The spatial consciousness of the ancients is reflected in the character formation,structure,and writing of the oracle bones.Piaget‟s genetic epistemology,Merleau-Ponty‟s philosophy of body,and cognitive linguistics su...The spatial consciousness of the ancients is reflected in the character formation,structure,and writing of the oracle bones.Piaget‟s genetic epistemology,Merleau-Ponty‟s philosophy of body,and cognitive linguistics suggest that human spatial awareness is derived from the formation of a spatial awareness of the body,and evidence for this can be found in the body-related characters in the oracle bones.As a combination of symbols and images,the oracle bones are themselves a spatial metaphor that can compensate for the lack of symbolic language and serve as a reference for the aesthetic language advocated by Adorno.展开更多
Mandarin在(pinyin:zài)is the most frequently used character in representing spatial and temporal relationship.Current studies mostly focus on its lexical meaning and syntactic structure while cognitive features o...Mandarin在(pinyin:zài)is the most frequently used character in representing spatial and temporal relationship.Current studies mostly focus on its lexical meaning and syntactic structure while cognitive features of its grammatical categories have been neglected.This paper investigates into the categorization of zài by conducting a morphosyntactic test among College English majors in China.The results show that:prototypes are organizing the grammatical categories of zài at all levels in terms of intra-categorial gradience;the semantic construal of zài construction could significantly influence the accuracy of the grammatical categorization of zài;the syntactic structure can provide viable cue for the identification of grammatical categories of zài;spatiality,temporality and the status of existing are three essential semantic features encoded by zài,the concurrence of which leads to various degree of inter-categorial vagueness,indicating a conflict between the rigid grammatical classification and the indeterminate nature of the grammatical functions of zai,suggesting the necessity to reconsider the efficacy of applying indiscriminately the Anglo-Saxon grammar into the study of Chinese spatial-temporal constructions.展开更多
In this paper I explore the conception of cognition and action found in the Inner Chapters of the Zhuangzi. More specifically, I focus on the role of explicit and implicit spatial imagery in the context of this comple...In this paper I explore the conception of cognition and action found in the Inner Chapters of the Zhuangzi. More specifically, I focus on the role of explicit and implicit spatial imagery in the context of this complex problem. Spatial imagery suggests that cognition is understood as fundamentally bimodal in the text： （1） the default modality, which is informed by an entrenched distinction pattern, is cast in terms of fullness and bulk; and （2） the auxiliary modality, which is free from this kind of constraint, is imagined in terms of emptiness and lack of bulk, as an axis or point. The latter is the preferred mode of engagement with the environment, according to the Zhuangzi. Spatial imagery brings out the crucial characteristics of this cognitive modality： its radical openness and infinite fecundity in the context of distinction-drawing and action. It also connects with other metaphorical schemata at work in the text, including organic imagery. Interestingly, the notion of emptiness and the figure of an axis do not mark an experience of undifferentiated oneness but the state of heightened sensitivity to the makeup of one＇s environment. Such sensitivity allows the agent to entertain the situation at hand without bias and to move around （relatively） conflict-free.展开更多
Alzheimer’s disease(AD)is the most common form of dementia.In addition to the lack of effective treatments,there are limitations in diagnostic capabilities.The complexity of AD itself,together with a variety of other...Alzheimer’s disease(AD)is the most common form of dementia.In addition to the lack of effective treatments,there are limitations in diagnostic capabilities.The complexity of AD itself,together with a variety of other diseases often observed in a patient’s history in addition to their AD diagnosis,make deciphering the molecular mechanisms that underlie AD,even more important.Large datasets of single-cell RNA sequencing,single-nucleus RNA-sequencing(snRNA-seq),and spatial transcriptomics(ST)have become essential in guiding and supporting new investigations into the cellular and regional susceptibility of AD.However,with unique technology,software,and larger databases emerging;a lack of integration of these data can contribute to ineffective use of valuable knowledge.Importantly,there was no specialized database that concentrates on ST in AD that offers comprehensive differential analyses under various conditions,such as sex-specific,region-specific,and comparisons between AD and control groups until the new Single-cell and Spatial RNA-seq databasE for Alzheimer’s Disease(ssREAD)database(Wang et al.,2024)was introduced to meet the scientific community’s growing demand for comprehensive,integrated,and accessible data analysis.展开更多
