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Objective We aimed to explore the symptom-herb relationships and the evolution law implied in the development of stroke treated by traditional Chinese medicine ( TCM). Methods Based on ancient books on TCM, a stroke symptom-herb network was constructed, and its temporal evolution was analyzed by network topology and node ranking feature calculation, community discovery, subnetwork similarity calculation, and other method. Results The changes in the structure and scale of the symptom-herb network of stroke and evolution analysis of the node sorting characteristics revealed the key symptoms and core herbs used to treat stroke in different historical periods, which confirmed the changes in the theoretical understanding of stroke in TCM and the gradual maturity of symptom differentiation and treatment. Subnetwork similarity analysis showed that stroke can be roughly divided into three categories: true stroke, analogous stroke, and acute stroke. Community discovery and evolutionary analysis uncovered symptom and drug combinations that were closely linked in different historical periods. Conclusion The temporal evolution analysis of complex networks serves as a new method for studying the complex relationship and evolution law between stroke-related symptoms and herbs used. The result can be used as a reference for combining the source and flow of stroke and clinical symptom differentiation and treatment. [ABSTRACT FROM AUTHOR]

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In this paper, a model was proposed to investigate the relationship among information access, information literacy, information application and digital opportunity. Firstly, besides verifying the model fit and explaining its influential effects, this study aims to evaluate whether different individual traits will have moderating effects on this relational model by using a multi-group analysis. Secondly, the study will further explore the intention for using the Internet for those people who are digital inclusive. We will classify them into three groups in light of their awareness of and attitude towards the computer and the Internet; these are awareness group, interest group and desire group. Meanwhile, the relations between individual traits and these three groups will also be discussed by using a correspondence analysis. Four important findings are noted as follows: (1) the relational model has a good model fit and explanatory ability; (2) different age and education levels have significant moderating effects on the relational model; (3) the result gleaned from the multi-group model analysis indicates that people with old age had higher influential effects on how the information access might impact on the information literacy; people with young and elementary education had higher influential effects on how the information access might impact on the information application; people with middle age had higher influential effects on how the information literacy might impact on the information application; people with old age had higher influential effects on how the information application might impact on the digital opportunity; (4) the result from the digital inclusion analysis unfolds that people with the elementary education was clustered into the awareness group; people who are over 61 years old and male was assembled into the interest group; people who are between 41 and 60 years old and female was classified into the desire group. [ABSTRACT FROM AUTHOR]