In this paper we propose a service-oriented architecture for spatial data integration (SOA-SDI) in the context of a large number of available spatial data sources that are physically sitting at different places, and d...In this paper we propose a service-oriented architecture for spatial data integration (SOA-SDI) in the context of a large number of available spatial data sources that are physically sitting at different places, and develop web-based GIS systems based on SOA-SDI, allowing client applications to pull in, analyze and present spatial data from those available spatial data sources. The proposed architecture logically includes 4 layers or components; they are layer of multiple data provider services, layer of data in-tegration, layer of backend services, and front-end graphical user interface (GUI) for spatial data presentation. On the basis of the 4-layered SOA-SDI framework, WebGIS applications can be quickly deployed, which proves that SOA-SDI has the potential to reduce the input of software development and shorten the development period.展开更多
This paper presents an procedure for purifying training data sets （i.e., past occurrences of slope failures） for inverse estimation on unobserved trigger factors of ＂different types of simultaneous slope failures＂...This paper presents an procedure for purifying training data sets （i.e., past occurrences of slope failures） for inverse estimation on unobserved trigger factors of ＂different types of simultaneous slope failures＂. Due to difficulties in pixel-by-pixel observations of trigger factors, as one of the measures, the authors had proposed an inverse analysis algorithm on trigger factors based on SEM （structural equation modeling）. Through a measurement equation, the trigger factor is inversely estimated, and a TFI （trigger factor influence） map can be also produced. As a subsequence subject, a purification procedure of training data set should be constructed to improve the accuracy of TFI map which depends on the representativeness of given training data sets of different types of slope failures. The proposed procedure resamples the matched pixels between original groups of past slope failures （i.e., surface slope failures, deep-seated slope failures, landslides） and classified three groups by K-means clustering for all pixels corresponding to those slope failures. For all cases of three types of slope failures, the improvement of success rates with respect to resampled training data sets was confirmed. As a final outcome, the differences between TFI maps produced by using original and resampled training data sets, respectively, are delineated on a DIF map （difference map） which is useful for analyzing trigger factor influence in terms of ＂risky- and safe-side assessment＂ sub-areas with respect to ＂different types of simultaneous slope failures＂.展开更多
Spatial online analytical processing(OLAP)and spatial data warehouse(SDW)systems are geo-business intelligence technologies that enable the analysis of huge volumes of geographic data.In the last decade,the conceptual...Spatial online analytical processing(OLAP)and spatial data warehouse(SDW)systems are geo-business intelligence technologies that enable the analysis of huge volumes of geographic data.In the last decade,the conceptual design and implementation of SDWs that integrate spatial data,which are represented using the vector model,have been extensively investigated.However,the integration of field data(a continuous representation of spatial data)in SDWs is a recent unresolved research issue.Enhancing SDWs with field data improves the spatio-multidimensional analysis capabilities with continuity and multiresolutions.Motivated by the need for a conceptual design tool and relational online analytical processing(ROLAP)implementation,we propose a UML profile for SDWs that integrates a regular grid of points and supports continuity and multiresolutions.We also propose an efficient implementation of a ROLAP architecture.展开更多
This paper presents a comparative visualization strategy of slope failure susceptibility maps for analyzing different types of simultaneous occurrences of slope failures. Through the SEM （structural equation modeling...This paper presents a comparative visualization strategy of slope failure susceptibility maps for analyzing different types of simultaneous occurrences of slope failures. Through the SEM （structural equation modeling）, slope failure susceptibility maps are produced by using causal factors （i.e., geographical information, satellite remotely sensed data）. As for a conventional pair-wise comparative procedure, the differences between susceptibility maps are delineated on difference maps, that can be, however, applied for evaluating differences only between pairs of susceptibility maps. One of the strong requirements from specialists working on slope stability evaluation is a comparative and visualization strategy of susceptibility maps with respect to ＂different types of simultaneous slope failures＂, for which the discussion is insufficient in the previous research activities for constructing the quantitative models for slope failure hazard mapping. As a measure, a color composite map based on susceptibility maps has been produced. The combination of assigning susceptibility maps to RGB-color planes is determined based on an index of ＂NCCT （normalized correlated color temperature）＂ which represents the relationship between chromaticity and human visual perception. Through the cases examined, the result indicates that the proposed color composite map, as a heuristic visualization strategy, is useful for simultaneously evaluating the hazardous areas affected by ＂different types of slope failures＂.展开更多