The article examines the existing infrastructure of open common spaces within two New Belgrade mass housing blocks(Blocks 23 and 70a)through a typo-morphological analysis.These spaces between the buildings,although th...The article examines the existing infrastructure of open common spaces within two New Belgrade mass housing blocks(Blocks 23 and 70a)through a typo-morphological analysis.These spaces between the buildings,although the most neglected,underused,and deteriorated components of mass housing neighbourhoods,are at the same time crucial to the quality,vitality and integrated governance of these neighbourhoods.They represent the primary tangible commons in cities and neighbourhoods.The question of urban commons is increasingly present in scientific literature,urban and architectural discourse.Nevertheless,approaches exploring the spatiality of the urban commons are scarce,leading to insufficient understanding of the spatial aspect and potentials of the already existing commons.Therefore,this study includes(1)identification,typological decoding and classification of the common spaces,focusing on the case of New Belgrade blocks,followed by(2)analysis of the spatial patterns and integration of the identified spaces within the blocks.The study confirms the complexity and diverse typology of the common spaces.It finds that the in-between,common spaces contribute to higher integration of different segments of the blocks.The open common spaces have an essential role in humanisation of the blocks,and thus the quality of life in the blocks as integrated neighbourhoods.The findings indicate that the spatial setting of the open common spaces in New Belgrade blocks allows for(re)emergence of collective practices,leading to inclusive and integrated rehabilitation of the neighbourhoods.展开更多
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
Cities are important carriers of green innovation.The foundation for accelerating China's ecological civilization construction and fostering regionally coordinated and sustainable development is quantitative analy...Cities are important carriers of green innovation.The foundation for accelerating China's ecological civilization construction and fostering regionally coordinated and sustainable development is quantitative analysis of the spatial evolution pattern and influencing factors of urban green innovation,as well as revealing the development differences between regions.This study's research object includes 284 Chinese cities that are at the prefecture level or above,excluding Xizang,Hong Kong,Macao,and Taiwan of China due to incomplete data.The spatial evolution characteristics of urban green innovation in China between 2005 and 2021 are comprehensively described using the gravity center model and boxplot analysis.The factors that affect urban green innovation are examined using the spatial Durbin model(SDM).The findings indicate that:1)over the period of the study,the gravity center of urban green innovation in China has always been distributed in the Henan-Anhui border region,showing a migration characteristic of‘initially shifting northeast,subsequently southeast',and the migration speed has gradually increased.2)Although there are also noticeable disparities in east-west,the north-south gap is the main cause of the shift in China's urban green innovation gravity center.The primary areas of urban green innovation in China are the cities with green innovation levels higher than the median.3)The main influencing factor of urban green innovation is the industrial structure level.The effect of the financial development level,the government intervention level,and the openness to the outside world degree on urban green innovation is weakened in turn.The environmental regulation degree is not truly influencing urban green innovation.The impact of various factors on green innovation across cities of different sizes,exhibiting heterogeneity.This study is conducive to broadening the academic community's comprehension of the spatial evolution characteristics of urban green innovation and offering a theoretical framework for developing policies for the all-encompassing green transformation of social and economic growth.展开更多
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
The word“spatial”fundamentally relates to human existence,evolution,and activity in terrestrial and even celestial spaces.After reviewing the spatial features of many areas,the paper describes basics of high level m...The word“spatial”fundamentally relates to human existence,evolution,and activity in terrestrial and even celestial spaces.After reviewing the spatial features of many areas,the paper describes basics of high level model and technology called Spatial Grasp for dealing with large distributed systems,which can provide spatial vision,awareness,management,control,and even consciousness.The technology description includes its key Spatial Grasp Language(SGL),self-evolution of recursive SGL scenarios,and implementation of SGL interpreter converting distributed networked systems into powerful spatial engines.Examples of typical spatial scenarios in SGL include finding shortest path tree and shortest path between network nodes,collecting proper information throughout the whole world,elimination of multiple targets by intelligent teams of chasers,and withstanding cyber attacks in distributed networked systems.Also this paper compares Spatial Grasp model with traditional algorithms,confirming universality of the former for any spatial systems,while the latter just tools for concrete applications.展开更多
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
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
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
