The L12 type trialuminide compounds Al3M possess outstanding mechanical properties, which enable them to be ideal for dispersed strengthening phases for the high-strength thermally stable Al based alloys. Ab-initio calculations based on the density functional theory (DFT) were performed to study the structural, electronic, thermal, and thermodynamic properties of L12-Al3M (M = Er, Hf, Lu, Sc, Ti, Tm, Yb, Li, Mg, Zr) structures in Al alloys. The total energy calculations showed that the L12 structures are quite stable. On the basis of the thermodynamic calculation, we found that the Yb, Lu, Er, and Tm atoms with a larger atomic radii than Al promoted the thermal stability of the Al alloys, and the thermal stability rank has been constructed as: Al3Yb > Al3Lu > Al3Er > Al3Tm > Al, which shows an apparent positive correlation between the atomic size and thermal stability. The chemical bond offers a firm basis upon which to forge links not only within chemistry but also with the macroscopic properties of materials. A careful analysis of the charge density indicated that Yb, Lu, Er, and Tm atoms covalently bonded to Al, providing a strong intrinsic basis for the thermal stability of the respective structures, suggesting that the addition of big atoms (Yb, Lu, Er, and Tm) are beneficial for the thermal stability of Al alloys.

Sina Weibo, which was launched in 2009, is the most popular Chinese micro-blogging service. It has been reported that Sina Weibo has more than 400 million registered users by the end of the third quarter in 2012. Sina Weibo and Twitter have a lot in common, however, in terms of the following preference, Sina Weibo users, most of whom are Chinese, behave differently compared with those of Twitter.This work is based on a data set of Sina Weibo which contains 80.8 million users' profiles and 7.2 billion relations and a large data set of Twitter. Firstly some basic features of Sina Weibo and Twitter are analyzed such as degree and activeness distribution, correlation between degree and activeness, and the degree of separation. Then the following preference is investigated by studying the assortative mixing, friend similarities, following distribution, edge balance ratio, and ranking correlation, where edge balance ratio is newly proposed to measure balance property of graphs. It is found that Sina Weibo has a lower reciprocity rate, more positive balanced relations and is more disassortative. Coinciding with Asian traditional culture, the following preference of Sina Weibo users is more concentrated and hierarchical: they are more likely to follow people at higher or the same social levels and less likely to follow people lower than themselves. In contrast, the same kind of following preference is weaker in Twitter. Twitter users are open as they follow people from levels, which accords with its global characteristic and the prevalence of western civilization. The message forwarding behavior is studied by displaying the propagation levels, delays, and critical users. The following preference derives from not only the usage habits but also underlying reasons such as personalities and social moralities that is worthy of future research. To the best of our knowledge, this is the first comparative work focusing on the following behavior using both large-scale data set of a global and a Chinese local online social networks.

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In this paper, we attempt to solve the problem of defense against sybil attacks in directed social networks. We propose a set of measures for the quality of network partitions, with modularity as a special case. We present an algorithm based on the set of measures and iterative optimization to detect the sybil region. The algorithm is evaluated using a subset of realworld social topology and is confirmed to be efficient for solving the problem. Moreover, a comparison between the proposed algorithm and SybilDefender is provided, which shows that the proposed algorithm is superior for the sybil region detection problem in directed social networks.

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