为探究城市带状绿地降减空气颗粒物的作用机制和效应,选取武汉市罗家港带状公园绿地及其周边建成环境作为研究对象,选择冬季天气晴朗无风且气象条件相似的3天进行重复观测,采用土地利用回归(land use regression,LUR)模型和主成分分析...为探究城市带状绿地降减空气颗粒物的作用机制和效应,选取武汉市罗家港带状公园绿地及其周边建成环境作为研究对象,选择冬季天气晴朗无风且气象条件相似的3天进行重复观测,采用土地利用回归(land use regression,LUR)模型和主成分分析相结合的方法,分析冬季城市带状绿地对空气PM_(10)和PM_(2.5)质量浓度的降减效应,识别其关键影响因素。结果显示,基于LUR模型得出城市带状绿地对空气PM_(10)和PM_(2.5)的降减作用存在宽度效应,宽度30~40 m的绿地在冬季对空气PM_(10)的降减效率最显著。同时,研究发现冬季城市带状绿地内部的空气PM_(2.5)和PM_(10)质量浓度会出现高于邻近道路位置的现象,空气PM_(10)和PM_(2.5)在城市带状绿地内存在明显的积聚效应。结果表明,城市带状绿地对空气PM_(10)和PM_(2.5)的降减作用会受到周边交通污染排放的干扰,不同宽度带状绿地创造的微气象条件也会对空气PM_(10)和PM_(2.5)的质量浓度产生一定影响。展开更多
通过北京市34个国控监测站点,建立0.5、1、1.5、2、3、4、5km的缓冲区,应用土地利用回归模型(Land Use Regression,LUR)对北京市采暖季与非采暖季PM_(2.5)浓度进行空间分布模拟,并采用留一交叉互验法验证模型精度。结果表明:采暖季LUR...通过北京市34个国控监测站点,建立0.5、1、1.5、2、3、4、5km的缓冲区,应用土地利用回归模型(Land Use Regression,LUR)对北京市采暖季与非采暖季PM_(2.5)浓度进行空间分布模拟,并采用留一交叉互验法验证模型精度。结果表明:采暖季LUR模型调整R^(2)为0.799,模拟精度为0.7992,均方根误差(Root Mean Square Error,RMSE)为6.66μg·m^(-3);非采暖季LUR模型调整R^(2)为0.807,模拟精度为0.8198,均方根误差为5.91μg·m^(-3),模型表现良好。从模拟结果来看,北京市PM_(2.5)主要分布在东南部人口、交通密集的平原区域,整体呈现南高北低的状态。展开更多
利用长沙市中心城区2015—2019年PM_(2.5)质量浓度监测数据,结合SPSS多元线性逐步回归功能和Arc GIS空间分析功能,构建土地利用回归(Land Use Regression,LUR)模型模拟长沙市2020年PM_(2.5)质量浓度空间分布。各季节的LUR模型拟合效果...利用长沙市中心城区2015—2019年PM_(2.5)质量浓度监测数据,结合SPSS多元线性逐步回归功能和Arc GIS空间分析功能,构建土地利用回归(Land Use Regression,LUR)模型模拟长沙市2020年PM_(2.5)质量浓度空间分布。各季节的LUR模型拟合效果均较理想,模型的自变量可解释70%以上的PM_(2.5)质量浓度变化;在构建土地利用回归模型中,研究区内的耕草地和气温对PM_(2.5)质量浓度影响最大,餐饮和道路次之;利用构建的LUR模型对研究区PM_(2.5)质量浓度进行2020年空间尺度的预测模拟,在空间上整体则呈现出由城中心区域向四周逐渐降低的态势。展开更多
Objective:To investigate whether tumor necrosis factor-α(TNFα)-238G/A and-308G/A polymorphisms are associated with susceptibility to pulmonary tuberculosis(TB) in the Lur ethnic population of Iran.Methods:TNF polymo...Objective:To investigate whether tumor necrosis factor-α(TNFα)-238G/A and-308G/A polymorphisms are associated with susceptibility to pulmonary tuberculosis(TB) in the Lur ethnic population of Iran.Methods:TNF polymorphisms genotyping was performed by polymerase chain reaction-restriction fragment length polymorphism method in 100 pulmonary TB patients and 100 healthy controls from the Lur population.Results:The allelic and genotypic frequencies of TNFα-238G/A polymorphism were not significantly different between the pulmonary TB patients and the healthy controls.However,the TNFα-308G/A polymorphism showed a significantly higher frequency of genotype GG in TB subjects compared to healthy controls(94% in the patients vs.62% in the controls,P = 0.0001,odds ratio = 0.104,confidence interval = 0.028-0.382).Moreover,in the TNFα-308G/A polymorphism,a significantly higher frequency of G allele was