In the conventional stochastic inversion method,the spatial structure information of underground strata is usually characterized by variograms.However,effectively characterizing the heterogeneity of complex strata is ...In the conventional stochastic inversion method,the spatial structure information of underground strata is usually characterized by variograms.However,effectively characterizing the heterogeneity of complex strata is difficult.In this paper,multiple parameters are used to fully explore the underground formation information in the known seismic reflection and well log data.The spatial structure characteristics of complex underground reservoirs are described more comprehensively using multiple statistical characteristic parameters.We propose a prestack seismic stochastic inversion method based on prior information on statistical characteristic parameters.According to the random medium theory,this method obtains several statistical characteristic parameters from known seismic and logging data,constructs a prior information model that meets the spatial structure characteristics of the underground strata,and integrates multiparameter constraints into the likelihood function to construct the objective function.The very fast quantum annealing algorithm is used to optimize and update the objective function to obtain the fi nal inversion result.The model test shows that compared with the traditional prior information model construction method,the prior information model based on multiple parameters in this paper contains more detailed stratigraphic information,which can better describe complex underground reservoirs.A real data analysis shows that the stochastic inversion method proposed in this paper can effectively predict the geophysical characteristics of complex underground reservoirs and has a high resolution.展开更多
Background End-of-life care is not usually a priority in cardiology departments. We sought to evaluate the changes in end-of-life care after the introduction of a do-not-resuscitate （DNR） order protocol. Methods ＆ ...Background End-of-life care is not usually a priority in cardiology departments. We sought to evaluate the changes in end-of-life care after the introduction of a do-not-resuscitate （DNR） order protocol. Methods ＆ Results Retrospective analysis of all deaths in a cardiology department in two periods, before and after the introduction of the protocol. Comparison of demographic characteristics, use of DNR orders, and end-of-life care issues between both periods, according to the presence in the second period of the new DNR sheet （Group A）, a conven- tional DNR order （Group B） or the absence of any DNR order （Group C）. The number of deaths was similar in both periods （n = 198 vs. n = 197）. The rate of patients dying with a DNR order increased significantly （57.1% vs. 68.5%; P = 0.02）. Only 4% of patients in both periods were aware of the decision taken about cardiopulmonary resuscitation. Patients in Group A received the DNR order one day earlier, and 24.5% received it within the first 24 h of admission （vs. 2.6% in the first period; P 〈 0.001）. All patients in Group A with an implantable cardioverter defibrillator （ICD） had shock therapies deactivated （vs. 25.0% in the first period; P = 0.02）. Conclusions The introduction of a DNR order protocol may improve end-of-life care in cardiac patients by increasing the use and shortening the time of registration of DNR orders. It may also contribute to increase ICD deactivation in patients with these orders in place. However, the introduction of the sheet in late stages of the disease failed to improve patient participation.展开更多
The basic inference function of mathematical statistics, the score function, is a vector function. The author has introduced the scalar score, a scalar inference function, which reflects main features of a continuous ...The basic inference function of mathematical statistics, the score function, is a vector function. The author has introduced the scalar score, a scalar inference function, which reflects main features of a continuous probability distribution and which is simple. Its simplicity makes it possible to introduce new relevant numerical characteristics of continuous distributions. The t-mean and score variance are descriptions of distributions without the drawbacks of the mean and variance, which may not exist even in cases of regular distributions. Their sample counterparts appear to be alternative descriptions of the observed data. The scalar score itself appears to be a new mathematical tool, which could be used in solving traditional statistical problems for models far from the normal one, skewed and heavy-tailed.展开更多
基金the National Science Foundation of China(No.42074136 and U19B2008)the Major National Science and Technology Projects(No.2016ZX05027004-001 and 2016ZX05002-005-009)+1 种基金the Fundamental Research Funds for the Central Universities(No.19CX02007A)China Postdoctoral Science Foundation(No.2020M672170).
文摘In the conventional stochastic inversion method,the spatial structure information of underground strata is usually characterized by variograms.However,effectively characterizing the heterogeneity of complex strata is difficult.In this paper,multiple parameters are used to fully explore the underground formation information in the known seismic reflection and well log data.The spatial structure characteristics of complex underground reservoirs are described more comprehensively using multiple statistical characteristic parameters.We propose a prestack seismic stochastic inversion method based on prior information on statistical characteristic parameters.According to the random medium theory,this method obtains several statistical characteristic parameters from known seismic and logging data,constructs a prior information model that meets the spatial structure characteristics of the underground strata,and integrates multiparameter constraints into the likelihood function to construct the objective function.The very fast quantum annealing algorithm is used to optimize and update the objective function to obtain the fi nal inversion result.The model test shows that compared with the traditional prior information model construction method,the prior information model based on multiple parameters in this paper contains more detailed stratigraphic information,which can better describe complex underground reservoirs.A real data analysis shows that the stochastic inversion method proposed in this paper can effectively predict the geophysical characteristics of complex underground reservoirs and has a high resolution.
文摘Background End-of-life care is not usually a priority in cardiology departments. We sought to evaluate the changes in end-of-life care after the introduction of a do-not-resuscitate （DNR） order protocol. Methods ＆ Results Retrospective analysis of all deaths in a cardiology department in two periods, before and after the introduction of the protocol. Comparison of demographic characteristics, use of DNR orders, and end-of-life care issues between both periods, according to the presence in the second period of the new DNR sheet （Group A）, a conven- tional DNR order （Group B） or the absence of any DNR order （Group C）. The number of deaths was similar in both periods （n = 198 vs. n = 197）. The rate of patients dying with a DNR order increased significantly （57.1% vs. 68.5%; P = 0.02）. Only 4% of patients in both periods were aware of the decision taken about cardiopulmonary resuscitation. Patients in Group A received the DNR order one day earlier, and 24.5% received it within the first 24 h of admission （vs. 2.6% in the first period; P 〈 0.001）. All patients in Group A with an implantable cardioverter defibrillator （ICD） had shock therapies deactivated （vs. 25.0% in the first period; P = 0.02）. Conclusions The introduction of a DNR order protocol may improve end-of-life care in cardiac patients by increasing the use and shortening the time of registration of DNR orders. It may also contribute to increase ICD deactivation in patients with these orders in place. However, the introduction of the sheet in late stages of the disease failed to improve patient participation.
文摘The basic inference function of mathematical statistics, the score function, is a vector function. The author has introduced the scalar score, a scalar inference function, which reflects main features of a continuous probability distribution and which is simple. Its simplicity makes it possible to introduce new relevant numerical characteristics of continuous distributions. The t-mean and score variance are descriptions of distributions without the drawbacks of the mean and variance, which may not exist even in cases of regular distributions. Their sample counterparts appear to be alternative descriptions of the observed data. The scalar score itself appears to be a new mathematical tool, which could be used in solving traditional statistical problems for models far from the normal one, skewed and heavy-tailed.
