Innovation Analysis Approach to Design Parameters of High Speed Train Carriage and Their Intrinsic Complexity Relationships

In view of the problem that it＇s difficult to accurately grasp the influence range and transmission path of the vehicle top design requirements on the underlying design parameters. Applying directed-weighted complex network to product parameter model is an important method that can clarify the relationships between product parameters and establish the top-down design of a product. The relationships of the product parameters of each node are calculated via a simple path searching algorithm, and the main design parameters are extracted by analysis and comparison. A uniform definition of the index formula for out-in degree can be provided based on the analysis of out- in-degree width and depth and control strength of train carriage body parameters. Vehicle gauge, axle load, crosswind and other parameters with higher values of the out-degree index are the most important boundary condi- tions; the most considerable performance indices are the parameters that have higher values of the out-in-degree index including torsional stiffness, maximum testing speed, service life of the vehicle, and so on; the main design parameters contain train carriage body weight, train weight per extended metre, train height and other parameters with higher values of the in-degree index. The network not only provides theoretical guidance for exploring the relationship of design parameters, but also further enriches the appli- cation of forward design method to high-speed trains.

A quantitative understanding of microRNA- mediated competing endogenous RNA regulation

MicroRNA （miRNA） plays key roles in post-transcriptional regulations. Recently, a competing endogenous RNA （ceRNA） hypothesis has been proposed that miRNA targets could communicate and regulate each other through titrating shared miRNAs, which provides a new layer of gene regulation. Though a number of ceRNAs playing biological functions have been identified, the ceRNA hypothesis remains controversial. Recent experimental and theoretical studies argued that the modulation of a single RNA species could hardly change the expression level of competing miRNA targets through ceRNA effect under normal physiological conditions. Here, we reviewed a common framework to model miRNA regulations, and summarized the current theoretical and experimental studies for quantitative understanding ceRNA effect. By revisiting a coarse-grained ceRNA model, we proposed that network topology could significantly influence the competing effect and ceRNA regulation at protein level could be much stronger than that at RNA level. We also provided a conditional independent binding equation to describe miRNA relative repression on different target, which could be applied to quantify siRNA off-target effect.