Understanding the cellular origins and early evolutionary dynamics that drive the initiation of carcinogenesis is critical to advancing early detection and prevention strategies.By characterizing key molecular,cellula...Understanding the cellular origins and early evolutionary dynamics that drive the initiation of carcinogenesis is critical to advancing early detection and prevention strategies.By characterizing key molecular,cellular and niche events at the precancerous tipping point of early gastric cancer(EGC),we aimed to develop more precise screening tools and design targeted interventions to prevent malignant transformation at this stage.We utilized our AI models to integrate spatial multimodal data from nine EGC endoscopic submucosal dissection(ESD)samples(covering sequential stages from normal to cancer),construct a spatial-temporal profile of disease progression,and identify a critical tipping point(PMC_P)characterized by an immune-suppressive microenvironment during early cancer development.At this stage,inflammatory pit mucous cells with stemness(PMC_2)interact with fibroblasts via NAMPT→ITGA5/ITGB1 and with macrophages via AREG→EGFR/ERBB2 signaling,fostering cancer initiation.We established gastric precancerous cell lines and organoids to demonstrate that NAMPT and AREG promote cellular proliferation in vitro.Furthermore,in the transgenic CEA-SV40 mouse model,targeting AREG and/or NAMPT disrupted key cell interactions,inhibited the JAK-STAT,MAPK,and NFκB pathways,and reduced PD-L1 expression,which was also confirmed by western blot in vitro.These interventions delayed disease progression,reversed the immunosuppressive microenvironment,and prevented malignant transformation.Clinical validation was conducted using endoscopically resected EGC specimens.Our study provides a precise spatiotemporal depiction of EGC development and identifies novel diagnostic markers and therapeutic targets for early intervention.展开更多
基金Supported by the Research Fund of Key GIS Lab of the Education Ministry (No. 200610)
文摘In this paper we propose a service-oriented architecture for spatial data integration (SOA-SDI) in the context of a large number of available spatial data sources that are physically sitting at different places, and develop web-based GIS systems based on SOA-SDI, allowing client applications to pull in, analyze and present spatial data from those available spatial data sources. The proposed architecture logically includes 4 layers or components; they are layer of multiple data provider services, layer of data in-tegration, layer of backend services, and front-end graphical user interface (GUI) for spatial data presentation. On the basis of the 4-layered SOA-SDI framework, WebGIS applications can be quickly deployed, which proves that SOA-SDI has the potential to reduce the input of software development and shorten the development period.
文摘This paper presents an procedure for purifying training data sets （i.e., past occurrences of slope failures） for inverse estimation on unobserved trigger factors of ＂different types of simultaneous slope failures＂. Due to difficulties in pixel-by-pixel observations of trigger factors, as one of the measures, the authors had proposed an inverse analysis algorithm on trigger factors based on SEM （structural equation modeling）. Through a measurement equation, the trigger factor is inversely estimated, and a TFI （trigger factor influence） map can be also produced. As a subsequence subject, a purification procedure of training data set should be constructed to improve the accuracy of TFI map which depends on the representativeness of given training data sets of different types of slope failures. The proposed procedure resamples the matched pixels between original groups of past slope failures （i.e., surface slope failures, deep-seated slope failures, landslides） and classified three groups by K-means clustering for all pixels corresponding to those slope failures. For all cases of three types of slope failures, the improvement of success rates with respect to resampled training data sets was confirmed. As a final outcome, the differences between TFI maps produced by using original and resampled training data sets, respectively, are delineated on a DIF map （difference map） which is useful for analyzing trigger factor influence in terms of ＂risky- and safe-side assessment＂ sub-areas with respect to ＂different types of simultaneous slope failures＂.
