leakages of blood products and protein-rich fluid into brain parenchyma.Endothelial dysfunction is an early pathological feature of Alzheimer’s disease,and the blood-brain barrier becomes increasingly leaky as the disease progresses.In addition,APOE4,the strongest genetic risk factor for Alzheimer’s disease,is associated with higher vascular amyloid burden,increased ARIA incidence,and accelerated blood-brain barrier disruptions.These interconnected vascular abnormalities highlight the importance of vascular contributions to the pathophysiology of Alzheimer’s disease.Here,we will closely examine recent research evaluating the heterogeneity of brain endothelial cells in the microvasculature of different brain regions and their relationships with Alzheimer’s disease progression.展开更多
Background:Utilizing population-based survey data in epidemiological research with a spatial perspective can integrate valuable context into the dynamics of HIV prevalence in West Africa.However,the situation in the M...Background:Utilizing population-based survey data in epidemiological research with a spatial perspective can integrate valuable context into the dynamics of HIV prevalence in West Africa.However,the situation in the Mano River Union(MRU)countries is largely unknown.This research aims to perform an ecological study to determine the HIV prevalence patterns in MRU.Methods:We analyzed Demographic and Health Survey(DHS)and AIDS Indicator Survey(AIS)data on HIV prevalence in MRU from 2005 to 2020.We examined the country-specifc,regional-specifc and sex-specifc ratios of respondents to profle the spatial–temporal heterogeneity of HIV prevalence and determine HIV hot spots.We employed Geodetector to measure the spatial stratifed heterogeneity(SSH)of HIV prevalence for adult women and men.We assessed the comprehensive correct knowledge(CCK)about HIV/AIDS and HIV testing uptake by employing the Least Absolute Shrinkage and Selection Operator(LASSO)regression to predict which combinations of CCKs can scale up the ratio of HIV testing uptake with sex-specifc needs.Results:In our analysis,we leveraged data for 158,408 respondents from 11 surveys in the MRU.From 2005–2015,Cote d’Ivoire was the hot spot for HIV prevalence with a Gi_Bin score of 3,Z-Score 8.0–10.1 and P<0.001.From 2016 to 2020,Guinea and Sierra Leone were hot spots for HIV prevalence with a Gi_Bin score of 2,Z-Score of 3.17 and P<0.01.The SSH confrmed the signifcant diferences in HIV prevalence at the national level strata,with a higher level for Cote d’Ivoire compared to other countries in both sexes with q-values of 0.61 and 0.40,respectively.Our LASSO model predicted diferent combinations of CCKs with sex-specifc needs to improve HIV testing uptake.Conclusions:The spatial distribution of HIV prevalence in the MRU is skewed and the CCK about HIV/AIDS and HIV testing uptake are far below the threshold target set by UNAIDS for ending the epidemic in the sub-region.Geodetector detected statistically signifcant SSH within and between countries in the MRU.Our LASSO model predicted that diferent emphases should be implemented when popularizing the CCK about HIV/AIDS for adult women and men.展开更多
As a significant city in the Yangtze River Delta regions,Hefei has experienced rapid changes in the sources of air pollution due to its high-speed economic development and urban expansion.However,there has been limite...As a significant city in the Yangtze River Delta regions,Hefei has experienced rapid changes in the sources of air pollution due to its high-speed economic development and urban expansion.However,there has been limited research in recent years on the spatial-temporal distribution and emission of its atmospheric pollutants.To address this,this study conducted mobile observations of urban roads using the Mobile-DOAS instrument from June 2021 to May 2022.The monitoring results exhibit a favourable consistent with TROPOMI satellite data and ground monitoring station data.Temporally,there were pronounced seasonal variations in air pollutants.Spatially,high concentration of HCHO and NO_(2)were closely associated with traffic congestion on roadways,while heightened SO_(2)levels were attributed to winter heating and industrial emissions.The study also revealed that with the implementation of road policies,the average vehicle speed increased by 95.4%,while the NO concentration decreased by 54.4%.In the estimation of urban NO_(x)emission flux,it was observed that in temporal terms,compared with inventory data,the emissions calculated viamobile measurements exhibitedmore distinct seasonal patterns,with the highest emission rate of 349 g/sec in winter and the lowest of 142 g/sec in summer.In spatial terms,the significant difference in emissions between the inner and outer ring roads also suggests the presence of the city’s primary NO_(x)emission sources in the area between these two rings.This study offers data support for formulating the next phase of air pollution control measures in urban areas.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
In recent years,advancements in single-cell and spatial transcriptomics,which are highly regarded developments in the current era,particularly the emerging integration of single-cell and spatiotemporal transcriptomics...In recent years,advancements in single-cell and spatial transcriptomics,which are highly regarded developments in the current era,particularly the emerging integration of single-cell and spatiotemporal transcriptomics,have enabled a detailed molecular comprehension of the complex regulation of cell fate.The insights obtained from these methodologies are anticipated to significantly contribute to the development of personalized medicine.Currently,single-cell technology is less frequently utilized for prostate cancer compared with other types of tumors.Start-ing from the perspective of RNA sequencing technology,this review outlined the signifcance of single-cell RNA sequencing(scRNA-seq)in prostate cancer research,encompassing preclinical medicine and clinical applications.We summarize the differences between mouse and human prostate cancer as revealed by scRNA-seq studies,as well as a combination of multi-omics methods involving scRNA-seq to highlight the key molecular targets for the diagnosis,treatment,and drug resistance characteristics of prostate cancer.These studies are expected to provide novel insights for the development of immunotherapy and other innovative treatment strategies for castration-resistant prostate cancer.Furthermore,we explore the potential clinical applications stemming from other single-cell technologies in this review,paving the way for future research in precision medicine.展开更多
