As the pivotal green space,urban parks play an important role in urban residents’daily activities.Thy can not only bring people physical health,but also can be more likely to elicit positive sentiment to those who vi...As the pivotal green space,urban parks play an important role in urban residents’daily activities.Thy can not only bring people physical health,but also can be more likely to elicit positive sentiment to those who visit them.Recently,social media big data has provided new data sources for sentiment analysis.However,there was limited researches that explored the connection between urban parks and individual’s sentiments.Therefore,this study firstly employed a pre-trained language model(BERT,Bidirectional Encoder Representations from Transformers)to calculate sentiment scores based on social media data.Secondly,this study analysed the relationship between urban parks and individual’s sentiment from both spatial and temporal perspectives.Finally,by utilizing structural equation model(SEM),we identified 13 factors and analyzed its degree of the influence.The research findings are listed as below:①It confirmed that individuals generally experienced positive sentiment with high sentiment scores in the majority of urban parks;②The urban park type showed an influence on sentiment scores.In this study,higher sentiment scores observed in Eco-parks,comprehensive parks,and historical parks;③The urban parks level showed low impact on sentiment scores.With distinctions observed mainly at level-3 and level-4;④Compared to internal factors in parks,the external infrastructure surround them exerted more significant impact on sentiment scores.For instance,number of bus and subway stations around urban parks led to higher sentiment scores,while scenic spots and restaurants had inverse result.This study provided a novel method to quantify the services of various urban parks,which can be served as inspiration for similar studies in other cities and countries,enhancing their park planning and management strategies.展开更多
城市节律可为观察和理解城市提供一种新的模式,为当代城市问题提供新的研究视角。城市居民出行时空行为呈现明显的节律特征,其一定程度反映出城市运行的复杂性,是城市地理和行为地理研究的重要问题之一。本研究引入城市节律这一概念,关...城市节律可为观察和理解城市提供一种新的模式,为当代城市问题提供新的研究视角。城市居民出行时空行为呈现明显的节律特征,其一定程度反映出城市运行的复杂性,是城市地理和行为地理研究的重要问题之一。本研究引入城市节律这一概念,关注居民非通勤出行时空行为,以交通小区为空间单元,利用手机信令数据和POI(Point of interest)数据,基于模糊C均值(Fuzzy C-Means Clustering,FCM)的时间序列软聚类方法和空间分析有机结合,探索居民非通勤出行活动节律模式;同时利用空间滞后模型揭示了出行节律模式隶属度的影响因素。结果表明:北京居民非通勤出行节律存在7种模式,根据不同模式区域的POI的频数密度和富集指数差异,可以将7种模式描述为:“居住导向型”“商业活动型”“商务导向型”“混合偏居住型”“混合偏商务型”“科教文化型”和“休闲娱乐型”。研究发现,不同模式的平均隶属度差异较大,影响因子也存在较大差异。在北京六环内非通勤出行节律模式混合度高,且不同模式的出行节律周期、功能特征和空间分布存在较大差异。此外,出行节律存在显著的空间依赖,并与城市商业、就业、居住等城市功能结构具有较强的相关性。本研究从时空融合视角对北京居民非通勤出行节律模式进行了深入探索,研究结果有助于进一步提高人群出行节律与城市功能结构关系的科学理解,从而能够为城市规划与建设提供重要的决策支撑。展开更多
目的了解2021年广西壮族自治区北部侗族人群乙型肝炎(乙肝)病毒(Hepatitis B virus,HBV)血清流行率。方法采取单纯随机抽样方法在龙胜县选取1-59岁侗族人群开展问卷调查,采集血标本,采用酶联免疫吸附试验检测乙肝表面抗原(Hepatitis B s...目的了解2021年广西壮族自治区北部侗族人群乙型肝炎(乙肝)病毒(Hepatitis B virus,HBV)血清流行率。方法采取单纯随机抽样方法在龙胜县选取1-59岁侗族人群开展问卷调查,采集血标本,采用酶联免疫吸附试验检测乙肝表面抗原(Hepatitis B surface antigen,HBsAg)、乙肝表面抗体(Hepatitis B surface antibody,HBsAb)、乙肝核心抗体(Hepatitis B core antibody,HBcAb)、乙肝e抗原(Hepatitis B e antigen,HBeAg)和乙肝e抗体(Hepatitis B e antibody,HBeAb),分析血清标志物流行率。结果在1261名调查对象中,HBsAg、HBsAb、HBcAb、HBeAg、HBeAb阳性率分别为6.11%、48.45%、15.86%、0.71%、15.31%。1-4岁、5-14岁、15-29岁、30-59岁人群HBsAg阳性率为分别为0.00%、0.00%、7.36%、7.99%(趋势χ^(2)=109.38,P<0.001);有、无、不详乙肝疫苗(Hepatitis B vaccine,HepB)免疫史人群HBsAg阳性率分别为0.31%、7.87%、8.18%(χ^(2)=25.14,P<0.001)。结论广西北部2021年1-59岁侗族人群HBV血清流行率总体处于中度水平,实施HepB免疫规划对控制儿童HBV感染取得显著效果。应继续做好新生儿HepB常规免疫,探索成人HepB免疫策略。展开更多
基金R&D Program of Beijing Municipal Education Commission(No.KM202211417015)Academic Research Projects of Beijing Union University(No.ZK10202209)+1 种基金The team-building subsidy of“Xuezhi Professorship”of the College of Applied Arts and Science of Beijing Union University(No.BUUCAS-XZJSTD-2024005)Academic Research Projects of Beijing Union University(No.ZKZD202305).
