Bulk flow scaling for turbulent channel and pipe flows

We report a theory deriving bulk flow scaling for canonical wall-bounded flows. The theory accounts for the symmetries of boundary geometry (flat plate channel versus circular pipe) by a variational calculation for a large-scale energy length, which characterizes its bulk flow scaling by a simple exponent, i.e. $m=4$ for channel and 5 for pipe. The predicted mean velocity shows excellent agreement with several dozen sets of quality empirical data for a wide range of the Reynolds number (Re), with a universal bulk flow constant $\kappa\approx0.45$. Predictions for dissipation and turbulent transport in the bulk flow are also given, awaiting data verification.Comment: 4 pages, 4 figure

Research and Prediction on the Sharing of WeChat Official Accounts’ Articles

With the development of mobile Internet, We Media was born. WeChat Official Account Platform is the largest we media platform in China. In WeChat social network, information can only be rapidly spread through the sharing operation of users. This paper takes WeChat official accounts as the object and uses logistic regression model to explore the influencing factors on sharing. After that, a prediction model is constructed based on logistic regression and support vector machine. The significance of this study is to propose the factors that influence WeChat official accounts’ articles sharing, and to construct a sharing prediction model

Cultural evolution: the case of babies’ first names

In social sciences, there is currently rare consensus on the underlying mechanism for cultural evolution, partially due to lack of suitable data. The evolution of first names of newborn babies offers a remarkable example for such researches. In this paper, we employ the historical data on baby names from the United States to investigate the evolutionary process of culture, in particular focusing on how inequality among baby names changes over time. Then we propose a stochastic model where individual choice is determined by both individual preference and social influence, and show that the decrease in the strength of social influence can account for all the observed empirical features. Therefore, we claim that the weakening of social influence drives cultural evolution