Mature oligodendrocytes form myelin sheaths that are crucial for the insulation of axons and efficient signal transmission in the central nervous system.Recent evidence has challenged the classical view of the functio...Mature oligodendrocytes form myelin sheaths that are crucial for the insulation of axons and efficient signal transmission in the central nervous system.Recent evidence has challenged the classical view of the functionally static mature oligodendrocyte and revealed a gamut of dynamic functions such as the ability to modulate neuronal circuitry and provide metabolic support to axons.Despite the recognition of potential heterogeneity in mature oligodendrocyte function,a comprehensive summary of mature oligodendrocyte diversity is lacking.We delve into early 20th-century studies by Robertson and Río-Hortega that laid the foundation for the modern identification of regional and morphological heterogeneity in mature oligodendrocytes.Indeed,recent morphologic and functional studies call into question the long-assumed homogeneity of mature oligodendrocyte function through the identification of distinct subtypes with varying myelination preferences.Furthermore,modern molecular investigations,employing techniques such as single cell/nucleus RNA sequencing,consistently unveil at least six mature oligodendrocyte subpopulations in the human central nervous system that are highly transcriptomically diverse and vary with central nervous system region.Age and disease related mature oligodendrocyte variation denotes the impact of pathological conditions such as multiple sclerosis,Alzheimer's disease,and psychiatric disorders.Nevertheless,caution is warranted when subclassifying mature oligodendrocytes because of the simplification needed to make conclusions about cell identity from temporally confined investigations.Future studies leveraging advanced techniques like spatial transcriptomics and single-cell proteomics promise a more nuanced understanding of mature oligodendrocyte heterogeneity.Such research avenues that precisely evaluate mature oligodendrocyte heterogeneity with care to understand the mitigating influence of species,sex,central nervous system region,age,and disease,hold promise for the development of therapeutic interventions targeting varied central nervous system pathology.展开更多
Heterogeneous federated learning(HtFL)has gained significant attention due to its ability to accommodate diverse models and data from distributed combat units.The prototype-based HtFL methods were proposed to reduce t...Heterogeneous federated learning(HtFL)has gained significant attention due to its ability to accommodate diverse models and data from distributed combat units.The prototype-based HtFL methods were proposed to reduce the high communication cost of transmitting model parameters.These methods allow for the sharing of only class representatives between heterogeneous clients while maintaining privacy.However,existing prototype learning approaches fail to take the data distribution of clients into consideration,which results in suboptimal global prototype learning and insufficient client model personalization capabilities.To address these issues,we propose a fair trainable prototype federated learning(FedFTP)algorithm,which employs a fair sampling training prototype(FSTP)mechanism and a hyperbolic space constraints(HSC)mechanism to enhance the fairness and effectiveness of prototype learning on the server in heterogeneous environments.Furthermore,a local prototype stable update(LPSU)mechanism is proposed as a means of maintaining personalization while promoting global consistency,based on contrastive learning.Comprehensive experimental results demonstrate that FedFTP achieves state-of-the-art performance in HtFL scenarios.展开更多
In the current situation of decelerating economic expansion,examining the digital economy(DE)as a novel economic model is beneficial for the local economy’s sustainable and high-quality development(HQD).We analyzed p...In the current situation of decelerating economic expansion,examining the digital economy(DE)as a novel economic model is beneficial for the local economy’s sustainable and high-quality development(HQD).We analyzed panel data from the Yellow River(YR)region from 2013 to 2021 and discovered notable spatial variances in the composite index and coupling coordination of the two systems.Specifically,the downstream region exhibited the highest coupling coordination,while the upstream region had the lowest.We identified that favorable factors such as economic development,innovation,industrial upgrading,and government intervention can bolster the coupling.Our findings provide a valuable framework for promoting DE and HQD in the YR region.展开更多
Accurate traffic flow prediction has a profound impact on modern traffic management. Traffic flow has complex spatial-temporal correlations and periodicity, which poses difficulties for precise prediction. To address ...Accurate traffic flow prediction has a profound impact on modern traffic management. Traffic flow has complex spatial-temporal correlations and periodicity, which poses difficulties for precise prediction. To address this problem, a Multi-head Self-attention and Spatial-Temporal Graph Convolutional Network (MSSTGCN) for multiscale traffic flow prediction is proposed. Firstly, to capture the hidden traffic periodicity of traffic flow, traffic flow is divided into three kinds of periods, including hourly, daily, and weekly data. Secondly, a graph attention residual layer is constructed to learn the global spatial features across regions. Local spatial-temporal dependence is captured by using a T-GCN module. Thirdly, a transformer layer is introduced to learn the long-term dependence in time. A position embedding mechanism is introduced to label position information for all traffic sequences. Thus, this multi-head self-attention mechanism can recognize the sequence order and allocate weights for different time nodes. Experimental results on four real-world datasets show that the MSSTGCN performs better than the baseline methods and can be successfully adapted to traffic prediction tasks.展开更多
Field tests have demonstrated that depressurization with controlled sand production is an effective technique for natural gas hydrate extraction.Variations in depositional environments and processes result in signific...Field tests have demonstrated that depressurization with controlled sand production is an effective technique for natural gas hydrate extraction.Variations in depositional environments and processes result in significant heterogeneity within subsea natural gas hydrate-bearing sediments.However,the influence of permeability heterogeneity on production performance during depressurization with controlled sand production remains inadequately understood.In this study,a multiphase,multi-component mathematical model is developed to simulate depressurization with controlled sand production in methane hydrate-bearing sediments,incorporating geological conditions representative of unconsolidated argillaceous siltstone hydrate deposits in the Shenhu area of the South China Sea.The effects of permeability heterogeneity-specifically,horizontal autocorrelation length and global permeability heterogeneity-on production performance during depressurization with sand production are investigated using geostatistical modeling combined with finite difference method based numerical simulations.Results show that as the horizontal autocorrelation length of permeability distribution increases,cumulative gas production first rises and then declines,reaching its peak at λ_(Dh)=0.1,whereas sand production steadily increases.In addition,higher formation permeability heterogeneity results in increased cumulative gas and sand production,suggesting that greater heterogeneity promotesmethane hydrate decomposition and gas recovery.These findings can offer valuable insights for optimizing future field development of hydrate-bearing sediments by depressurization with controlled sand production.展开更多
Due to severe mass transfer limitations,the remediation efficiency of low-permeability contaminated sites often fails to meet expectations.Hydraulic fracturing technology has been utilized to enhance amendment deliver...Due to severe mass transfer limitations,the remediation efficiency of low-permeability contaminated sites often fails to meet expectations.Hydraulic fracturing technology has been utilized to enhance amendment delivery,but the influence of soil heterogeneity is commonly overlooked.To address this issue,this study develops a numerical model to simulate the enhanced transport of amendments,incorporating convection,diffusion,adsorption,and degradation processes.Within the model,random permeability fields are generated based on geostatistical methods to explore how soil heterogeneity affects amendment injection efficiency,distribution characteristics,and the underlying physical mechanisms.The results indicate that(1)soil heterogeneity significantly reduces the amendment injection efficiency,with stronger heterogeneity correlating to lower efficiency,(2)soil heterogeneity markedly alters the amendment distribution characteristics,leading to the formation of localized“nodes”,(3)the mechanism by which heterogeneity reduces injection efficiency involves decreasing the density of preferential flow paths in the soil,and(4)the adverse effects of heterogeneity can be mitigated by employing pressure compensation or adjusting well spacing.展开更多
