This study was aimed to prepare landslide susceptibility maps for the Pithoragarh district in Uttarakhand,India,using advanced ensemble models that combined Radial Basis Function Networks(RBFN)with three ensemble lear...This study was aimed to prepare landslide susceptibility maps for the Pithoragarh district in Uttarakhand,India,using advanced ensemble models that combined Radial Basis Function Networks(RBFN)with three ensemble learning techniques:DAGGING(DG),MULTIBOOST(MB),and ADABOOST(AB).This combination resulted in three distinct ensemble models:DG-RBFN,MB-RBFN,and AB-RBFN.Additionally,a traditional weighted method,Information Value(IV),and a benchmark machine learning(ML)model,Multilayer Perceptron Neural Network(MLP),were employed for comparison and validation.The models were developed using ten landslide conditioning factors,which included slope,aspect,elevation,curvature,land cover,geomorphology,overburden depth,lithology,distance to rivers and distance to roads.These factors were instrumental in predicting the output variable,which was the probability of landslide occurrence.Statistical analysis of the models’performance indicated that the DG-RBFN model,with an Area Under ROC Curve(AUC)of 0.931,outperformed the other models.The AB-RBFN model achieved an AUC of 0.929,the MB-RBFN model had an AUC of 0.913,and the MLP model recorded an AUC of 0.926.These results suggest that the advanced ensemble ML model DG-RBFN was more accurate than traditional statistical model,single MLP model,and other ensemble models in preparing trustworthy landslide susceptibility maps,thereby enhancing land use planning and decision-making.展开更多
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
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
Phthalate esters(PAEs),recognized as endocrine disruptors,are released into the environment during usage,thereby exerting adverse ecological effects.This study investigates the occurrence,sources,and risk assessment o...Phthalate esters(PAEs),recognized as endocrine disruptors,are released into the environment during usage,thereby exerting adverse ecological effects.This study investigates the occurrence,sources,and risk assessment of PAEs in surface water obtained from 36 sampling points within the Yellow River and Yangtze River basins.The total concentration of PAEs in the Yellow River spans from124.5 to 836.5 ng/L,with Dimethyl phthalate(DMP)(75.4±102.7 ng/L)and Diisobutyl phthalate(DiBP)(263.4±103.1 ng/L)emerging as the predominant types.Concentrations exhibit a pattern of upstream(512.9±202.1 ng/L)>midstream(344.5±135.3 ng/L)>downstream(177.8±46.7 ng/L).In the Yangtze River,the total concentration ranges from 81.9 to 441.6 ng/L,with DMP(46.1±23.4 ng/L),Diethyl phthalate(DEP)(93.3±45.2 ng/L),and DiBP(174.2±67.6 ng/L)as the primary components.Concentration levels follow a midstream(324.8±107.3 ng/L)>upstream(200.8±51.8 ng/L)>downstream(165.8±71.6 ng/L)pattern.Attention should be directed towards the moderate ecological risks of DiBP in the upstream of HH,and both the upstream and midstream of CJ need consideration for the moderate ecological risks associated with Di-n-octyl phthalate(DNOP).Conversely,in other regions,the associated risk with PAEs is either low or negligible.The main source of PAEs in Yellow River is attributed to the release of construction land,while in the Yangtze River Basin,it stems from the accumulation of pollutants in lakes and forests discharged into the river.These findings are instrumental for pinpointing sources of PAEs pollution and formulating control strategies in the Yellow and Yangtze Rivers,providing valuable insights for global PAEs research in other major rivers.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
Since the release of ChatGPT in late 2022,Generative Artificial Intelligence(GAI)has gained widespread attention because of its impressive capabilities in language comprehension,reasoning,and generation.GAI has been s...Since the release of ChatGPT in late 2022,Generative Artificial Intelligence(GAI)has gained widespread attention because of its impressive capabilities in language comprehension,reasoning,and generation.GAI has been successfully applied across various aspects(e.g.,creative writing,code generation,translation,and information retrieval).In cartography and GIS,researchers have employed GAI to handle some specific tasks,such as map generation,geographic question answering,and spatiotemporal data analysis,yielding a series of remarkable results.Although GAI-based techniques are developing rapidly,literature reviews of their applications in cartography and GIS remain relatively limited.This paper reviews recent GAI-related research in cartography and GIS,focusing on three aspects:①map generation,②geographical analysis,and③evaluation of GAI’s spatial cognition abilities.In addition,the paper analyzes current challenges and proposes future research directions.展开更多