measured in the patient group compared with the control group(97%in the patient group vs.81% in the control group,P=0.0001,odds ratio = 0.132,confidence interval = 0.038-0.462).Conclusions:Our findings suggest that TNFα-308G/A polymorphism may increase the susceptibility to pulmonary TB in the Lur population of Iran.Despite TNFα polymorphisms and susceptibility to pulmonary TB,we suggest that more studies with larger sample size are needed in the future.Increasing our understanding of susceptibility risk factors may help to improve current preventive measures and treatment for TB.展开更多
In this work, the analysis of robust stability and design of robust H∞ output feedback controllers for a class of Lur'e systems with both time-delays and parameter uncertainties were studied. A robust H∞ output ...In this work, the analysis of robust stability and design of robust H∞ output feedback controllers for a class of Lur'e systems with both time-delays and parameter uncertainties were studied. A robust H∞ output feedback controller based on Linear Matrix Inequalities (LMIs) was developed to guarantee the robust stability and H∞ performance of the resultant closed-loop system. The presented design approach is based on the application of descriptor model transformation and Park's inequality for the bounding of cross terms and is expected to be less conservative compared to reported design methods. Finally, illustrative examples are advanced to demonstrate the superiority of the obtained method.展开更多
构建武汉市NO_2浓度的土地利用回归(Land use regression,LUR)模型,可用于个体NO_2长期暴露水平的估计。收集了武汉市10个空气质量监测站2015年的日均NO_2监测数据作为因变量,以武汉市土地利用、海拔高度、人口密度和道路总长度数据作...构建武汉市NO_2浓度的土地利用回归(Land use regression,LUR)模型,可用于个体NO_2长期暴露水平的估计。收集了武汉市10个空气质量监测站2015年的日均NO_2监测数据作为因变量,以武汉市土地利用、海拔高度、人口密度和道路总长度数据作为预测变量,采用逐步回归方法构建LUR模型,并采用留一交叉验证法对模型的精度进行评价。结果显示,武汉市NO_2浓度主要与所在地半径2千米缓冲区内的植被地面积和半径5千米缓冲区内的农用地面积相关。LUR模型的调整R^2大小为0.85,表明模型能解释大部分的变异;LOOCV检验的调整R^2大小为0.63,表明模型具有较好的拟合精度。展开更多
随着工业化加速和经济快速发展,PM2.5引起的空气污染日益严重,对环境和人类健康造成严重影响。本研究采用Adaboost机器学习方法优化土地利用回归模型(LUR),利用2015年中国PM2.5监测数据及多源遥感数据,模拟中国PM2.5的空间分布,并评价...随着工业化加速和经济快速发展,PM2.5引起的空气污染日益严重,对环境和人类健康造成严重影响。本研究采用Adaboost机器学习方法优化土地利用回归模型(LUR),利用2015年中国PM2.5监测数据及多源遥感数据,模拟中国PM2.5的空间分布,并评价模型拟合效果。结果显示,Adaboost优化后的LUR模型拟合精度显著提高,R2从0.241提高至0.62 (春)、0.69 (夏)、0.60 (秋)、0.67 (冬)和0.65 (年),并通过SPSS软件识别出28个与PM2.5浓度相关的变量。研究发现,PM2.5浓度具有季节性变化,冬季最高,夏季最低,且存在明显的空间自相关性,表现为高–高集聚以及低–低集聚。本研究为PM2.5浓度精确预测提供了新方法,对公共健康保护和空气质量管理具有重要意义。