The phenomenon described here has no scientific title, but occurs frequently in daily living, from science to philosophy, religion, and medicine. In every field of human endeavor, when a view is expressed, sharp and p...The phenomenon described here has no scientific title, but occurs frequently in daily living, from science to philosophy, religion, and medicine. In every field of human endeavor, when a view is expressed, sharp and profound differences of opinion ensue. Initially, we coin this phenomenon as ＂understanding blindness＂ or ＂mind＇s awareness.＂ Thereafter, we decide to refer to it as ＂mind blindness,＂ a concept introduced to science by Professor Simon Baron-Cohen, who coins it for a cognitive disorder associated with autism, Asperger＇s syndrome, and schizophrenia. Baron-Cohen＇s usage has subsequently been extended to dementia, bi-polar disorders, antisocial personality disorders, and even normal aging. In our view, definition and identification of ＂mind blindness＂ in philosophy, religion, science, medicine, and at end-of-life care can help mankind to better understand mechanisms of human behavior, and the causes of conflicts, controversies, contradictions, and sharp differences of opinion in human life, and even to solve some of them.展开更多
Network and equation-based （EB） models are two prominent methods used in the study of epidemics. While EB models use a global approach to model aggregate population, net- work models focus on the behavior of individ...Network and equation-based （EB） models are two prominent methods used in the study of epidemics. While EB models use a global approach to model aggregate population, net- work models focus on the behavior of individuals in the population. The two approaches have been used in several areas of research, including finance, computer science, social science and epidemiology. In this study, epidemiology is used to contrast EB models with network models. The methods are based on the assumptions and properties of compartmental models. In EB models we solve a system of ordinary differential equations and in network models we simulate the spread of epidemics on contact networks using bond percolation. We examine the impact of network structures on the spread of infection by considering various networks, including Poisson, Erd3s R6nyi, Scale-free, and Watts- Strogatz small-world networks, and discuss how control measures can make use of the network structures. In addition, we simulate EB assumptions on Watts-Strogatz net- works to determine when the results are similar to that of EB models. As a case study, we use data from the 1918 Spanish flu pandemic and that from measles outbreak to validate our results.展开更多
文摘The phenomenon described here has no scientific title, but occurs frequently in daily living, from science to philosophy, religion, and medicine. In every field of human endeavor, when a view is expressed, sharp and profound differences of opinion ensue. Initially, we coin this phenomenon as ＂understanding blindness＂ or ＂mind＇s awareness.＂ Thereafter, we decide to refer to it as ＂mind blindness,＂ a concept introduced to science by Professor Simon Baron-Cohen, who coins it for a cognitive disorder associated with autism, Asperger＇s syndrome, and schizophrenia. Baron-Cohen＇s usage has subsequently been extended to dementia, bi-polar disorders, antisocial personality disorders, and even normal aging. In our view, definition and identification of ＂mind blindness＂ in philosophy, religion, science, medicine, and at end-of-life care can help mankind to better understand mechanisms of human behavior, and the causes of conflicts, controversies, contradictions, and sharp differences of opinion in human life, and even to solve some of them.
文摘Network and equation-based （EB） models are two prominent methods used in the study of epidemics. While EB models use a global approach to model aggregate population, net- work models focus on the behavior of individuals in the population. The two approaches have been used in several areas of research, including finance, computer science, social science and epidemiology. In this study, epidemiology is used to contrast EB models with network models. The methods are based on the assumptions and properties of compartmental models. In EB models we solve a system of ordinary differential equations and in network models we simulate the spread of epidemics on contact networks using bond percolation. We examine the impact of network structures on the spread of infection by considering various networks, including Poisson, Erd3s R6nyi, Scale-free, and Watts- Strogatz small-world networks, and discuss how control measures can make use of the network structures. In addition, we simulate EB assumptions on Watts-Strogatz net- works to determine when the results are similar to that of EB models. As a case study, we use data from the 1918 Spanish flu pandemic and that from measles outbreak to validate our results.