Scientifically understanding the evolution of urbanization and analysing the coupling mechanism of human-land systems are important foundations for solving spatial conflicts and promoting regional sustainable developm...Scientifically understanding the evolution of urbanization and analysing the coupling mechanism of human-land systems are important foundations for solving spatial conflicts and promoting regional sustainable development.This study analyzed the spatiotemporal evolution and landscape pattern change of construction land in the Yangtze River Delta(YRD)region from 1990 to 2018 by integrating Geographical Information System(GIS)spatial analysis and landscape pattern indices,and revealed its driving mechanism by XGBoost and SHapley Additive ex Planations(SHAP).Moreover,we compared the disparities in the core driving factors for construction land evolution in cities with diverse development orientations within the YRD region.Results show that:1)development intensity of construction land continued to increase from 7.54%in 1990 to 13.44%in 2018,primarily by occupying farmland.The landscape fragmentation of construction land in the YRD region decreased,and landscape dominance increased.Spatially,the eastern part of the YRD exhibits a high degree of spatial agglomeration of construction land,whereas the western part shows a high degree of fragmentation,revealing distinct spatial gradient differentiation characteristics.The landscape dominance of the construction land in the eastern region of the YRD is higher than that in the western and northern regions.2)Transportation and infrastructure exert the highest contribution rate on development intensity changes of construction land in the YRD.The industrial structure significantly influences the conversion of farmland to construction land.Additionally,infrastructure plays a crucial role in shaping the spatial agglomeration patterns of construction land.Population distribution is the dominant factor determining the regularity of the landscape shape of construction land.3)The core driving factors for the development intensity of construction land in central cities primarily lies in transportation,whereas for non-central cities,besides transportation,the year-end balance of per capita savings deposits of urban and rural residents also play a significant role.The area change of construction land occupying farmland in central and non-central cities is mainly driven by industrial structure and economic level,respectively.This study informs refined spatial optimization and regional high-quality integrated development.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
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
The Hengduan Mountains,situated on the southeastern edge of the Qinghai-Tibet Plateau,are the longest and widest north-south-oriented mountain range in China,exerting a significant influence on the ecological and geog...The Hengduan Mountains,situated on the southeastern edge of the Qinghai-Tibet Plateau,are the longest and widest north-south-oriented mountain range in China,exerting a significant influence on the ecological and geographical pattern.Understanding the topographic and geomorphological characteristics of the Hengduan Mountains is fundamental and crucial for research in related fields such as ecology,geography,and sustainability.In this study,Digital Elevation Model(DEM)data were utilized to extract and analyze the topography and geomorphology(TG)pattern.TG maps have been developed to quantitatively classify the TG types in the Hengduan Mountains by combining the five factors of elevation,slope,aspect,relief and landform.The spatial distribution and quantitative characteristics of these factors were mapped and investigated using geographic information systems.The results revealed that:(1)The Hengduan Mountains exhibit an elongated north-south distribution,with an average elevation of approximately 3746 m,an average slope of around 25°,and an average relief of about 266 m.(2)The Hengduan Mountains display significant elevation differences,with an overall high elevation,characterized by a trend of lower elevation in the east and higher elevation in the west,as well as irregular orientations of various aspects.(3)The 19 landform types were identified,the landform types of the Hengduan Mountains are primarily composed of low-relief high-mountains(42.0618%),low-relief mid-mountains(22.4624%),and high-elevation hills(20.5839%).The results of the study can provide data and information support for the ecology,environmental protection and sustainable development of the Hengduan Mountains.展开更多
文摘The spatial consciousness of the ancients is reflected in the character formation,structure,and writing of the oracle bones.Piaget‟s genetic epistemology,Merleau-Ponty‟s philosophy of body,and cognitive linguistics suggest that human spatial awareness is derived from the formation of a spatial awareness of the body,and evidence for this can be found in the body-related characters in the oracle bones.As a combination of symbols and images,the oracle bones are themselves a spatial metaphor that can compensate for the lack of symbolic language and serve as a reference for the aesthetic language advocated by Adorno.
文摘Mandarin在(pinyin:zài)is the most frequently used character in representing spatial and temporal relationship.Current studies mostly focus on its lexical meaning and syntactic structure while cognitive features of its grammatical categories have been neglected.This paper investigates into the categorization of zài by conducting a morphosyntactic test among College English majors in China.The results show that:prototypes are organizing the grammatical categories of zài at all levels in terms of intra-categorial gradience;the semantic construal of zài construction could significantly influence the accuracy of the grammatical categorization of zài;the syntactic structure can provide viable cue for the identification of grammatical categories of zài;spatiality,temporality and the status of existing are three essential semantic features encoded by zài,the concurrence of which leads to various degree of inter-categorial vagueness,indicating a conflict between the rigid grammatical classification and the indeterminate nature of the grammatical functions of zai,suggesting the necessity to reconsider the efficacy of applying indiscriminately the Anglo-Saxon grammar into the study of Chinese spatial-temporal constructions.