On September 5,2022,at least 10,855 landslides had been triggered by a magnitude Mw 6.7(Ms 6.8)earthquake on the eastern margin of the Tibetan Plateau.Unfortunately,a detailed analysis of the spatial patterns of lands...On September 5,2022,at least 10,855 landslides had been triggered by a magnitude Mw 6.7(Ms 6.8)earthquake on the eastern margin of the Tibetan Plateau.Unfortunately,a detailed analysis of the spatial patterns of landslides in the eastern margin of the Baryan Har block is lacking.The observations show that the highest landslide concentrations are distributed along the seismogenic fault(Moxi fault)and Dadu River valley,coinciding with the effects of the hanging wall and microepicenter.Seismogenic tectonics controlled the regional distribution of new landslides,and the local topography influenced the detailed positions on the slopes.The total landslide mass wasting volume was 223.1×10^(6)m^(3),and the maximum occurred in the Wandong Basin(value of 74×10^(6)m^(3)).Thirty landslide dams were temporarily existing.Although some local collapses occurred at the toe of the Hailuogou glacier,seismic shaking had no obvious influence on the overall stability of the glacier.A post debris flow assessment indicates that some large basins contained much loose material and that some steep small basins had high debris flow susceptibility.On the eastern margin of the Bayan Har block,the landslide-triggering thrust and strike-slip events both follow the distributions of the hanging wall.展开更多
Majority of carbon emissions originate from fossil energy consumption,thus necessitating calculation and monitoring of carbon emissions from energy consumption.In this study,we utilized energy consumption data from Si...Majority of carbon emissions originate from fossil energy consumption,thus necessitating calculation and monitoring of carbon emissions from energy consumption.In this study,we utilized energy consumption data from Sichuan Province and Chongqing Municipality for the years 2000 to 2019 to estimate their statistical carbon emissions.We then employed nighttime light data to downscale and infer the spatial distribution of carbon emissions at the county level within the Chengdu-Chongqing urban agglomeration.Furthermore,we analyzed the spatial pattern of carbon emissions at the county level using the coefficient of variation and spatial autocorrelation,and we used the Geographically and Temporally Weighted Regression(GTWR)model to analyze the influencing factors of carbon emissions at this scale.The results of this study are as follows:(1)from 2000 to 2019,the overall carbon emissions in the Chengdu-Chongqing urban agglomeration showed an increasing trend followed by a decrease,with an average annual growth rate of 4.24%.However,in recent years,it has stabilized,and 2012 was the peak year for carbon emissions in the Chengdu-Chongqing urban agglomeration;(2)carbon emissions exhibited significant spatial clustering,with high-high clustering observed in the core urban areas of Chengdu and Chongqing and low-low clustering in the southern counties of the Chengdu-Chongqing urban agglomeration;(3)factors such as GDP,population(Pop),urbanization rate(Ur),and industrialization structure(Ic)all showed a significant influence on carbon emissions;(4)the spatial heterogeneity of each influencing factor was evident.展开更多
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
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
Fifty agricultural soil samples collected from Fuzhou,southeast China,were first investigated for the occurrence,distribution,and potential risks of twelve organophosphate esters(OPEs).The total concentration of OPEs(...Fifty agricultural soil samples collected from Fuzhou,southeast China,were first investigated for the occurrence,distribution,and potential risks of twelve organophosphate esters(OPEs).The total concentration of OPEs(ΣOPEs)in soil ranged from 1.33 to 96.5 ng/g dry weight(dw),with an average value of 17.1 ng/g dw.Especially,halogenated-OPEs were the predominant group with amean level of 9.75 ng/g dw,and tris(1-chloro-2-propyl)phosphate(TCIPP)was the most abundant OPEs,accounting for 51.1%ofΣOPEs.The concentrations of TCIPP andΣOPEs were found to be significantly higher(P<0.05)in soils of urban areas than those in suburban areas.In addition,the use of agricultural plastic films and total organic carbon had a positive effect on the occurrence of OPE in this study.The positive matrix factorization model suggested complex sources of OPEs in agricultural soils from Fuzhou.The ecological risk assessment demonstrated that tricresyl phosphate presented a medium risk to land-based organisms(0.1≤risk quotient<1.0).Nevertheless,the carcinogenic and noncarcinogenic risks for human exposure to OPEs through soil ingestion and dermal absorption were negligible.These findings would facilitate further investigations into the pollution management and risk control of OPEs.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