By employing micrometer-diameter microelectrodes, the metastable pitting corrosion behavior of Co_(68.15)Fe_(4.35)Si_(12.5)B_(12)Cr_(3) metallic glasses (MGs) exposed to 0.6 mol/L NaCl solution was investigated to cla...By employing micrometer-diameter microelectrodes, the metastable pitting corrosion behavior of Co_(68.15)Fe_(4.35)Si_(12.5)B_(12)Cr_(3) metallic glasses (MGs) exposed to 0.6 mol/L NaCl solution was investigated to clarify the correlation between metastable pitting and structural heterogeneity in MGs. Thermally induced degeneration of structural heterogeneity inhibits the initiation, decelerates the growth kinetics, and accelerates the repassivation kinetics of metastable pits while also decreasing the probability of transition from metastability to stability. This enhanced resistance to pitting corrosion is attributed to a reduction in active pitting precursor sites and a decrease in electrochemical activity caused by the structural homogenization of MGs.展开更多
Spatial-temporal traffic prediction technology is crucial for network planning,resource allocation optimizing,and user experience improving.With the development of virtual network operators,multi-operator collaboratio...Spatial-temporal traffic prediction technology is crucial for network planning,resource allocation optimizing,and user experience improving.With the development of virtual network operators,multi-operator collaborations,and edge computing,spatial-temporal traffic data has taken on a distributed nature.Consequently,noncentralized spatial-temporal traffic prediction solutions have emerged as a recent research focus.Currently,the majority of research typically adopts federated learning methods to train traffic prediction models distributed on each base station.This method reduces additional burden on communication systems.However,this method has a drawback:it cannot handle irregular traffic data.Due to unstable wireless network environments,device failures,insufficient storage resources,etc.,data missing inevitably occurs during the process of collecting traffic data.This results in the irregular nature of distributed traffic data.Yet,commonly used traffic prediction models such as Recurrent Neural Networks(RNN)and Long Short-Term Memory(LSTM)typically assume that the data is complete and regular.To address the challenge of handling irregular traffic data,this paper transforms irregular traffic prediction into problems of estimating latent variables and generating future traffic.To solve the aforementioned problems,this paper introduces split learning to design a structured distributed learning framework.The framework comprises a Global-level Spatial structure mining Model(GSM)and several Nodelevel Generative Models(NGMs).NGM and GSM represent Seq2Seq models deployed on the base station and graph neural network models deployed on the cloud or central controller.Firstly,the time embedding layer in NGM establishes the mapping relationship between irregular traffic data and regular latent temporal feature variables.Secondly,GSM collects statistical feature parameters of latent temporal feature variables from various nodes and executes graph embedding for spatial-temporal traffic data.Finally,NGM generates future traffic based on latent temporal and spatial feature variables.The introduction of the time attention mechanism enhances the framework’s capability to handle irregular traffic data.Graph attention network introduces spatially correlated base station traffic feature information into local traffic prediction,which compensates for missing information in local irregular traffic data.The proposed framework effectively addresses the distributed prediction issues of irregular traffic data.By testing on real world datasets,the proposed framework improves traffic prediction accuracy by 35%compared to other commonly used distributed traffic prediction methods.展开更多
Although the spatial characteristics within the tumor microenvironment of lung adenocarcinoma(LUAD)have been identified,the mechanisms by which these factors promote LUAD progression and immune evasion remain unclear....Although the spatial characteristics within the tumor microenvironment of lung adenocarcinoma(LUAD)have been identified,the mechanisms by which these factors promote LUAD progression and immune evasion remain unclear.Using spatial transcriptomics and single-cell RNA-sequencing data from multi-regional LUAD biopsies consisting of tumor core,tumor edge,and normal area,we sought to delineate the spatial heterogeneity and driving factors of cell colocalization.Two cancer cell sub-clusters(Cancer_c1 and Cancer_c2),associated with LUAD initiation and metastasis,respectively,exhibit distinct spatial distributions and immune cell colocalizations.In particular,Cancer_c1,enriched within the tumor core,could directly interact with B cells or indirectly recruit B cells through macrophages.Conversely,Cancer_c2 enriched within the tumor edge exhibits colocalization with CD8^(+)T cells.Collectively,our work elucidates the spatial distribution of cancer cell subtypes and their interaction with immune cells in the core and edge of LUAD,providing insights for developing therapeutic strategies for cancer intervention.展开更多
The trade-off between strength and ductility has long been a challenge for Mg alloy.To address this issue,bimodal-structured AZ80 Mg alloys with varying heterogeneity levels were fabricated via low-temperature extrusi...The trade-off between strength and ductility has long been a challenge for Mg alloy.To address this issue,bimodal-structured AZ80 Mg alloys with varying heterogeneity levels were fabricated via low-temperature extrusion in this work.The results reveal the microstructure comprising second-phase particle(SP_(p),β-Mg_(17)Al_(12)and Mg_(3) Mn_(2) Al_(18))-reinforced fine grains(FGs)FGs and SP_(p)-free coarse grains(CGs),with the heterogeneity level decreasing as extrusion temperature increases.As the heterogeneity level decreases,the synergistic deformation capacity initially improves,reaching a maximum at the moderate heterogeneity level of 0.31 GPa and 0.238,and then declines.This exceptional capacity is attributed to the hetero-deformation induced(HDI)stress,which effectively alleviates the strain gradients by activating〈c+a〉dislocations and non-basal〈a〉dislocations during deformation.An optimal combination of 287 MPa in yield strength,393 MPa in ultimate tensile strength,and 14.96%in elongation is achieved in the alloy with a moderate heterogeneity level.The excellent strength-ductility synergy originates from the enhanced capacity of dislocations accumulation driven by remarkable capacity of synergistic deformation and the synergistic strengthening mechanisms.This work provides a new insight into the design of bimodal structure to produce high-performance Mg alloys.展开更多