文摘In this paper I explore the conception of cognition and action found in the Inner Chapters of the Zhuangzi. More specifically, I focus on the role of explicit and implicit spatial imagery in the context of this complex problem. Spatial imagery suggests that cognition is understood as fundamentally bimodal in the text： （1） the default modality, which is informed by an entrenched distinction pattern, is cast in terms of fullness and bulk; and （2） the auxiliary modality, which is free from this kind of constraint, is imagined in terms of emptiness and lack of bulk, as an axis or point. The latter is the preferred mode of engagement with the environment, according to the Zhuangzi. Spatial imagery brings out the crucial characteristics of this cognitive modality： its radical openness and infinite fecundity in the context of distinction-drawing and action. It also connects with other metaphorical schemata at work in the text, including organic imagery. Interestingly, the notion of emptiness and the figure of an axis do not mark an experience of undifferentiated oneness but the state of heightened sensitivity to the makeup of one＇s environment. Such sensitivity allows the agent to entertain the situation at hand without bias and to move around （relatively） conflict-free.
文摘Alzheimer’s disease(AD)is the most common form of dementia.In addition to the lack of effective treatments,there are limitations in diagnostic capabilities.The complexity of AD itself,together with a variety of other diseases often observed in a patient’s history in addition to their AD diagnosis,make deciphering the molecular mechanisms that underlie AD,even more important.Large datasets of single-cell RNA sequencing,single-nucleus RNA-sequencing(snRNA-seq),and spatial transcriptomics(ST)have become essential in guiding and supporting new investigations into the cellular and regional susceptibility of AD.However,with unique technology,software,and larger databases emerging;a lack of integration of these data can contribute to ineffective use of valuable knowledge.Importantly,there was no specialized database that concentrates on ST in AD that offers comprehensive differential analyses under various conditions,such as sex-specific,region-specific,and comparisons between AD and control groups until the new Single-cell and Spatial RNA-seq databasE for Alzheimer’s Disease(ssREAD)database(Wang et al.,2024)was introduced to meet the scientific community’s growing demand for comprehensive,integrated,and accessible data analysis.
基金This article is part of an ongoing PhD research of the first author.The field work and the student workshops were supported by Erasmus+mobilitygrants。
文摘The article examines the existing infrastructure of open common spaces within two New Belgrade mass housing blocks(Blocks 23 and 70a)through a typo-morphological analysis.These spaces between the buildings,although the most neglected,underused,and deteriorated components of mass housing neighbourhoods,are at the same time crucial to the quality,vitality and integrated governance of these neighbourhoods.They represent the primary tangible commons in cities and neighbourhoods.The question of urban commons is increasingly present in scientific literature,urban and architectural discourse.Nevertheless,approaches exploring the spatiality of the urban commons are scarce,leading to insufficient understanding of the spatial aspect and potentials of the already existing commons.Therefore,this study includes(1)identification,typological decoding and classification of the common spaces,focusing on the case of New Belgrade blocks,followed by(2)analysis of the spatial patterns and integration of the identified spaces within the blocks.The study confirms the complexity and diverse typology of the common spaces.It finds that the in-between,common spaces contribute to higher integration of different segments of the blocks.The open common spaces have an essential role in humanisation of the blocks,and thus the quality of life in the blocks as integrated neighbourhoods.The findings indicate that the spatial setting of the open common spaces in New Belgrade blocks allows for(re)emergence of collective practices,leading to inclusive and integrated rehabilitation of the neighbourhoods.
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 National Natural Science Foundation of China(No.42371192)Natural Science Foundation of Hunan Province(No.2023JJ30100)Social Science Foundation of Hunan Province(No.23ZDAJ023,23YBA133)。
文摘Cities are important carriers of green innovation.The foundation for accelerating China's ecological civilization construction and fostering regionally coordinated and sustainable development is quantitative analysis of the spatial evolution pattern and influencing factors of urban green innovation,as well as revealing the development differences between regions.This study's research object includes 284 Chinese cities that are at the prefecture level or above,excluding Xizang,Hong Kong,Macao,and Taiwan of China due to incomplete data.The spatial evolution characteristics of urban green innovation in China between 2005 and 2021 are comprehensively described using the gravity center model and boxplot analysis.The factors that affect urban green innovation are examined using the spatial Durbin model(SDM).The findings indicate that:1)over the period of the study,the gravity center of urban green innovation in China has always been distributed in the Henan-Anhui border region,showing a migration characteristic of‘initially shifting northeast,subsequently southeast',and the migration speed has gradually increased.2)Although there are also noticeable disparities in east-west,the north-south gap is the main cause of the shift in China's urban green innovation gravity center.The primary areas of urban green innovation in China are the cities with green innovation levels higher than the median.3)The main influencing factor of urban green innovation is the industrial structure level.The effect of the financial development level,the government intervention level,and the openness to the outside world degree on urban green innovation is weakened in turn.The environmental regulation degree is not truly influencing urban green innovation.The impact of various factors on green innovation across cities of different sizes,exhibiting heterogeneity.This study is conducive to broadening the academic community's comprehension of the spatial evolution characteristics of urban green innovation and offering a theoretical framework for developing policies for the all-encompassing green transformation of social and economic growth.