X-ray detectors show potential applications in medical imaging,materials science,and nuclear energy.To achieve high detection efficiency and spatial resolution,many conventional semiconductor materials,such as amorpho...X-ray detectors show potential applications in medical imaging,materials science,and nuclear energy.To achieve high detection efficiency and spatial resolution,many conventional semiconductor materials,such as amorphous selenium,cadmium telluride zinc,and perovskites,have been utilized in direct conversion X-ray detectors.However,these semiconductor materials are susceptible to temperature-induced performance degradation,crystallization,delamination,uneven lattice growth,radiation damage,and high dark current.This study explores a new approach by coupling an FC40 electronic fluorinated liquid with a specialized high-resolution and high-readout-speed complementary metal-oxide-semiconductor(CMOS)pixel array,specifically the Topmetal II−chip,to fabricate a direct conversion X-ray detector.The fluorinated liquid FC40(molecular formula:C_(21)F_(48)N_(2))is an electronic medium that is minimally affected by temperature and displays no issues with uniform conductivity.It exhibits a low dark current and minimal radiation damage and enables customizable thickness in X-ray absorption.This addresses the limitations inherent in conventional semiconductor-based detectors.In this study,simple X-ray detector imaging tests were conducted,demonstrating the excellent coupling capability between FC40 electronic fluorinated liquid and CMOS chips by the X-ray detector.A spatial resolution of 4.0 lp/mm was measured using a striped line par card,and a relatively clear image of a cockroach was displayed in the digital radiography imaging results.Preliminary test results indicated the feasibility of fabricating an X-ray detector by combining FC40 electronic fluorinated liquid and CMOS chips.Owing to the absence of issues related to chip-material coupling,a high spatial resolution could be achieved by reducing the chip pixel size.This method presents a new avenue for studies on novel liquid-based direct conversion X-ray detectors.展开更多
A new method based on the iterative adaptive algorithm(IAA)and blocking matrix preprocessing(BMP)is proposed to study the suppression of multi-mainlobe interference.The algorithm is applied to precisely estimate the s...A new method based on the iterative adaptive algorithm(IAA)and blocking matrix preprocessing(BMP)is proposed to study the suppression of multi-mainlobe interference.The algorithm is applied to precisely estimate the spatial spectrum and the directions of arrival(DOA)of interferences to overcome the drawbacks associated with conventional adaptive beamforming(ABF)methods.The mainlobe interferences are identified by calculating the correlation coefficients between direction steering vectors(SVs)and rejected by the BMP pretreatment.Then,IAA is subsequently employed to reconstruct a sidelobe interference-plus-noise covariance matrix for the preferable ABF and residual interference suppression.Simulation results demonstrate the excellence of the proposed method over normal methods based on BMP and eigen-projection matrix perprocessing(EMP)under both uncorrelated and coherent circumstances.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
Edge structures are ubiquitous in the processing and fabrication of various optoelectronic devices.Novel physical properties and enhanced light–matter interactions are anticipated to occur at crystal edges due to the...Edge structures are ubiquitous in the processing and fabrication of various optoelectronic devices.Novel physical properties and enhanced light–matter interactions are anticipated to occur at crystal edges due to the broken spatial translational symmetry.However,the intensity of first-order Raman scattering at crystal edges has been rarely explored,although the mechanical stress and edge characteristics have been thoroughly studied by the Raman peak shift and the spectral features of the edge-related Raman modes.Here,by taking Ga As crystal with a well-defined edge as an example,we reveal the intensity enhancement of Raman-active modes and the emergence of Raman-forbidden modes under specific polarization configurations at the edge.This is attributed to the presence of a hot spot at the edge due to the redistributed electromagnetic fields and electromagnetic wave propagations of incident laser and Raman signal near the edge,which are confirmed by the finite-difference time-domain simulations.Spatially-resolved Raman intensities of both Raman-active and Raman-forbidden modes near the edge are calculated based on the redistributed electromagnetic fields,which quantitatively reproduce the corresponding experimental results.These findings offer new insights into the intensity enhancement of Raman scattering at crystal edges and present a new avenue to manipulate light–matter interactions of crystal by manufacturing various types of edges and to characterize the edge structures in photonic and optoelectronic devices.展开更多