With the acceleration of industrialization and rapid economic development, the air pollution caused by PM2.5 is becoming more and more serious, causing serious impacts on the environment and human health. In this study, the Adaboost machine learning method was used to optimize the land use regression (LUR) model to simulate the spatial distribution of PM2.5 in China by using the 2015 Chinese PM2.5 monitoring data and multi-source remote sensing data, and to evaluate the model fitting effect. The results showed that the fitting accuracy of LUR model optimized by Adaboost was significantly improved, R2 increased from 0.241 to 0.62 (spring), 0.69 (summer), 0.60 (autumn), 0.67 (winter) and 0.65 (year). 28 variables related to PM2.5 concentration were identified by SPSS software. It was found that PM2.5 concentration has seasonal variations, with the highest in winter and the lowest in summer, and there is an obvious spatial autocorrelation, which is manifested as high-high concentration as well as low-low concentration. This study provides a new method for accurate prediction of PM2.5 concentration, which is important for public health protection and air quality management.展开更多
针对结构网格很难处理复杂外形和非结构网格无法计算具有边界层的粘性流动的缺点,发展了基于混合网格格点的隐式算法,成功地解决了在工程应用中难于处理的复杂外形粘性流场计算和效率问题。同时针对大规模的工程问题,发展了基于MPI通信...针对结构网格很难处理复杂外形和非结构网格无法计算具有边界层的粘性流动的缺点,发展了基于混合网格格点的隐式算法,成功地解决了在工程应用中难于处理的复杂外形粘性流场计算和效率问题。同时针对大规模的工程问题,发展了基于MPI通信技术的染色分层通讯并行计算方法。其中空间离散采用基于Roe格式发展的三阶迎风HLLEW(Harten-Lax-Van Leer-Einfeldt-Wada)或AUSM格式,湍流模型采用k??两方程湍流模型,时间推进考虑到LU-SGS并行等效较困难则采用基于DP-LUR(Data-Parallel Lower-Upper Relaxation)格式的隐式算法,计算CFL数可取到105量级,从2个到128个CPU的并行加速效率都保持在90%以上,大大提高了计算效率。算例对标模M6机翼模型流场进行计算,验证了方法的可靠性;然后对标模DLR-F6翼身组合体进行混合网格粘性与无粘计算结果进行比较,进一步验证混合网格方法;最后计算了DLR-WBNP外挂发动机翼身组合体模型,准确模拟了外挂和超临界机翼的相互干扰流动问题,采用4 CPU 16 CORE到24 CPU 96 CORE,2000步计算时间都不超过3小时。为民机跨声速气动弹性分析的计算效率提升提供了基本的数值模拟工具。展开更多
文摘为探究城市带状绿地降减空气颗粒物的作用机制和效应,选取武汉市罗家港带状公园绿地及其周边建成环境作为研究对象,选择冬季天气晴朗无风且气象条件相似的3天进行重复观测,采用土地利用回归(land use regression,LUR)模型和主成分分析相结合的方法,分析冬季城市带状绿地对空气PM_(10)和PM_(2.5)质量浓度的降减效应,识别其关键影响因素。结果显示,基于LUR模型得出城市带状绿地对空气PM_(10)和PM_(2.5)的降减作用存在宽度效应,宽度30~40 m的绿地在冬季对空气PM_(10)的降减效率最显著。同时,研究发现冬季城市带状绿地内部的空气PM_(2.5)和PM_(10)质量浓度会出现高于邻近道路位置的现象,空气PM_(10)和PM_(2.5)在城市带状绿地内存在明显的积聚效应。结果表明,城市带状绿地对空气PM_(10)和PM_(2.5)的降减作用会受到周边交通污染排放的干扰,不同宽度带状绿地创造的微气象条件也会对空气PM_(10)和PM_(2.5)的质量浓度产生一定影响。
文摘通过北京市34个国控监测站点,建立0.5、1、1.5、2、3、4、5km的缓冲区,应用土地利用回归模型(Land Use Regression,LUR)对北京市采暖季与非采暖季PM_(2.5)浓度进行空间分布模拟,并采用留一交叉互验法验证模型精度。结果表明:采暖季LUR模型调整R^(2)为0.799,模拟精度为0.7992,均方根误差(Root Mean Square Error,RMSE)为6.66μg·m^(-3);非采暖季LUR模型调整R^(2)为0.807,模拟精度为0.8198,均方根误差为5.91μg·m^(-3),模型表现良好。从模拟结果来看,北京市PM_(2.5)主要分布在东南部人口、交通密集的平原区域,整体呈现南高北低的状态。
文摘利用长沙市中心城区2015—2019年PM_(2.5)质量浓度监测数据,结合SPSS多元线性逐步回归功能和Arc GIS空间分析功能,构建土地利用回归(Land Use Regression,LUR)模型模拟长沙市2020年PM_(2.5)质量浓度空间分布。各季节的LUR模型拟合效果均较理想,模型的自变量可解释70%以上的PM_(2.5)质量浓度变化;在构建土地利用回归模型中,研究区内的耕草地和气温对PM_(2.5)质量浓度影响最大,餐饮和道路次之;利用构建的LUR模型对研究区PM_(2.5)质量浓度进行2020年空间尺度的预测模拟,在空间上整体则呈现出由城中心区域向四周逐渐降低的态势。