基金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.
文摘The word“spatial”fundamentally relates to human existence,evolution,and activity in terrestrial and even celestial spaces.After reviewing the spatial features of many areas,the paper describes basics of high level model and technology called Spatial Grasp for dealing with large distributed systems,which can provide spatial vision,awareness,management,control,and even consciousness.The technology description includes its key Spatial Grasp Language(SGL),self-evolution of recursive SGL scenarios,and implementation of SGL interpreter converting distributed networked systems into powerful spatial engines.Examples of typical spatial scenarios in SGL include finding shortest path tree and shortest path between network nodes,collecting proper information throughout the whole world,elimination of multiple targets by intelligent teams of chasers,and withstanding cyber attacks in distributed networked systems.Also this paper compares Spatial Grasp model with traditional algorithms,confirming universality of the former for any spatial systems,while the latter just tools for concrete applications.
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 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Under the auspices of the National Natural Science Foundation of China(No.42301470,42171389)。
文摘Scientifically understanding the evolution of urbanization and analysing the coupling mechanism of human-land systems are important foundations for solving spatial conflicts and promoting regional sustainable development.This study analyzed the spatiotemporal evolution and landscape pattern change of construction land in the Yangtze River Delta(YRD)region from 1990 to 2018 by integrating Geographical Information System(GIS)spatial analysis and landscape pattern indices,and revealed its driving mechanism by XGBoost and SHapley Additive ex Planations(SHAP).Moreover,we compared the disparities in the core driving factors for construction land evolution in cities with diverse development orientations within the YRD region.Results show that:1)development intensity of construction land continued to increase from 7.54%in 1990 to 13.44%in 2018,primarily by occupying farmland.The landscape fragmentation of construction land in the YRD region decreased,and landscape dominance increased.Spatially,the eastern part of the YRD exhibits a high degree of spatial agglomeration of construction land,whereas the western part shows a high degree of fragmentation,revealing distinct spatial gradient differentiation characteristics.The landscape dominance of the construction land in the eastern region of the YRD is higher than that in the western and northern regions.2)Transportation and infrastructure exert the highest contribution rate on development intensity changes of construction land in the YRD.The industrial structure significantly influences the conversion of farmland to construction land.Additionally,infrastructure plays a crucial role in shaping the spatial agglomeration patterns of construction land.Population distribution is the dominant factor determining the regularity of the landscape shape of construction land.3)The core driving factors for the development intensity of construction land in central cities primarily lies in transportation,whereas for non-central cities,besides transportation,the year-end balance of per capita savings deposits of urban and rural residents also play a significant role.The area change of construction land occupying farmland in central and non-central cities is mainly driven by industrial structure and economic level,respectively.This study informs refined spatial optimization and regional high-quality integrated development.
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 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funded by the Yunnan Provincial Basic Research Joint Special Fund Project(2019FH001(-052))Cangshan Mountain Synthetic Scientific Expeditions Fund.
文摘The Hengduan Mountains,situated on the southeastern edge of the Qinghai-Tibet Plateau,are the longest and widest north-south-oriented mountain range in China,exerting a significant influence on the ecological and geographical pattern.Understanding the topographic and geomorphological characteristics of the Hengduan Mountains is fundamental and crucial for research in related fields such as ecology,geography,and sustainability.In this study,Digital Elevation Model(DEM)data were utilized to extract and analyze the topography and geomorphology(TG)pattern.TG maps have been developed to quantitatively classify the TG types in the Hengduan Mountains by combining the five factors of elevation,slope,aspect,relief and landform.The spatial distribution and quantitative characteristics of these factors were mapped and investigated using geographic information systems.The results revealed that:(1)The Hengduan Mountains exhibit an elongated north-south distribution,with an average elevation of approximately 3746 m,an average slope of around 25°,and an average relief of about 266 m.(2)The Hengduan Mountains display significant elevation differences,with an overall high elevation,characterized by a trend of lower elevation in the east and higher elevation in the west,as well as irregular orientations of various aspects.(3)The 19 landform types were identified,the landform types of the Hengduan Mountains are primarily composed of low-relief high-mountains(42.0618%),low-relief mid-mountains(22.4624%),and high-elevation hills(20.5839%).The results of the study can provide data and information support for the ecology,environmental protection and sustainable development of the Hengduan Mountains.
