Characteristics of urban heat island （UHI） effect and its cause are investigated by using MODIS data in April 2004. Surface parameters from the MODIS data have surface temperature （ts） albedo（α）, and normalized...Characteristics of urban heat island （UHI） effect and its cause are investigated by using MODIS data in April 2004. Surface parameters from the MODIS data have surface temperature （ts） albedo（α）, and normalized difference vegetation index （NDVI）. Their heterogeneities over urban and rural area are analyzed based on land cover classification, and their relations are also presented in order to explain the UHI effect. The results show that there exists obvious the UHI effect. Ts over urban areas are by 10.83 % higher than those over rural area, and NDVI and α over urban area are by 62 % and 18.75 % less than those over rural area, respectively. Surface temperature has significantly negative correlation with NDVI and their correlation coefficient is -0.73. Correlation between NDVI and albedo is determined by the spectrum of light. Difference in vegetation cover is the primary cause of the UHI effect.展开更多
The Connolly （1999） elastic impedance （EI） equation is a function of P-wave velocity, S-wave velocity, density, and incidence angle. Conventional inversion methods based on this equation can only extract P-velocit...The Connolly （1999） elastic impedance （EI） equation is a function of P-wave velocity, S-wave velocity, density, and incidence angle. Conventional inversion methods based on this equation can only extract P-velocity, S-velocity, and density data directly and the elastic impedance at different incidence angles are not at the same scale, which makes comparison difficult. We propose a new elastic impedance equation based on the Gray et al. （1999） Zoeppritz approximation using Lamé parameters to address the conventional inversion method＇s deficiencies. This equation has been normalized to unify the elastic impedance dimensions at different angles and used for inversion. Lamé parameters can be extracted directly from the elastic impedance data obtained from inversion using the linear relation between Lamé parameters and elastic impedance. The application example shows that the elastic parameters extracted using this new method are more stable and correct and can recover the reservoir information very well. The new method is an improvement on the conventional method based on Connolly＇s equation.展开更多
During the process of coal prospecting and exploration, different measurement time, different logging instruments and series can lead to systematic errors in well logs. Accordingly, all logging curves need to be norma...During the process of coal prospecting and exploration, different measurement time, different logging instruments and series can lead to systematic errors in well logs. Accordingly, all logging curves need to be normalized in the mining area. By studying well-logging normalization methods, and focusing on the characteristics of the coalfield, the frequency histogram method was used in accordance with the condition of the Guqiao Coal Mine. In this way, the density and sonic velocity at marker bed in the non-key well were made to close to those in the key well, and were eventually equal. Well log normalization was completed when this method was applied to the entire logging curves. The results show that the scales of logging data were unified by normalizing coal logging curves, and the logging data were consistent with wave impedance inversion data. A satisfactory inversion effect was obtained.展开更多
The primary aim of clinical trials is to investigate whether a treatment is effective for a particular disease or condition. Randomized controlled clinical trials are considered to be the gold standard for evaluating ...The primary aim of clinical trials is to investigate whether a treatment is effective for a particular disease or condition. Randomized controlled clinical trials are considered to be the gold standard for evaluating the effect of a certain intervention. However, in clinical trials, even after randomization, there are situations where the patients differ substantially with respect to the baseline value of the outcome variable. Many a times the response to interventions depends on the baseline values of the outcome variable. When there are baseline-dependent treatment effects, differences among treatments vary as a function of baseline level. Although variation in outcome associated with baseline value is accounted for in ANCOVA, analysis of individual differences in treatment effect is precluded by the homogeneity of regression assumption. This assumption requires that expected differences in outcome among treatments be constant across all baseline levels. To overcome this difficulty, Weigel and Narvaez [7] proposed a regression model for two treatment groups to analyze individual response to treatments in randomized controlled clinical trials. The authors reviewed the model suggested by Weigel and Narvaez and extended further for three or more treatment groups. The utility of the model was demonstrated with real life data from a randomized controlled clinical trial of bronchial asthma.展开更多
基金the project of National Natural Science Funding of China under grant No.40075004.
文摘Characteristics of urban heat island （UHI） effect and its cause are investigated by using MODIS data in April 2004. Surface parameters from the MODIS data have surface temperature （ts） albedo（α）, and normalized difference vegetation index （NDVI）. Their heterogeneities over urban and rural area are analyzed based on land cover classification, and their relations are also presented in order to explain the UHI effect. The results show that there exists obvious the UHI effect. Ts over urban areas are by 10.83 % higher than those over rural area, and NDVI and α over urban area are by 62 % and 18.75 % less than those over rural area, respectively. Surface temperature has significantly negative correlation with NDVI and their correlation coefficient is -0.73. Correlation between NDVI and albedo is determined by the spectrum of light. Difference in vegetation cover is the primary cause of the UHI effect.
文摘The Connolly （1999） elastic impedance （EI） equation is a function of P-wave velocity, S-wave velocity, density, and incidence angle. Conventional inversion methods based on this equation can only extract P-velocity, S-velocity, and density data directly and the elastic impedance at different incidence angles are not at the same scale, which makes comparison difficult. We propose a new elastic impedance equation based on the Gray et al. （1999） Zoeppritz approximation using Lamé parameters to address the conventional inversion method＇s deficiencies. This equation has been normalized to unify the elastic impedance dimensions at different angles and used for inversion. Lamé parameters can be extracted directly from the elastic impedance data obtained from inversion using the linear relation between Lamé parameters and elastic impedance. The application example shows that the elastic parameters extracted using this new method are more stable and correct and can recover the reservoir information very well. The new method is an improvement on the conventional method based on Connolly＇s equation.
基金Supported by the National Basic Research Program of China （2009CB219603, 2010CB226800） the National Natural Science Foundation of China （40874071, 40672104）
文摘During the process of coal prospecting and exploration, different measurement time, different logging instruments and series can lead to systematic errors in well logs. Accordingly, all logging curves need to be normalized in the mining area. By studying well-logging normalization methods, and focusing on the characteristics of the coalfield, the frequency histogram method was used in accordance with the condition of the Guqiao Coal Mine. In this way, the density and sonic velocity at marker bed in the non-key well were made to close to those in the key well, and were eventually equal. Well log normalization was completed when this method was applied to the entire logging curves. The results show that the scales of logging data were unified by normalizing coal logging curves, and the logging data were consistent with wave impedance inversion data. A satisfactory inversion effect was obtained.
文摘The primary aim of clinical trials is to investigate whether a treatment is effective for a particular disease or condition. Randomized controlled clinical trials are considered to be the gold standard for evaluating the effect of a certain intervention. However, in clinical trials, even after randomization, there are situations where the patients differ substantially with respect to the baseline value of the outcome variable. Many a times the response to interventions depends on the baseline values of the outcome variable. When there are baseline-dependent treatment effects, differences among treatments vary as a function of baseline level. Although variation in outcome associated with baseline value is accounted for in ANCOVA, analysis of individual differences in treatment effect is precluded by the homogeneity of regression assumption. This assumption requires that expected differences in outcome among treatments be constant across all baseline levels. To overcome this difficulty, Weigel and Narvaez [7] proposed a regression model for two treatment groups to analyze individual response to treatments in randomized controlled clinical trials. The authors reviewed the model suggested by Weigel and Narvaez and extended further for three or more treatment groups. The utility of the model was demonstrated with real life data from a randomized controlled clinical trial of bronchial asthma.