Layered rare-earth metal oxides,harnessing the dual properties of oxides and two-dimensional layered materials,exhibit remarkable thermal stability and quantum confinement effects.Therefore,this work adopts the first-...Layered rare-earth metal oxides,harnessing the dual properties of oxides and two-dimensional layered materials,exhibit remarkable thermal stability and quantum confinement effects.Therefore,this work adopts the first-principles calculation combined with the Boltzmann transport theory to predict the thermoelectric properties of NdZnSbO compound.The coexistence of weak interlayer van der Waals interactions,robust intralayer ionic bonding,and partial covalent bonding leads to remarkable bonding heterogeneity,which engenders pronounced phonon scattering and imposes constraints on thermal transport along the out-of-plane direction.The weakened chemical bonds induced by the antibonding states,together with the rattling-like behavior of the Zn atom,culminate in the profound anharmonicity in the layered NdZnSbO compound.The weakening bond and heavy element contribute to the softness of phonon modes,which significantly diminishes the phonon group velocity.The redistribution-dominated four-phonon scattering process spans a large optical gap,which effectively reduces the lattice thermal conductivity.The NdZnSbO compound exhibits direct semiconductor characteristic with a bandgap of 0.73 e V by adopting the Heyd-Scuseria-Ernzerhof(HSE06)functional in combination with spin–orbit coupling(SOC)effect.The multi-valley feature of NdZnSbO compound augur favorably for band degeneracy,thus amplifying the power factor.Consequently,an optimal figure-of-merit(ZT)of 3.40 at 900 K is achieved for the n-type NdZnSbO compound.The present study delves deeply insights into the origins for the low thermal conductivity of NdZnSbO compound and proposes an optimization scheme to enhance overall thermoelectric performance.展开更多
Reservoirs play a critical role in addressing water resources challenges.However,their vertical influence on the assembly mechanisms of different microbial communities,including prokaryotes and eukaryotes,remains uncl...Reservoirs play a critical role in addressing water resources challenges.However,their vertical influence on the assembly mechanisms of different microbial communities,including prokaryotes and eukaryotes,remains unclear.This study examined the vertical diversity patterns of abundant and rare subcommunities of prokaryotes and eukaryotes in an urban reservoir,using water depth as a geographical gradient and employing high-throughput sequencing.The impact of vertical environmental heterogeneity on community structure was quantified,and key drivers of these dynamics were identified.The results indicated that the urban reservoir exhibited statistically significant differences in the vertical distribution of water temperature and oxidation/reduction potential.The a-diversity of the abundant subcommunity displayed an opposing vertical pattern compared to that of the rare subcommunity,while the b-diversity for both subcommunities of prokaryotes and eukaryotes increased with water depth.Moreover,the distinct diversity patterns of abundant and rare subcommunities were associated with environmental heterogeneity and species adaptability.Notably,the b-diversity of the rare subcommunity of eukaryotes was primarily driven by species turnover in surface water,whereas nestedness became the dominant factor in deeper water.Furthermore,eukaryotic microbes exhibited a more pronounced response to changes in water depth than prokaryotes,consistent with the importance of heterogeneous selection to the eukaryotic community.Water temperature significantly affected the community composition of all groups,highlighting its importance in shaping community dynamics.This study provides valuable insights into the vertical distribution and assembly mechanisms of microbial communities in urban reservoirs,contributing to the protection and management of aquatic ecosystems under river regulation.展开更多
基金Under the auspices of the National Natural Science Foundation of China(No.41671123,41971158,41671122)Major Project of Philosophy and Social Science Research of Jiangsu Universities(No.2018SJZDA010).
文摘This study analyzed the spatial-temporal heterogeneity of green development efficiency and its influencing factors in the growing Xuzhou Metropolitan Area for the period 2000–2015.The slacks-based measure(SBM)model,spatial autocorrelation,and the geographically weighted regression(GWR)model were used to conduct the analysis.The conclusions were as follows:first,the overall efficiency of green development of the Xuzhou Metropolitan Area decreased,the regional differences and spatial agglomeration shrunk and differences within the region were the main contributors to the regional differences of green development efficiency.Second,the counties with high-efficiency green development were distributed along the coast,and along the routes of the Beijing-Shanghai and the Eastern Longhai railways.A developing axis of the high-efficiency counties was the main feature of the spatial pattern for green development efficiency.Third,regarding spatial correlation and green development efficiency,the High-High type counties in the Xuzhou Metropolitan Area formed a centralized distribution corridor along the inter-provincial border areas of Henan and Jiangsu,whereas the Low-Low type counties were concentrated in the external,marginal parts of the metropolitan area.Fourth,the major factors(ranked in decreasing order of impact)influencing green development efficiency were innovation,government regulations,the economic development level,energy consumption,and industrial structure.These factors exerted their influence to varying extents;the influence of the same factor had different effects in different regions and obvious spatial differences were observed for the different regions.
基金Under the auspices of the National Natural Science Foundation of China(No.41371146,41671123)National Social Science Foundation of China(No.13BJY067)
文摘Employing decoupling index and industrial structure characteristic bias index methods, this study analyzed the spatial-temporal characteristics of industrial structure transformations and their resulting carbon emissions in the Xuzhou Metropolitan Area from 2000 to 2014, with a focus on their relationships and driving factors. Our research indicates that carbon emission intensity from industrial structures in the Xuzhou Metropolitan Area at first showed an increasing trend, which then decreased. Furthermore, the relationship between emissions and industrial economic growth has been trending toward absolute decoupling. From the perspective of the center-periphery, the Xuzhou Metropolitan Area formed a concentric pattern, where both progress towards low emissions and the level of technological advancement gradually diminished from the center to the periphery. In terms of variation across provinces, the ISCB index in the eastern Henan has decreased the slowest, followed by the southern Shandong and the northern Anhui, with the northern Jiangsu ranking last. During this period, resource-and labor-intensive industries were the primary growth industries in the northern Anhui and the eastern Henan, while labor-intensive industries dominated the southern Shandong and capital-intensive industries dominated the northern Jiangsu. In terms of city types, the spatial pattern for industrial structure indicates that recession resource-based cities had higher carbon emission intensities than mature resource-based cities, followed by non-resource-based cities and regenerative resource-based cities. Generally, the industrial structure in the Xuzhou Metropolitan Area has transformed from being resource-intensive to capital-intensive, and has been trending toward technology-intensive as resource availability has been exploited to exhaustion and then been regenerated. Industrial structure has been the leading factor causing heterogeneity of carbon emission intensities between metropolitan cities. Therefore, the key to optimizing the industrial structure and layout of metropolitan areas is to promote industrial structure transformation and improve the system controlling collaborative industrial development between cities.