Secondary injury following spinal cord injury is primarily characterized by a complex inflammatory response,with resident microglia and infiltrating macrophages playing pivotal roles.While previous studies have groupe...Secondary injury following spinal cord injury is primarily characterized by a complex inflammatory response,with resident microglia and infiltrating macrophages playing pivotal roles.While previous studies have grouped these two cell types together based on similarities in structure and function,an increasing number of studies have demonstrated that microglia and macrophages exhibit differences in structure and function and have different effects on disease processes.In this study,we used single-cell RNA sequencing and spatial transcriptomics to identify the distinct evolutionary paths of microglia and macrophages following spinal cord injury.Our results showed that microglia were activated to a pro-inflammatory phenotype immediately after spinal cord injury,gradually transforming to an anti-inflammatory steady state phenotype as the disease progressed.Regarding macrophages,our findings highlighted abundant communication with other cells,including fibroblasts and neurons.Both pro-inflammatory and neuroprotective effects of macrophages were also identified;the pro-inflammatory effect may be related to integrin β2(Itgb2) and the neuroprotective effect may be related to the oncostatin M pathway.These findings were validated by in vivo experiments.This research underscores differences in the cellular dynamics of microglia and macrophages following spinal cord injury,and may offer new perspectives on inflammatory mechanisms and potential therapeutic targets.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
Seal authentication is an important task for verifying the authenticity of stamped seals used in various domains to protect legal documents from tampering and counterfeiting.Stamped seal inspection is commonly audited...Seal authentication is an important task for verifying the authenticity of stamped seals used in various domains to protect legal documents from tampering and counterfeiting.Stamped seal inspection is commonly audited manually to ensure document authenticity.However,manual assessment of seal images is tedious and laborintensive due to human errors,inconsistent placement,and completeness of the seal.Traditional image recognition systems are inadequate enough to identify seal types accurately,necessitating a neural network-based method for seal image recognition.However,neural network-based classification algorithms,such as Residual Networks(ResNet)andVisualGeometryGroup with 16 layers(VGG16)yield suboptimal recognition rates on stamp datasets.Additionally,the fixed training data categories make handling new categories to be a challenging task.This paper proposes amulti-stage seal recognition algorithmbased on Siamese network to overcome these limitations.Firstly,the seal image is pre-processed by applying an image rotation correction module based on Histogram of Oriented Gradients(HOG).Secondly,the similarity between input seal image pairs is measured by utilizing a similarity comparison module based on the Siamese network.Finally,we compare the results with the pre-stored standard seal template images in the database to obtain the seal type.To evaluate the performance of the proposed method,we further create a new seal image dataset that contains two subsets with 210,000 valid labeled pairs in total.The proposed work has a practical significance in industries where automatic seal authentication is essential as in legal,financial,and governmental sectors,where automatic seal recognition can enhance document security and streamline validation processes.Furthermore,the experimental results show that the proposed multi-stage method for seal image recognition outperforms state-of-the-art methods on the two established datasets.展开更多
基金the University of Transport Technology under the project entitled“Application of Machine Learning Algorithms in Landslide Susceptibility Mapping in Mountainous Areas”with grant number DTTD2022-16.
