The accessibility of urban public transit directly influences residents’quality of life,travel behavior,and social equity.Its correlation with housing prices has garnered significant attention across disciplines such...The accessibility of urban public transit directly influences residents’quality of life,travel behavior,and social equity.Its correlation with housing prices has garnered significant attention across disciplines such as geography,economics,and urban planning.Although much existing research focuses on the impact of individual transportation facilities on housing prices,there is a notable gap in comprehensive analyses that assess the influence of overall urban transit accessibility on housing market dynamics.This study selected the main urban area of Hefei,China,as a case to investigate the spatial distribution of housing prices and evaluate public transit accessibility in 2022.Employing techniques such as the optimized parameter geographical detector and local spatial regression models,the study aimed to elucidate the effects and underlying mechanisms of urban transit accessibility on housing prices.The findings revealed that:1)housing prices in Hefei exhibited a clustered spatial pattern,with high prices concentrated in the city center and lower prices in peripheral areas,forming three distinct high-price hotspots with a‘belt-like’distribution;2)public transit accessibility showed a‘coreperiphery’structure,with accessibility declining in a‘circumferential’pattern around the city center.Based on the‘housing price-accessibility’dimension,four categories were identified:high price-high accessibility(37.25%),high price-low accessibility(19.07%),low price-high accessibility(21.95%),and low price-low accessibility(21.73%);3)the impact of transit accessibility on housing prices was spatially heterogeneous,with bus travel showing the strongest explanatory power(0.692),followed by automobile,subway,and bicycle travel.The interaction of these transportation modes generated a synergistic effect on housing price differentiation,with most influencing factors contributing more than 25%.These findings offer valuable insights for optimizing the spatial distribution of public transit infrastructure and improving both urban housing quality and residents’living standards.展开更多
随着分子生物学技术蓬勃发展,越来越多的肿瘤学者通过The Cancer Genome Atlas(TCGA)数据库下载高通量测序数据,运用生物信息学分析的方法,识别肿瘤免疫微环境中各种细胞的表达量,进行肿瘤浸润性免疫细胞的分析工作,但是肿瘤与免疫的相...随着分子生物学技术蓬勃发展,越来越多的肿瘤学者通过The Cancer Genome Atlas(TCGA)数据库下载高通量测序数据,运用生物信息学分析的方法,识别肿瘤免疫微环境中各种细胞的表达量,进行肿瘤浸润性免疫细胞的分析工作,但是肿瘤与免疫的相互作用往往十分复杂,临床工作人员面对庞大数据量展开分析工作仍然充满困难,基于此本文介绍一款全面分析肿瘤浸润性免疫细胞及其可视化的数据库TIMER2.0,旨在为临床研究人员轻松识别多种癌症类型与正常组织及免疫细胞浸润之间的基因组学关系,快速运用多种算法掌握肿瘤概况。展开更多
基金Under the auspices of the National Natural Science Foundation of China(No.42271224,41901193)Ministry of Edu cation Humanities and Social Sciences Research Planning Fund Project of China(No.24YJAZH190)+1 种基金Anhui Province Excellent Youth Research Project in Universities(No.2022AH030019)Anhui Social Sciences Innovation Development Research Project(No.2024CXQ503)。
文摘The accessibility of urban public transit directly influences residents’quality of life,travel behavior,and social equity.Its correlation with housing prices has garnered significant attention across disciplines such as geography,economics,and urban planning.Although much existing research focuses on the impact of individual transportation facilities on housing prices,there is a notable gap in comprehensive analyses that assess the influence of overall urban transit accessibility on housing market dynamics.This study selected the main urban area of Hefei,China,as a case to investigate the spatial distribution of housing prices and evaluate public transit accessibility in 2022.Employing techniques such as the optimized parameter geographical detector and local spatial regression models,the study aimed to elucidate the effects and underlying mechanisms of urban transit accessibility on housing prices.The findings revealed that:1)housing prices in Hefei exhibited a clustered spatial pattern,with high prices concentrated in the city center and lower prices in peripheral areas,forming three distinct high-price hotspots with a‘belt-like’distribution;2)public transit accessibility showed a‘coreperiphery’structure,with accessibility declining in a‘circumferential’pattern around the city center.Based on the‘housing price-accessibility’dimension,four categories were identified:high price-high accessibility(37.25%),high price-low accessibility(19.07%),low price-high accessibility(21.95%),and low price-low accessibility(21.73%);3)the impact of transit accessibility on housing prices was spatially heterogeneous,with bus travel showing the strongest explanatory power(0.692),followed by automobile,subway,and bicycle travel.The interaction of these transportation modes generated a synergistic effect on housing price differentiation,with most influencing factors contributing more than 25%.These findings offer valuable insights for optimizing the spatial distribution of public transit infrastructure and improving both urban housing quality and residents’living standards.
文摘随着分子生物学技术蓬勃发展,越来越多的肿瘤学者通过The Cancer Genome Atlas(TCGA)数据库下载高通量测序数据,运用生物信息学分析的方法,识别肿瘤免疫微环境中各种细胞的表达量,进行肿瘤浸润性免疫细胞的分析工作,但是肿瘤与免疫的相互作用往往十分复杂,临床工作人员面对庞大数据量展开分析工作仍然充满困难,基于此本文介绍一款全面分析肿瘤浸润性免疫细胞及其可视化的数据库TIMER2.0,旨在为临床研究人员轻松识别多种癌症类型与正常组织及免疫细胞浸润之间的基因组学关系,快速运用多种算法掌握肿瘤概况。