基金supported by the National Natural Science Foundation of China(42171129)the second Tibetan Plateau Scientific Expedition and Research(2019QZKK0208)Yunnan University Talent Introduction Research Project(YJRC3201702)。
文摘Land surface evapotranspiration(ET)is a critical component in the hydrological cycle but has not well been understood in data-scarce areas especially in river basins,like Nujiang River(NRB)which is characterized by large elevation gradient and different vegetation zones with complex processes of water and energy exchange.The quality of ET from optical remote sensing is constrained by cloud cover which is common in the NRB in the monsoon seasons.To understand factors controlling the spatial-temporal heterogeneity of ET in NRB,we employed the Variable Infiltration Capacity(VIC)hydrological model by parameter optimization with support of quality controlled remote sensing ET product and observed river runoff series in the river.The modeled ET has increased during 1984-2018,which might be one of the reasons for the runoff decrease but precipitation increase in the same period.ET increase and runoff decrease tended to be quicker within altitudinal band of 2000-4000 m than in other areas in NRB.We observed that ET variation in different climatic zones were controlled by different factors.ET is generally positively correlated with precipitation,temperature,and shortwave radiation but negatively with relative humidity.In the Tundra Climate(Et)zone in the upper reach of NRB,ET is controlled by precipitation,while it is controlled by shortwave radiation in the snow climate with dry winter(Dw)zone.ET increase is influenced by the increase of temperature,wind speed,and shortwave radiation in the middle and downstream of NRB with warm temperate climate,fully humid(Cf)and warm temperate climate with dry winter(Cw).
基金supported by the National Natural Science Foundation of China,Nos.82404892(to QY),82061160374(to ZZ)the Science and Technology Development Fund,Macao Special Administrative Region,China,Nos.0023/2020/AFJ,0035/2020/AGJ+2 种基金the University of Macao Research Grant,Nos.MYRG2022-00248-ICMS,MYRG-CRG2022-00010-ICMS(to MPMH)the Natural Science Foundation of Guangdong Province,No.2024A1515012818(to ZZ)the Fundamental Research Funds for the Central Universities,No.21623114(to ZZ).
文摘Drug development for Alzheimer’s disease is extremely challenging,as demonstrated by the repeated failures of amyloid-β-targeted therapeutics and the controversies surrounding the amyloid-βcascade hypothesis.More recently,advances in the development of Lecanemab,an anti-amyloid-βmonoclonal antibody,have shown positive results in reducing brain A burden and slowing cognitive decline in patients with early-stage Alzheimer’s disease in the Phase Ⅲ clinical trial(Clarity Alzheimer’s disease).Despite these promising results,side effects such as amyloid-related imaging abnormalities(ARIA)may limit its usage.ARIA can manifest as ARIA-E(cerebral edema or effusions)and ARIA-H(microhemorrhages or superficial siderosis)and is thought to be caused by increased vascular permeability due to inflammatory responses,leading to leakages of blood products and protein-rich fluid into brain parenchyma.Endothelial dysfunction is an early pathological feature of Alzheimer’s disease,and the blood-brain barrier becomes increasingly leaky as the disease progresses.In addition,APOE4,the strongest genetic risk factor for Alzheimer’s disease,is associated with higher vascular amyloid burden,increased ARIA incidence,and accelerated blood-brain barrier disruptions.These interconnected vascular abnormalities highlight the importance of vascular contributions to the pathophysiology of Alzheimer’s disease.Here,we will closely examine recent research evaluating the heterogeneity of brain endothelial cells in the microvasculature of different brain regions and their relationships with Alzheimer’s disease progression.
文摘Background:Utilizing population-based survey data in epidemiological research with a spatial perspective can integrate valuable context into the dynamics of HIV prevalence in West Africa.However,the situation in the Mano River Union(MRU)countries is largely unknown.This research aims to perform an ecological study to determine the HIV prevalence patterns in MRU.Methods:We analyzed Demographic and Health Survey(DHS)and AIDS Indicator Survey(AIS)data on HIV prevalence in MRU from 2005 to 2020.We examined the country-specifc,regional-specifc and sex-specifc ratios of respondents to profle the spatial–temporal heterogeneity of HIV prevalence and determine HIV hot spots.We employed Geodetector to measure the spatial stratifed heterogeneity(SSH)of HIV prevalence for adult women and men.We assessed the comprehensive correct knowledge(CCK)about HIV/AIDS and HIV testing uptake by employing the Least Absolute Shrinkage and Selection Operator(LASSO)regression to predict which combinations of CCKs can scale up the ratio of HIV testing uptake with sex-specifc needs.Results:In our analysis,we leveraged data for 158,408 respondents from 11 surveys in the MRU.From 2005–2015,Cote d’Ivoire was the hot spot for HIV prevalence with a Gi_Bin score of 3,Z-Score 8.0–10.1 and P<0.001.From 2016 to 2020,Guinea and Sierra Leone were hot spots for HIV prevalence with a Gi_Bin score of 2,Z-Score of 3.17 and P<0.01.The SSH confrmed the signifcant diferences in HIV prevalence at the national level strata,with a higher level for Cote d’Ivoire compared to other countries in both sexes with q-values of 0.61 and 0.40,respectively.Our LASSO model predicted diferent combinations of CCKs with sex-specifc needs to improve HIV testing uptake.Conclusions:The spatial distribution of HIV prevalence in the MRU is skewed and the CCK about HIV/AIDS and HIV testing uptake are far below the threshold target set by UNAIDS for ending the epidemic in the sub-region.Geodetector detected statistically signifcant SSH within and between countries in the MRU.Our LASSO model predicted that diferent emphases should be implemented when popularizing the CCK about HIV/AIDS for adult women and men.
基金supported by the National Natural Science Foundation of China(Nos.U19A2044,42105132,42030609,41975037,and 42105133)the National Key Research and Development Program of China(No.2022YFC3703502)+1 种基金the Plan for Anhui Major Provincial Science&Technology Project(No.202203a07020003)Hefei Ecological Environment Bureau Project(No.2020BFFFD01804).