文摘This study was aimed to prepare landslide susceptibility maps for the Pithoragarh district in Uttarakhand,India,using advanced ensemble models that combined Radial Basis Function Networks(RBFN)with three ensemble learning techniques:DAGGING(DG),MULTIBOOST(MB),and ADABOOST(AB).This combination resulted in three distinct ensemble models:DG-RBFN,MB-RBFN,and AB-RBFN.Additionally,a traditional weighted method,Information Value(IV),and a benchmark machine learning(ML)model,Multilayer Perceptron Neural Network(MLP),were employed for comparison and validation.The models were developed using ten landslide conditioning factors,which included slope,aspect,elevation,curvature,land cover,geomorphology,overburden depth,lithology,distance to rivers and distance to roads.These factors were instrumental in predicting the output variable,which was the probability of landslide occurrence.Statistical analysis of the models’performance indicated that the DG-RBFN model,with an Area Under ROC Curve(AUC)of 0.931,outperformed the other models.The AB-RBFN model achieved an AUC of 0.929,the MB-RBFN model had an AUC of 0.913,and the MLP model recorded an AUC of 0.926.These results suggest that the advanced ensemble ML model DG-RBFN was more accurate than traditional statistical model,single MLP model,and other ensemble models in preparing trustworthy landslide susceptibility maps,thereby enhancing land use planning and decision-making.
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 the Ministry of Science and Technology of China(Nos.2021YFC3200904 and 2022YFC3203705)the National Natural Science Foundation of China(Nos.52270012 and 52070184).
文摘Phthalate esters(PAEs),recognized as endocrine disruptors,are released into the environment during usage,thereby exerting adverse ecological effects.This study investigates the occurrence,sources,and risk assessment of PAEs in surface water obtained from 36 sampling points within the Yellow River and Yangtze River basins.The total concentration of PAEs in the Yellow River spans from124.5 to 836.5 ng/L,with Dimethyl phthalate(DMP)(75.4±102.7 ng/L)and Diisobutyl phthalate(DiBP)(263.4±103.1 ng/L)emerging as the predominant types.Concentrations exhibit a pattern of upstream(512.9±202.1 ng/L)>midstream(344.5±135.3 ng/L)>downstream(177.8±46.7 ng/L).In the Yangtze River,the total concentration ranges from 81.9 to 441.6 ng/L,with DMP(46.1±23.4 ng/L),Diethyl phthalate(DEP)(93.3±45.2 ng/L),and DiBP(174.2±67.6 ng/L)as the primary components.Concentration levels follow a midstream(324.8±107.3 ng/L)>upstream(200.8±51.8 ng/L)>downstream(165.8±71.6 ng/L)pattern.Attention should be directed towards the moderate ecological risks of DiBP in the upstream of HH,and both the upstream and midstream of CJ need consideration for the moderate ecological risks associated with Di-n-octyl phthalate(DNOP).Conversely,in other regions,the associated risk with PAEs is either low or negligible.The main source of PAEs in Yellow River is attributed to the release of construction land,while in the Yangtze River Basin,it stems from the accumulation of pollutants in lakes and forests discharged into the river.These findings are instrumental for pinpointing sources of PAEs pollution and formulating control strategies in the Yellow and Yangtze Rivers,providing valuable insights for global PAEs research in other major rivers.
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National Natural Science Foundation of China(Nos.4210144242394063).
文摘Since the release of ChatGPT in late 2022,Generative Artificial Intelligence(GAI)has gained widespread attention because of its impressive capabilities in language comprehension,reasoning,and generation.GAI has been successfully applied across various aspects(e.g.,creative writing,code generation,translation,and information retrieval).In cartography and GIS,researchers have employed GAI to handle some specific tasks,such as map generation,geographic question answering,and spatiotemporal data analysis,yielding a series of remarkable results.Although GAI-based techniques are developing rapidly,literature reviews of their applications in cartography and GIS remain relatively limited.This paper reviews recent GAI-related research in cartography and GIS,focusing on three aspects:①map generation,②geographical analysis,and③evaluation of GAI’s spatial cognition abilities.In addition,the paper analyzes current challenges and proposes future research directions.