基金Supported by the Lorestan University of Medical Sciences under Grant No 1328
文摘Objective:To investigate whether tumor necrosis factor-α(TNFα)-238G/A and-308G/A polymorphisms are associated with susceptibility to pulmonary tuberculosis(TB) in the Lur ethnic population of Iran.Methods:TNF polymorphisms genotyping was performed by polymerase chain reaction-restriction fragment length polymorphism method in 100 pulmonary TB patients and 100 healthy controls from the Lur population.Results:The allelic and genotypic frequencies of TNFα-238G/A polymorphism were not significantly different between the pulmonary TB patients and the healthy controls.However,the TNFα-308G/A polymorphism showed a significantly higher frequency of genotype GG in TB subjects compared to healthy controls(94% in the patients vs.62% in the controls,P = 0.0001,odds ratio = 0.104,confidence interval = 0.028-0.382).Moreover,in the TNFα-308G/A polymorphism,a significantly higher frequency of G allele was measured in the patient group compared with the control group(97%in the patient group vs.81% in the control group,P=0.0001,odds ratio = 0.132,confidence interval = 0.038-0.462).Conclusions:Our findings suggest that TNFα-308G/A polymorphism may increase the susceptibility to pulmonary TB in the Lur population of Iran.Despite TNFα polymorphisms and susceptibility to pulmonary TB,we suggest that more studies with larger sample size are needed in the future.Increasing our understanding of susceptibility risk factors may help to improve current preventive measures and treatment for TB.
基金Project supported by the National Outstanding Young Science Foundation of China (No. 60025308)Teach and Research Award Program for Outstanding Young Teachers in Higher Education Institutions of Ministry of Education, China
文摘In this work, the analysis of robust stability and design of robust H∞ output feedback controllers for a class of Lur'e systems with both time-delays and parameter uncertainties were studied. A robust H∞ output feedback controller based on Linear Matrix Inequalities (LMIs) was developed to guarantee the robust stability and H∞ performance of the resultant closed-loop system. The presented design approach is based on the application of descriptor model transformation and Park's inequality for the bounding of cross terms and is expected to be less conservative compared to reported design methods. Finally, illustrative examples are advanced to demonstrate the superiority of the obtained method.