文摘As a significant city in the Yangtze River Delta regions,Hefei has experienced rapid changes in the sources of air pollution due to its high-speed economic development and urban expansion.However,there has been limited research in recent years on the spatial-temporal distribution and emission of its atmospheric pollutants.To address this,this study conducted mobile observations of urban roads using the Mobile-DOAS instrument from June 2021 to May 2022.The monitoring results exhibit a favourable consistent with TROPOMI satellite data and ground monitoring station data.Temporally,there were pronounced seasonal variations in air pollutants.Spatially,high concentration of HCHO and NO_(2)were closely associated with traffic congestion on roadways,while heightened SO_(2)levels were attributed to winter heating and industrial emissions.The study also revealed that with the implementation of road policies,the average vehicle speed increased by 95.4%,while the NO concentration decreased by 54.4%.In the estimation of urban NO_(x)emission flux,it was observed that in temporal terms,compared with inventory data,the emissions calculated viamobile measurements exhibitedmore distinct seasonal patterns,with the highest emission rate of 349 g/sec in winter and the lowest of 142 g/sec in summer.In spatial terms,the significant difference in emissions between the inner and outer ring roads also suggests the presence of the city’s primary NO_(x)emission sources in the area between these two rings.This study offers data support for formulating the next phase of air pollution control measures in urban areas.
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Chinese Scholarship Council(202206240086)National Natural Science Foundation of China(81974099,82170785,81974098,82170784)+4 种基金National Key Research and Development Program of China(2021YFC2009303)programs from Science and Technology Department of Sichuan Province(2021YFH0172)Young Investigator Award of Sichuan University 2017(2017SCU04A17)Technology Innovation Research and Development Project of Chengdu Science and Technology Bureau(2019-YF05-00296-SN)Sichuan University-Panzhihua science and technology cooperation special fund(2020CDPZH-4).
文摘In recent years,advancements in single-cell and spatial transcriptomics,which are highly regarded developments in the current era,particularly the emerging integration of single-cell and spatiotemporal transcriptomics,have enabled a detailed molecular comprehension of the complex regulation of cell fate.The insights obtained from these methodologies are anticipated to significantly contribute to the development of personalized medicine.Currently,single-cell technology is less frequently utilized for prostate cancer compared with other types of tumors.Start-ing from the perspective of RNA sequencing technology,this review outlined the signifcance of single-cell RNA sequencing(scRNA-seq)in prostate cancer research,encompassing preclinical medicine and clinical applications.We summarize the differences between mouse and human prostate cancer as revealed by scRNA-seq studies,as well as a combination of multi-omics methods involving scRNA-seq to highlight the key molecular targets for the diagnosis,treatment,and drug resistance characteristics of prostate cancer.These studies are expected to provide novel insights for the development of immunotherapy and other innovative treatment strategies for castration-resistant prostate cancer.Furthermore,we explore the potential clinical applications stemming from other single-cell technologies in this review,paving the way for future research in precision medicine.
基金supported by a grant from the Progressive MS Alliance(BRAVE in MS)Le Grand Portage Fund。
文摘Mature oligodendrocytes form myelin sheaths that are crucial for the insulation of axons and efficient signal transmission in the central nervous system.Recent evidence has challenged the classical view of the functionally static mature oligodendrocyte and revealed a gamut of dynamic functions such as the ability to modulate neuronal circuitry and provide metabolic support to axons.Despite the recognition of potential heterogeneity in mature oligodendrocyte function,a comprehensive summary of mature oligodendrocyte diversity is lacking.We delve into early 20th-century studies by Robertson and Río-Hortega that laid the foundation for the modern identification of regional and morphological heterogeneity in mature oligodendrocytes.Indeed,recent morphologic and functional studies call into question the long-assumed homogeneity of mature oligodendrocyte function through the identification of distinct subtypes with varying myelination preferences.Furthermore,modern molecular investigations,employing techniques such as single cell/nucleus RNA sequencing,consistently unveil at least six mature oligodendrocyte subpopulations in the human central nervous system that are highly transcriptomically diverse and vary with central nervous system region.Age and disease related mature oligodendrocyte variation denotes the impact of pathological conditions such as multiple sclerosis,Alzheimer's disease,and psychiatric disorders.Nevertheless,caution is warranted when subclassifying mature oligodendrocytes because of the simplification needed to make conclusions about cell identity from temporally confined investigations.Future studies leveraging advanced techniques like spatial transcriptomics and single-cell proteomics promise a more nuanced understanding of mature oligodendrocyte heterogeneity.Such research avenues that precisely evaluate mature oligodendrocyte heterogeneity with care to understand the mitigating influence of species,sex,central nervous system region,age,and disease,hold promise for the development of therapeutic interventions targeting varied central nervous system pathology.
基金supported by the Natural Science Foundation of Xinjiang Uygur Autonomous Region(No.2022D01B187).
文摘Heterogeneous federated learning(HtFL)has gained significant attention due to its ability to accommodate diverse models and data from distributed combat units.The prototype-based HtFL methods were proposed to reduce the high communication cost of transmitting model parameters.These methods allow for the sharing of only class representatives between heterogeneous clients while maintaining privacy.However,existing prototype learning approaches fail to take the data distribution of clients into consideration,which results in suboptimal global prototype learning and insufficient client model personalization capabilities.To address these issues,we propose a fair trainable prototype federated learning(FedFTP)algorithm,which employs a fair sampling training prototype(FSTP)mechanism and a hyperbolic space constraints(HSC)mechanism to enhance the fairness and effectiveness of prototype learning on the server in heterogeneous environments.Furthermore,a local prototype stable update(LPSU)mechanism is proposed as a means of maintaining personalization while promoting global consistency,based on contrastive learning.Comprehensive experimental results demonstrate that FedFTP achieves state-of-the-art performance in HtFL scenarios.
基金supported by the National Office for Philosophy and Social Sciences(grant reference 22&ZD067).
文摘In the current situation of decelerating economic expansion,examining the digital economy(DE)as a novel economic model is beneficial for the local economy’s sustainable and high-quality development(HQD).We analyzed panel data from the Yellow River(YR)region from 2013 to 2021 and discovered notable spatial variances in the composite index and coupling coordination of the two systems.Specifically,the downstream region exhibited the highest coupling coordination,while the upstream region had the lowest.We identified that favorable factors such as economic development,innovation,industrial upgrading,and government intervention can bolster the coupling.Our findings provide a valuable framework for promoting DE and HQD in the YR region.
基金supported by the National Natural Science Foundation of China(Grant Nos.62472149,62376089,62202147)Hubei Provincial Science and Technology Plan Project(2023BCB04100).