基金supported by the National Natural Science Foundation of China(Grant Nos.U22A20603 and U21A2008)the Science Technology Research Program of the Institute of Mountain Hazards and Environment,Chinese Academy of Sciences(Grant No.IMHE-ZYTS-03).
文摘On September 5,2022,at least 10,855 landslides had been triggered by a magnitude Mw 6.7(Ms 6.8)earthquake on the eastern margin of the Tibetan Plateau.Unfortunately,a detailed analysis of the spatial patterns of landslides in the eastern margin of the Baryan Har block is lacking.The observations show that the highest landslide concentrations are distributed along the seismogenic fault(Moxi fault)and Dadu River valley,coinciding with the effects of the hanging wall and microepicenter.Seismogenic tectonics controlled the regional distribution of new landslides,and the local topography influenced the detailed positions on the slopes.The total landslide mass wasting volume was 223.1×10^(6)m^(3),and the maximum occurred in the Wandong Basin(value of 74×10^(6)m^(3)).Thirty landslide dams were temporarily existing.Although some local collapses occurred at the toe of the Hailuogou glacier,seismic shaking had no obvious influence on the overall stability of the glacier.A post debris flow assessment indicates that some large basins contained much loose material and that some steep small basins had high debris flow susceptibility.On the eastern margin of the Bayan Har block,the landslide-triggering thrust and strike-slip events both follow the distributions of the hanging wall.
基金supported by the Humanities and Social Sciences Project of the Ministry of Education of the Peoples Republic(No.21YJCZH099)the National Natural Science Foundation of China(Nos.41401089 and 41741014)the Science and Technology Project of Sichuan Province(No.2023NSFSC1979).
文摘Majority of carbon emissions originate from fossil energy consumption,thus necessitating calculation and monitoring of carbon emissions from energy consumption.In this study,we utilized energy consumption data from Sichuan Province and Chongqing Municipality for the years 2000 to 2019 to estimate their statistical carbon emissions.We then employed nighttime light data to downscale and infer the spatial distribution of carbon emissions at the county level within the Chengdu-Chongqing urban agglomeration.Furthermore,we analyzed the spatial pattern of carbon emissions at the county level using the coefficient of variation and spatial autocorrelation,and we used the Geographically and Temporally Weighted Regression(GTWR)model to analyze the influencing factors of carbon emissions at this scale.The results of this study are as follows:(1)from 2000 to 2019,the overall carbon emissions in the Chengdu-Chongqing urban agglomeration showed an increasing trend followed by a decrease,with an average annual growth rate of 4.24%.However,in recent years,it has stabilized,and 2012 was the peak year for carbon emissions in the Chengdu-Chongqing urban agglomeration;(2)carbon emissions exhibited significant spatial clustering,with high-high clustering observed in the core urban areas of Chengdu and Chongqing and low-low clustering in the southern counties of the Chengdu-Chongqing urban agglomeration;(3)factors such as GDP,population(Pop),urbanization rate(Ur),and industrialization structure(Ic)all showed a significant influence on carbon emissions;(4)the spatial heterogeneity of each influencing factor was evident.
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 Open Fund of the Laboratory for Earth Surface Processes,Ministry of Education,Peking University,Beijing,China,and the Cultivation Fund Program for Excellent Dissertation in Fujian Normal University,China(No.LWPYS202315)the Research Start-up Fund of Fujian Normal University,China(No.Y0720304X13).