文摘构建武汉市NO_2浓度的土地利用回归(Land use regression,LUR)模型,可用于个体NO_2长期暴露水平的估计。收集了武汉市10个空气质量监测站2015年的日均NO_2监测数据作为因变量,以武汉市土地利用、海拔高度、人口密度和道路总长度数据作为预测变量,采用逐步回归方法构建LUR模型,并采用留一交叉验证法对模型的精度进行评价。结果显示,武汉市NO_2浓度主要与所在地半径2千米缓冲区内的植被地面积和半径5千米缓冲区内的农用地面积相关。LUR模型的调整R^2大小为0.85,表明模型能解释大部分的变异;LOOCV检验的调整R^2大小为0.63,表明模型具有较好的拟合精度。
文摘随着工业化加速和经济快速发展,PM2.5引起的空气污染日益严重,对环境和人类健康造成严重影响。本研究采用Adaboost机器学习方法优化土地利用回归模型(LUR),利用2015年中国PM2.5监测数据及多源遥感数据,模拟中国PM2.5的空间分布,并评价模型拟合效果。结果显示,Adaboost优化后的LUR模型拟合精度显著提高,R2从0.241提高至0.62 (春)、0.69 (夏)、0.60 (秋)、0.67 (冬)和0.65 (年),并通过SPSS软件识别出28个与PM2.5浓度相关的变量。研究发现,PM2.5浓度具有季节性变化,冬季最高,夏季最低,且存在明显的空间自相关性,表现为高–高集聚以及低–低集聚。本研究为PM2.5浓度精确预测提供了新方法,对公共健康保护和空气质量管理具有重要意义。With the acceleration of industrialization and rapid economic development, the air pollution caused by PM2.5 is becoming more and more serious, causing serious impacts on the environment and human health. In this study, the Adaboost machine learning method was used to optimize the land use regression (LUR) model to simulate the spatial distribution of PM2.5 in China by using the 2015 Chinese PM2.5 monitoring data and multi-source remote sensing data, and to evaluate the model fitting effect. The results showed that the fitting accuracy of LUR model optimized by Adaboost was significantly improved, R2 increased from 0.241 to 0.62 (spring), 0.69 (summer), 0.60 (autumn), 0.67 (winter) and 0.65 (year). 28 variables related to PM2.5 concentration were identified by SPSS software. It was found that PM2.5 concentration has seasonal variations, with the highest in winter and the lowest in summer, and there is an obvious spatial autocorrelation, which is manifested as high-high concentration as well as low-low concentration. This study provides a new method for accurate prediction of PM2.5 concentration, which is important for public health protection and air quality management.
文摘针对结构网格很难处理复杂外形和非结构网格无法计算具有边界层的粘性流动的缺点,发展了基于混合网格格点的隐式算法,成功地解决了在工程应用中难于处理的复杂外形粘性流场计算和效率问题。同时针对大规模的工程问题,发展了基于MPI通信技术的染色分层通讯并行计算方法。其中空间离散采用基于Roe格式发展的三阶迎风HLLEW(Harten-Lax-Van Leer-Einfeldt-Wada)或AUSM格式,湍流模型采用k??两方程湍流模型,时间推进考虑到LU-SGS并行等效较困难则采用基于DP-LUR(Data-Parallel Lower-Upper Relaxation)格式的隐式算法,计算CFL数可取到105量级,从2个到128个CPU的并行加速效率都保持在90%以上,大大提高了计算效率。算例对标模M6机翼模型流场进行计算,验证了方法的可靠性;然后对标模DLR-F6翼身组合体进行混合网格粘性与无粘计算结果进行比较,进一步验证混合网格方法;最后计算了DLR-WBNP外挂发动机翼身组合体模型,准确模拟了外挂和超临界机翼的相互干扰流动问题,采用4 CPU 16 CORE到24 CPU 96 CORE,2000步计算时间都不超过3小时。为民机跨声速气动弹性分析的计算效率提升提供了基本的数值模拟工具。