文摘Accurate traffic flow prediction has a profound impact on modern traffic management. Traffic flow has complex spatial-temporal correlations and periodicity, which poses difficulties for precise prediction. To address this problem, a Multi-head Self-attention and Spatial-Temporal Graph Convolutional Network (MSSTGCN) for multiscale traffic flow prediction is proposed. Firstly, to capture the hidden traffic periodicity of traffic flow, traffic flow is divided into three kinds of periods, including hourly, daily, and weekly data. Secondly, a graph attention residual layer is constructed to learn the global spatial features across regions. Local spatial-temporal dependence is captured by using a T-GCN module. Thirdly, a transformer layer is introduced to learn the long-term dependence in time. A position embedding mechanism is introduced to label position information for all traffic sequences. Thus, this multi-head self-attention mechanism can recognize the sequence order and allocate weights for different time nodes. Experimental results on four real-world datasets show that the MSSTGCN performs better than the baseline methods and can be successfully adapted to traffic prediction tasks.
基金funded by the National Key Research and Development Program of China(grant number 2023YFC3009204)the National Natural Science Foundation of China(grant number 52174015).
文摘Field tests have demonstrated that depressurization with controlled sand production is an effective technique for natural gas hydrate extraction.Variations in depositional environments and processes result in significant heterogeneity within subsea natural gas hydrate-bearing sediments.However,the influence of permeability heterogeneity on production performance during depressurization with controlled sand production remains inadequately understood.In this study,a multiphase,multi-component mathematical model is developed to simulate depressurization with controlled sand production in methane hydrate-bearing sediments,incorporating geological conditions representative of unconsolidated argillaceous siltstone hydrate deposits in the Shenhu area of the South China Sea.The effects of permeability heterogeneity-specifically,horizontal autocorrelation length and global permeability heterogeneity-on production performance during depressurization with sand production are investigated using geostatistical modeling combined with finite difference method based numerical simulations.Results show that as the horizontal autocorrelation length of permeability distribution increases,cumulative gas production first rises and then declines,reaching its peak at λ_(Dh)=0.1,whereas sand production steadily increases.In addition,higher formation permeability heterogeneity results in increased cumulative gas and sand production,suggesting that greater heterogeneity promotesmethane hydrate decomposition and gas recovery.These findings can offer valuable insights for optimizing future field development of hydrate-bearing sediments by depressurization with controlled sand production.
基金supported by the National Natural Science Foundation of China(Grant Nos.42227804 and 42402279)the Natural Science Foundation of Shanghai(Grant No.24ZR1467500).
文摘Due to severe mass transfer limitations,the remediation efficiency of low-permeability contaminated sites often fails to meet expectations.Hydraulic fracturing technology has been utilized to enhance amendment delivery,but the influence of soil heterogeneity is commonly overlooked.To address this issue,this study develops a numerical model to simulate the enhanced transport of amendments,incorporating convection,diffusion,adsorption,and degradation processes.Within the model,random permeability fields are generated based on geostatistical methods to explore how soil heterogeneity affects amendment injection efficiency,distribution characteristics,and the underlying physical mechanisms.The results indicate that(1)soil heterogeneity significantly reduces the amendment injection efficiency,with stronger heterogeneity correlating to lower efficiency,(2)soil heterogeneity markedly alters the amendment distribution characteristics,leading to the formation of localized“nodes”,(3)the mechanism by which heterogeneity reduces injection efficiency involves decreasing the density of preferential flow paths in the soil,and(4)the adverse effects of heterogeneity can be mitigated by employing pressure compensation or adjusting well spacing.
基金supported by the National Natural Science Foun-dation of China(No.52401222)Zhejiang Provincial Natural Sci-ence Foundation(LQN25E010011)+2 种基金Ningbo Natural Science Founda-tion(2024J073)Ningbo Major Special Projects of the Plan“Science and Technology Innovation 2025"(No.2022Z107)Ningbo Key Research and Development Program(No.2023Z097).
文摘By employing micrometer-diameter microelectrodes, the metastable pitting corrosion behavior of Co_(68.15)Fe_(4.35)Si_(12.5)B_(12)Cr_(3) metallic glasses (MGs) exposed to 0.6 mol/L NaCl solution was investigated to clarify the correlation between metastable pitting and structural heterogeneity in MGs. Thermally induced degeneration of structural heterogeneity inhibits the initiation, decelerates the growth kinetics, and accelerates the repassivation kinetics of metastable pits while also decreasing the probability of transition from metastability to stability. This enhanced resistance to pitting corrosion is attributed to a reduction in active pitting precursor sites and a decrease in electrochemical activity caused by the structural homogenization of MGs.
基金supported by the Beijing Natural Science Foundation(Certificate Number:L234025).
文摘Spatial-temporal traffic prediction technology is crucial for network planning,resource allocation optimizing,and user experience improving.With the development of virtual network operators,multi-operator collaborations,and edge computing,spatial-temporal traffic data has taken on a distributed nature.Consequently,noncentralized spatial-temporal traffic prediction solutions have emerged as a recent research focus.Currently,the majority of research typically adopts federated learning methods to train traffic prediction models distributed on each base station.This method reduces additional burden on communication systems.However,this method has a drawback:it cannot handle irregular traffic data.Due to unstable wireless network environments,device failures,insufficient storage resources,etc.,data missing inevitably occurs during the process of collecting traffic data.This results in the irregular nature of distributed traffic data.Yet,commonly used traffic prediction models such as Recurrent Neural Networks(RNN)and Long Short-Term Memory(LSTM)typically assume that the data is complete and regular.To address the challenge of handling irregular traffic data,this paper transforms irregular traffic prediction into problems of estimating latent variables and generating future traffic.To solve the aforementioned problems,this paper introduces split learning to design a structured distributed learning framework.The framework comprises a Global-level Spatial structure mining Model(GSM)and several Nodelevel Generative Models(NGMs).NGM and GSM represent Seq2Seq models deployed on the base station and graph neural network models deployed on the cloud or central controller.Firstly,the time embedding layer in NGM establishes the mapping relationship between irregular traffic data and regular latent temporal feature variables.Secondly,GSM collects statistical feature parameters of latent temporal feature variables from various nodes and executes graph embedding for spatial-temporal traffic data.Finally,NGM generates future traffic based on latent temporal and spatial feature variables.The introduction of the time attention mechanism enhances the framework’s capability to handle irregular traffic data.Graph attention network introduces spatially correlated base station traffic feature information into local traffic prediction,which compensates for missing information in local irregular traffic data.The proposed framework effectively addresses the distributed prediction issues of irregular traffic data.By testing on real world datasets,the proposed framework improves traffic prediction accuracy by 35%compared to other commonly used distributed traffic prediction methods.