文摘As the pivotal green space,urban parks play an important role in urban residents’daily activities.Thy can not only bring people physical health,but also can be more likely to elicit positive sentiment to those who visit them.Recently,social media big data has provided new data sources for sentiment analysis.However,there was limited researches that explored the connection between urban parks and individual’s sentiments.Therefore,this study firstly employed a pre-trained language model(BERT,Bidirectional Encoder Representations from Transformers)to calculate sentiment scores based on social media data.Secondly,this study analysed the relationship between urban parks and individual’s sentiment from both spatial and temporal perspectives.Finally,by utilizing structural equation model(SEM),we identified 13 factors and analyzed its degree of the influence.The research findings are listed as below:①It confirmed that individuals generally experienced positive sentiment with high sentiment scores in the majority of urban parks;②The urban park type showed an influence on sentiment scores.In this study,higher sentiment scores observed in Eco-parks,comprehensive parks,and historical parks;③The urban parks level showed low impact on sentiment scores.With distinctions observed mainly at level-3 and level-4;④Compared to internal factors in parks,the external infrastructure surround them exerted more significant impact on sentiment scores.For instance,number of bus and subway stations around urban parks led to higher sentiment scores,while scenic spots and restaurants had inverse result.This study provided a novel method to quantify the services of various urban parks,which can be served as inspiration for similar studies in other cities and countries,enhancing their park planning and management strategies.
文摘城市节律可为观察和理解城市提供一种新的模式,为当代城市问题提供新的研究视角。城市居民出行时空行为呈现明显的节律特征,其一定程度反映出城市运行的复杂性,是城市地理和行为地理研究的重要问题之一。本研究引入城市节律这一概念,关注居民非通勤出行时空行为,以交通小区为空间单元,利用手机信令数据和POI(Point of interest)数据,基于模糊C均值(Fuzzy C-Means Clustering,FCM)的时间序列软聚类方法和空间分析有机结合,探索居民非通勤出行活动节律模式;同时利用空间滞后模型揭示了出行节律模式隶属度的影响因素。结果表明:北京居民非通勤出行节律存在7种模式,根据不同模式区域的POI的频数密度和富集指数差异,可以将7种模式描述为:“居住导向型”“商业活动型”“商务导向型”“混合偏居住型”“混合偏商务型”“科教文化型”和“休闲娱乐型”。研究发现,不同模式的平均隶属度差异较大,影响因子也存在较大差异。在北京六环内非通勤出行节律模式混合度高,且不同模式的出行节律周期、功能特征和空间分布存在较大差异。此外,出行节律存在显著的空间依赖,并与城市商业、就业、居住等城市功能结构具有较强的相关性。本研究从时空融合视角对北京居民非通勤出行节律模式进行了深入探索,研究结果有助于进一步提高人群出行节律与城市功能结构关系的科学理解,从而能够为城市规划与建设提供重要的决策支撑。
文摘目的了解2021年广西壮族自治区北部侗族人群乙型肝炎(乙肝)病毒(Hepatitis B virus,HBV)血清流行率。方法采取单纯随机抽样方法在龙胜县选取1-59岁侗族人群开展问卷调查,采集血标本,采用酶联免疫吸附试验检测乙肝表面抗原(Hepatitis B surface antigen,HBsAg)、乙肝表面抗体(Hepatitis B surface antibody,HBsAb)、乙肝核心抗体(Hepatitis B core antibody,HBcAb)、乙肝e抗原(Hepatitis B e antigen,HBeAg)和乙肝e抗体(Hepatitis B e antibody,HBeAb),分析血清标志物流行率。结果在1261名调查对象中,HBsAg、HBsAb、HBcAb、HBeAg、HBeAb阳性率分别为6.11%、48.45%、15.86%、0.71%、15.31%。1-4岁、5-14岁、15-29岁、30-59岁人群HBsAg阳性率为分别为0.00%、0.00%、7.36%、7.99%(趋势χ^(2)=109.38,P<0.001);有、无、不详乙肝疫苗(Hepatitis B vaccine,HepB)免疫史人群HBsAg阳性率分别为0.31%、7.87%、8.18%(χ^(2)=25.14,P<0.001)。结论广西北部2021年1-59岁侗族人群HBV血清流行率总体处于中度水平,实施HepB免疫规划对控制儿童HBV感染取得显著效果。应继续做好新生儿HepB常规免疫,探索成人HepB免疫策略。