文摘Fifty agricultural soil samples collected from Fuzhou,southeast China,were first investigated for the occurrence,distribution,and potential risks of twelve organophosphate esters(OPEs).The total concentration of OPEs(ΣOPEs)in soil ranged from 1.33 to 96.5 ng/g dry weight(dw),with an average value of 17.1 ng/g dw.Especially,halogenated-OPEs were the predominant group with amean level of 9.75 ng/g dw,and tris(1-chloro-2-propyl)phosphate(TCIPP)was the most abundant OPEs,accounting for 51.1%ofΣOPEs.The concentrations of TCIPP andΣOPEs were found to be significantly higher(P<0.05)in soils of urban areas than those in suburban areas.In addition,the use of agricultural plastic films and total organic carbon had a positive effect on the occurrence of OPE in this study.The positive matrix factorization model suggested complex sources of OPEs in agricultural soils from Fuzhou.The ecological risk assessment demonstrated that tricresyl phosphate presented a medium risk to land-based organisms(0.1≤risk quotient<1.0).Nevertheless,the carcinogenic and noncarcinogenic risks for human exposure to OPEs through soil ingestion and dermal absorption were negligible.These findings would facilitate further investigations into the pollution management and risk control of OPEs.
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.
基金supported by the National Natural Science Foundation of China(No.12235006)the National Key Research and Development Program of China(No.2020YFE0202002.
文摘X-ray detectors show potential applications in medical imaging,materials science,and nuclear energy.To achieve high detection efficiency and spatial resolution,many conventional semiconductor materials,such as amorphous selenium,cadmium telluride zinc,and perovskites,have been utilized in direct conversion X-ray detectors.However,these semiconductor materials are susceptible to temperature-induced performance degradation,crystallization,delamination,uneven lattice growth,radiation damage,and high dark current.This study explores a new approach by coupling an FC40 electronic fluorinated liquid with a specialized high-resolution and high-readout-speed complementary metal-oxide-semiconductor(CMOS)pixel array,specifically the Topmetal II−chip,to fabricate a direct conversion X-ray detector.The fluorinated liquid FC40(molecular formula:C_(21)F_(48)N_(2))is an electronic medium that is minimally affected by temperature and displays no issues with uniform conductivity.It exhibits a low dark current and minimal radiation damage and enables customizable thickness in X-ray absorption.This addresses the limitations inherent in conventional semiconductor-based detectors.In this study,simple X-ray detector imaging tests were conducted,demonstrating the excellent coupling capability between FC40 electronic fluorinated liquid and CMOS chips by the X-ray detector.A spatial resolution of 4.0 lp/mm was measured using a striped line par card,and a relatively clear image of a cockroach was displayed in the digital radiography imaging results.Preliminary test results indicated the feasibility of fabricating an X-ray detector by combining FC40 electronic fluorinated liquid and CMOS chips.Owing to the absence of issues related to chip-material coupling,a high spatial resolution could be achieved by reducing the chip pixel size.This method presents a new avenue for studies on novel liquid-based direct conversion X-ray detectors.
基金The National Natural Science Foundation of China(No.U19B2031).
文摘A new method based on the iterative adaptive algorithm(IAA)and blocking matrix preprocessing(BMP)is proposed to study the suppression of multi-mainlobe interference.The algorithm is applied to precisely estimate the spatial spectrum and the directions of arrival(DOA)of interferences to overcome the drawbacks associated with conventional adaptive beamforming(ABF)methods.The mainlobe interferences are identified by calculating the correlation coefficients between direction steering vectors(SVs)and rejected by the BMP pretreatment.Then,IAA is subsequently employed to reconstruct a sidelobe interference-plus-noise covariance matrix for the preferable ABF and residual interference suppression.Simulation results demonstrate the excellence of the proposed method over normal methods based on BMP and eigen-projection matrix perprocessing(EMP)under both uncorrelated and coherent circumstances.