基金supported by the National Natural Science Foundation of China(82002432 to J.W.,82302068 to M.Z.,and 32300568 to T.W.)the Natural Science Foundation of Shandong Province(ZR2024MH159 to Y.Z.,ZR2020QH179 to J.W.,ZR2022QH057 to M.Z.,and ZR2021QH005 to T.W.)the China Postdoctoral Science Foundation(2024M752006 to S.M.)。
文摘Although the spatial characteristics within the tumor microenvironment of lung adenocarcinoma(LUAD)have been identified,the mechanisms by which these factors promote LUAD progression and immune evasion remain unclear.Using spatial transcriptomics and single-cell RNA-sequencing data from multi-regional LUAD biopsies consisting of tumor core,tumor edge,and normal area,we sought to delineate the spatial heterogeneity and driving factors of cell colocalization.Two cancer cell sub-clusters(Cancer_c1 and Cancer_c2),associated with LUAD initiation and metastasis,respectively,exhibit distinct spatial distributions and immune cell colocalizations.In particular,Cancer_c1,enriched within the tumor core,could directly interact with B cells or indirectly recruit B cells through macrophages.Conversely,Cancer_c2 enriched within the tumor edge exhibits colocalization with CD8^(+)T cells.Collectively,our work elucidates the spatial distribution of cancer cell subtypes and their interaction with immune cells in the core and edge of LUAD,providing insights for developing therapeutic strategies for cancer intervention.
基金funded by the Guangdong Province general university Young Innovative Talents Program Project(2024KQNCX153)Postdoctoral Research Start-up Funds of Dongguan University of Technology。
文摘The trade-off between strength and ductility has long been a challenge for Mg alloy.To address this issue,bimodal-structured AZ80 Mg alloys with varying heterogeneity levels were fabricated via low-temperature extrusion in this work.The results reveal the microstructure comprising second-phase particle(SP_(p),β-Mg_(17)Al_(12)and Mg_(3) Mn_(2) Al_(18))-reinforced fine grains(FGs)FGs and SP_(p)-free coarse grains(CGs),with the heterogeneity level decreasing as extrusion temperature increases.As the heterogeneity level decreases,the synergistic deformation capacity initially improves,reaching a maximum at the moderate heterogeneity level of 0.31 GPa and 0.238,and then declines.This exceptional capacity is attributed to the hetero-deformation induced(HDI)stress,which effectively alleviates the strain gradients by activating〈c+a〉dislocations and non-basal〈a〉dislocations during deformation.An optimal combination of 287 MPa in yield strength,393 MPa in ultimate tensile strength,and 14.96%in elongation is achieved in the alloy with a moderate heterogeneity level.The excellent strength-ductility synergy originates from the enhanced capacity of dislocations accumulation driven by remarkable capacity of synergistic deformation and the synergistic strengthening mechanisms.This work provides a new insight into the design of bimodal structure to produce high-performance Mg alloys.
基金Financial supports from the National Natural Science Foundation of China(21503039)Department of Science and Technology of Liaoning Province(2019MS164)+1 种基金Department of Education of Liaoning Province(LJ2020JCL034)Discipline Innovation Team of Liaoning Technical University(LNTU20TD-16)are greatly acknowledged。
文摘Layered rare-earth metal oxides,harnessing the dual properties of oxides and two-dimensional layered materials,exhibit remarkable thermal stability and quantum confinement effects.Therefore,this work adopts the first-principles calculation combined with the Boltzmann transport theory to predict the thermoelectric properties of NdZnSbO compound.The coexistence of weak interlayer van der Waals interactions,robust intralayer ionic bonding,and partial covalent bonding leads to remarkable bonding heterogeneity,which engenders pronounced phonon scattering and imposes constraints on thermal transport along the out-of-plane direction.The weakened chemical bonds induced by the antibonding states,together with the rattling-like behavior of the Zn atom,culminate in the profound anharmonicity in the layered NdZnSbO compound.The weakening bond and heavy element contribute to the softness of phonon modes,which significantly diminishes the phonon group velocity.The redistribution-dominated four-phonon scattering process spans a large optical gap,which effectively reduces the lattice thermal conductivity.The NdZnSbO compound exhibits direct semiconductor characteristic with a bandgap of 0.73 e V by adopting the Heyd-Scuseria-Ernzerhof(HSE06)functional in combination with spin–orbit coupling(SOC)effect.The multi-valley feature of NdZnSbO compound augur favorably for band degeneracy,thus amplifying the power factor.Consequently,an optimal figure-of-merit(ZT)of 3.40 at 900 K is achieved for the n-type NdZnSbO compound.The present study delves deeply insights into the origins for the low thermal conductivity of NdZnSbO compound and proposes an optimization scheme to enhance overall thermoelectric performance.
基金supported by the Key Program of the National Natural Science Foundation of China(Grant No.92047201)the Fundamental Research Funds for the Central Universities(Grant No.B230201026)+1 种基金the National Natural Science Foundation of China(Grants No.42377054 and 42007149)the Open Project of Jiangsu Key Laboratory for Eco-Agricultural Biotechnology around Hongze Lake(Grant No.HZHLAB2301).
文摘Reservoirs play a critical role in addressing water resources challenges.However,their vertical influence on the assembly mechanisms of different microbial communities,including prokaryotes and eukaryotes,remains unclear.This study examined the vertical diversity patterns of abundant and rare subcommunities of prokaryotes and eukaryotes in an urban reservoir,using water depth as a geographical gradient and employing high-throughput sequencing.The impact of vertical environmental heterogeneity on community structure was quantified,and key drivers of these dynamics were identified.The results indicated that the urban reservoir exhibited statistically significant differences in the vertical distribution of water temperature and oxidation/reduction potential.The a-diversity of the abundant subcommunity displayed an opposing vertical pattern compared to that of the rare subcommunity,while the b-diversity for both subcommunities of prokaryotes and eukaryotes increased with water depth.Moreover,the distinct diversity patterns of abundant and rare subcommunities were associated with environmental heterogeneity and species adaptability.Notably,the b-diversity of the rare subcommunity of eukaryotes was primarily driven by species turnover in surface water,whereas nestedness became the dominant factor in deeper water.Furthermore,eukaryotic microbes exhibited a more pronounced response to changes in water depth than prokaryotes,consistent with the importance of heterogeneous selection to the eukaryotic community.Water temperature significantly affected the community composition of all groups,highlighting its importance in shaping community dynamics.This study provides valuable insights into the vertical distribution and assembly mechanisms of microbial communities in urban reservoirs,contributing to the protection and management of aquatic ecosystems under river regulation.