文摘Spatial online analytical processing(OLAP)and spatial data warehouse(SDW)systems are geo-business intelligence technologies that enable the analysis of huge volumes of geographic data.In the last decade,the conceptual design and implementation of SDWs that integrate spatial data,which are represented using the vector model,have been extensively investigated.However,the integration of field data(a continuous representation of spatial data)in SDWs is a recent unresolved research issue.Enhancing SDWs with field data improves the spatio-multidimensional analysis capabilities with continuity and multiresolutions.Motivated by the need for a conceptual design tool and relational online analytical processing(ROLAP)implementation,we propose a UML profile for SDWs that integrates a regular grid of points and supports continuity and multiresolutions.We also propose an efficient implementation of a ROLAP architecture.
文摘This paper presents a comparative visualization strategy of slope failure susceptibility maps for analyzing different types of simultaneous occurrences of slope failures. Through the SEM （structural equation modeling）, slope failure susceptibility maps are produced by using causal factors （i.e., geographical information, satellite remotely sensed data）. As for a conventional pair-wise comparative procedure, the differences between susceptibility maps are delineated on difference maps, that can be, however, applied for evaluating differences only between pairs of susceptibility maps. One of the strong requirements from specialists working on slope stability evaluation is a comparative and visualization strategy of susceptibility maps with respect to ＂different types of simultaneous slope failures＂, for which the discussion is insufficient in the previous research activities for constructing the quantitative models for slope failure hazard mapping. As a measure, a color composite map based on susceptibility maps has been produced. The combination of assigning susceptibility maps to RGB-color planes is determined based on an index of ＂NCCT （normalized correlated color temperature）＂ which represents the relationship between chromaticity and human visual perception. Through the cases examined, the result indicates that the proposed color composite map, as a heuristic visualization strategy, is useful for simultaneously evaluating the hazardous areas affected by ＂different types of slope failures＂.
基金supported by Shanghai Oriental Talent Youth Program(QNKJ2024006)National Natural Science Foundation of China(82170555,32300523,32570769,and 62132015)+1 种基金Shanghai Academic/Technology Research Leader(22XD1422400)Shuguang Program of Shanghai Education Development Foundation and Shanghai Municipal Education Commission(22SG06).
文摘Understanding the cellular origins and early evolutionary dynamics that drive the initiation of carcinogenesis is critical to advancing early detection and prevention strategies.By characterizing key molecular,cellular and niche events at the precancerous tipping point of early gastric cancer(EGC),we aimed to develop more precise screening tools and design targeted interventions to prevent malignant transformation at this stage.We utilized our AI models to integrate spatial multimodal data from nine EGC endoscopic submucosal dissection(ESD)samples(covering sequential stages from normal to cancer),construct a spatial-temporal profile of disease progression,and identify a critical tipping point(PMC_P)characterized by an immune-suppressive microenvironment during early cancer development.At this stage,inflammatory pit mucous cells with stemness(PMC_2)interact with fibroblasts via NAMPT→ITGA5/ITGB1 and with macrophages via AREG→EGFR/ERBB2 signaling,fostering cancer initiation.We established gastric precancerous cell lines and organoids to demonstrate that NAMPT and AREG promote cellular proliferation in vitro.Furthermore,in the transgenic CEA-SV40 mouse model,targeting AREG and/or NAMPT disrupted key cell interactions,inhibited the JAK-STAT,MAPK,and NFκB pathways,and reduced PD-L1 expression,which was also confirmed by western blot in vitro.These interventions delayed disease progression,reversed the immunosuppressive microenvironment,and prevented malignant transformation.Clinical validation was conducted using endoscopically resected EGC specimens.Our study provides a precise spatiotemporal depiction of EGC development and identifies novel diagnostic markers and therapeutic targets for early intervention.