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Project supported by the National Key Research and Development Program of China(Grant No.2023YFA1407000)the Strategic Priority Research Program of Chinese Academy of Sciences(Grant No.XDB0460000)+4 种基金the National Natural Science Foundation of China(Grant Nos.12322401,12127807,and 12393832)CAS Key Research Program of Frontier Sciences(Grant No.ZDBS-LY-SLH004)Beijing Nova Program(Grant No.20230484301)Youth Innovation Promotion Association,Chinese Academy of Sciences(Grant No.2023125)CAS Project for Young Scientists in Basic Research(Grant No.YSBR-026)。
文摘Edge structures are ubiquitous in the processing and fabrication of various optoelectronic devices.Novel physical properties and enhanced light–matter interactions are anticipated to occur at crystal edges due to the broken spatial translational symmetry.However,the intensity of first-order Raman scattering at crystal edges has been rarely explored,although the mechanical stress and edge characteristics have been thoroughly studied by the Raman peak shift and the spectral features of the edge-related Raman modes.Here,by taking Ga As crystal with a well-defined edge as an example,we reveal the intensity enhancement of Raman-active modes and the emergence of Raman-forbidden modes under specific polarization configurations at the edge.This is attributed to the presence of a hot spot at the edge due to the redistributed electromagnetic fields and electromagnetic wave propagations of incident laser and Raman signal near the edge,which are confirmed by the finite-difference time-domain simulations.Spatially-resolved Raman intensities of both Raman-active and Raman-forbidden modes near the edge are calculated based on the redistributed electromagnetic fields,which quantitatively reproduce the corresponding experimental results.These findings offer new insights into the intensity enhancement of Raman scattering at crystal edges and present a new avenue to manipulate light–matter interactions of crystal by manufacturing various types of edges and to characterize the edge structures in photonic and optoelectronic devices.
文摘Secondary injury following spinal cord injury is primarily characterized by a complex inflammatory response,with resident microglia and infiltrating macrophages playing pivotal roles.While previous studies have grouped these two cell types together based on similarities in structure and function,an increasing number of studies have demonstrated that microglia and macrophages exhibit differences in structure and function and have different effects on disease processes.In this study,we used single-cell RNA sequencing and spatial transcriptomics to identify the distinct evolutionary paths of microglia and macrophages following spinal cord injury.Our results showed that microglia were activated to a pro-inflammatory phenotype immediately after spinal cord injury,gradually transforming to an anti-inflammatory steady state phenotype as the disease progressed.Regarding macrophages,our findings highlighted abundant communication with other cells,including fibroblasts and neurons.Both pro-inflammatory and neuroprotective effects of macrophages were also identified;the pro-inflammatory effect may be related to integrin β2(Itgb2) and the neuroprotective effect may be related to the oncostatin M pathway.These findings were validated by in vivo experiments.This research underscores differences in the cellular dynamics of microglia and macrophages following spinal cord injury,and may offer new perspectives on inflammatory mechanisms and potential therapeutic targets.
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.
基金the National Natural Science Foundation of China(Grant No.62172132)Public Welfare Technology Research Project of Zhejiang Province(Grant No.LGF21F020014)the Opening Project of Key Laboratory of Public Security Information Application Based on Big-Data Architecture,Ministry of Public Security of Zhejiang Police College(Grant No.2021DSJSYS002).
文摘Seal authentication is an important task for verifying the authenticity of stamped seals used in various domains to protect legal documents from tampering and counterfeiting.Stamped seal inspection is commonly audited manually to ensure document authenticity.However,manual assessment of seal images is tedious and laborintensive due to human errors,inconsistent placement,and completeness of the seal.Traditional image recognition systems are inadequate enough to identify seal types accurately,necessitating a neural network-based method for seal image recognition.However,neural network-based classification algorithms,such as Residual Networks(ResNet)andVisualGeometryGroup with 16 layers(VGG16)yield suboptimal recognition rates on stamp datasets.Additionally,the fixed training data categories make handling new categories to be a challenging task.This paper proposes amulti-stage seal recognition algorithmbased on Siamese network to overcome these limitations.Firstly,the seal image is pre-processed by applying an image rotation correction module based on Histogram of Oriented Gradients(HOG).Secondly,the similarity between input seal image pairs is measured by utilizing a similarity comparison module based on the Siamese network.Finally,we compare the results with the pre-stored standard seal template images in the database to obtain the seal type.To evaluate the performance of the proposed method,we further create a new seal image dataset that contains two subsets with 210,000 valid labeled pairs in total.The proposed work has a practical significance in industries where automatic seal authentication is essential as in legal,financial,and governmental sectors,where automatic seal recognition can enhance document security and streamline validation processes.Furthermore,the experimental results show that the proposed multi-stage method for seal image recognition outperforms state-of-the-art methods on the two established datasets.
