The detailed analysis of individual rain events characteristics is an essential step for improving our understanding of variation in precipitation over different topographies. In this study, the homogeneity among rain...The detailed analysis of individual rain events characteristics is an essential step for improving our understanding of variation in precipitation over different topographies. In this study, the homogeneity among rain gauges was investigated using the concept of “rain event properties,” linking them to the main atmospheric system that affects the rainfall in the region. For this, eight properties of more than 23,000 rain events recorded at 47 meteorological stations in Mumbai, India, were analyzed utilizing seasonal (June-September) rainfall records over 2006-2016. The high similarities among the properties indicated the similarities among the rain gauges. Furthermore, similar rain gauges were distinguished, investigated and characterized by cluster analysis using self-organizing maps (SOM). The cluster analysis results show six clusters of similarly behaving rain gauges, where each cluster addresses one isolated class of variables for the rain gauge. Additionally, the clusters confirm the spatial variation of rainfall caused by the complex topography of Mumbai, comprising the flatland near the Arabian Sea, high-rise buildings (urban area) and mountain and hills areas (Sanjay Gandhi National Park located in the northern part of Mumbai).展开更多
文摘The detailed analysis of individual rain events characteristics is an essential step for improving our understanding of variation in precipitation over different topographies. In this study, the homogeneity among rain gauges was investigated using the concept of “rain event properties,” linking them to the main atmospheric system that affects the rainfall in the region. For this, eight properties of more than 23,000 rain events recorded at 47 meteorological stations in Mumbai, India, were analyzed utilizing seasonal (June-September) rainfall records over 2006-2016. The high similarities among the properties indicated the similarities among the rain gauges. Furthermore, similar rain gauges were distinguished, investigated and characterized by cluster analysis using self-organizing maps (SOM). The cluster analysis results show six clusters of similarly behaving rain gauges, where each cluster addresses one isolated class of variables for the rain gauge. Additionally, the clusters confirm the spatial variation of rainfall caused by the complex topography of Mumbai, comprising the flatland near the Arabian Sea, high-rise buildings (urban area) and mountain and hills areas (Sanjay Gandhi National Park located in the northern part of Mumbai).
文摘目的:探讨冠心病患者心指数和平均动脉压(mean arterial pressure,MAP)与抗氧化系统活性和心血管不良事件的关系。方法:随机选取诊治的冠心病患者105例,根据心指数分为<4.5 L/min/m^2(65例)和≥4.5 L/min/m^2(40例),另根据MAP值为65 mm Hg为分界点进行分组,检测两组抗氧化系统超氧化物歧化酶(Superoxide Dismutase,SOD)、谷胱甘肽过氧化物酶(glutathione peroxidase,GP)和过氧化氢酶(catalase,CAT)的水平,并分析其与不良事件发生率的相关性。结果:心指数<4.5 L/min/m^2组抗氧化指标SOD、GP和CAT均高于心指数≥4.5 L/min/m^2(P<0.05);MAP<65 mm Hg组患者上述抗氧化指标与MAP≥65 mm Hg比较差异无统计学意义(P>0.05);随访6个月发现,心指数≥4.5 L/min/m^2和MAP≥65 mm Hg组患者合并心血管不良事件包括再发心绞痛、再发心肌梗塞、恶性心律失常和心脏猝死,各组不良事件发生率比较差异有统计学意义(P<0.05)。结论:冠心病患者心指数越高,并发氧化应激反应越严重,同时增加了心血管不良事件发生率。
