Rime length, stress, and association domains

Every regular Chinese syllable has a syllable tone (the tone we get when the syllable is read in isolation). In some Chinese languages, the tonal pattern of a multisyllabic expression is basically a concatenation of the syllable tones. In other Chinese languages, the tonal pattern of a multisyllabic expression is determined solely by the initial syllable. I call the former M -languages (represented by Mandarin) and the latter S -languages (represented by Shanghai). I argue that there is an additional difference in rime structures between the two language groups. In S-languages, all rimes are simple, i.e., there are no underlying diphthongs or codas. In M-languages, all regular rimes are heavy. I further argue that a syllable keeps its underlying tones only if it has stress. Independent metrical evidence tells us that heavy rimes may carry inherent stress. Thus, in M-languages, all regular syllables are stressed and retain their underlying tones (which may or may not undergo further changes). In contrast, in S-languages, regular rimes do not carry inherent stress; instead, only those syllables that are assigned stress by rule can keep their underlying tones and hence head a multisyllabic tonal domain.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/42998/1/10831_2005_Article_BF01440582.pd

A Motif-Based Analysis to Reveal Local Implied Information in Cross-Shareholding Networks

Cross-shareholding is a new type of strategic means for capital operation and is an important component of corporate governance. With the increasing complexity of business motivation, the structure of a cross-shareholding network (CSN) is becoming more intricate, and it exposes various important local patterns with different economic functions. The goal of this paper is to uncover investment mechanisms and economic functions implied in cross-shareholding networks (CSNs) by analyzing the local characteristic patterns of company interactions. In this paper, we construct the CSNs of listed companies and extract the directed triadic motifs to reveal the evolutionary characteristics of local investment patterns at the company and industry levels. On the company level, we find that companies tend to form V-shaped structures with other companies, but bidirectional shareholding patterns and circular relationships in the triads are scarce. On the industry level, we identify the characteristic linking patterns of some industries with a role analysis of the industries. Furthermore, we detect the evolutionary characteristics of industry interrelationships in three implied patterns. Such a motif evolution analysis may provide valuable information for investors and supervisory departments that make decisions about investment portfolios and policy. Meanwhile, this study is also helpful for exploring the implied information in other empirical networks