Second-Order Assortative Mixing in Social Networks

In a social network, the number of links of a node, or node degree, is often assumed as a proxy for the node's importance or prominence within the network. It is known that social networks exhibit the (first-order) assortative mixing, i.e. if two nodes are connected, they tend to have similar node degrees, suggesting that people tend to mix with those of comparable prominence. In this paper, we report the second-order assortative mixing in social networks. If two nodes are connected, we measure the degree correlation between their most prominent neighbours, rather than between the two nodes themselves. We observe very strong second-order assortative mixing in social networks, often significantly stronger than the first-order assortative mixing. This suggests that if two people interact in a social network, then the importance of the most prominent person each knows is very likely to be the same. This is also true if we measure the average prominence of neighbours of the two people. This property is weaker or negative in non-social networks. We investigate a number of possible explanations for this property. However, none of them was found to provide an adequate explanation. We therefore conclude that second-order assortative mixing is a new property of social networks.Comment: Cite as: Zhou S., Cox I.J., Hansen L.K. (2017) Second-Order Assortative Mixing in Social Networks. In: Goncalves B., Menezes R., Sinatra R., Zlatic V. (eds) Complex Networks VIII. CompleNet 2017. Springer Proceedings in Complexity. Springer, Cham. https://doi.org/10.1007/978-3-319-54241-6_

The US stock market leads the Federal funds rate and Treasury bond yields

Using a recently introduced method to quantify the time varying lead-lag dependencies between pairs of economic time series (the thermal optimal path method), we test two fundamental tenets of the theory of fixed income: (i) the stock market variations and the yield changes should be anti-correlated; (ii) the change in central bank rates, as a proxy of the monetary policy of the central bank, should be a predictor of the future stock market direction. Using both monthly and weekly data, we found very similar lead-lag dependence between the S&P500 stock market index and the yields of bonds inside two groups: bond yields of short-term maturities (Federal funds rate (FFR), 3M, 6M, 1Y, 2Y, and 3Y) and bond yields of long-term maturities (5Y, 7Y, 10Y, and 20Y). In all cases, we observe the opposite of (i) and (ii). First, the stock market and yields move in the same direction. Second, the stock market leads the yields, including and especially the FFR. Moreover, we find that the short-term yields in the first group lead the long-term yields in the second group before the financial crisis that started mid-2007 and the inverse relationship holds afterwards. These results suggest that the Federal Reserve is increasingly mindful of the stock market behavior, seen at key to the recovery and health of the economy. Long-term investors seem also to have been more reactive and mindful of the signals provided by the financial stock markets than the Federal Reserve itself after the start of the financial crisis. The lead of the S&P500 stock market index over the bond yields of all maturities is confirmed by the traditional lagged cross-correlation analysis.Comment: 12 pages, 7 figures, 1 tabl

Dynamics of one-dimensional tight-binding models with arbitrary time-dependent external homogeneous fields

The exact propagators of two one-dimensional systems with time-dependent external fields are presented by following the path-integral method. It is shown that the Bloch acceleration theorem can be generalized to the impulse-momentum theorem in quantum version. We demonstrate that an evolved Gaussian wave packet always keeps its shape in an arbitrary time-dependent homogeneous driven field. Moreover, that stopping and accelerating of a wave packet can be achieved by the pulsed field in a diabatic way.Comment: 8 pages, 6 figure

Giant schwannoma of thoracic vertebra: A case report

BACKGROUND,It is relatively rare for schwannomas to invade bone, but it is very rare for a large,mass to form concurrently in the paravertebral region. Surgical resection is the,only effective treatment. Because of the extensive tumor involvement and the,many important surrounding structures, the tumor needs to be fully exposed.,Most of the tumors are completely removed by posterior combined open-heart,surgery to relieve spinal cord compression, restore the stability of the spine and,maximize the recovery of nerve and spinal cord function. The main objective of,this article is to present a schwannoma that had invaded the T5 and T6 vertebral,bodies and formed a large paravertebral mass with simultaneous invasion of the,spinal canal and compression of the spinal cord.,CASE SUMMARY,A 40-year-old female suffered from intermittent chest and back pain for 8 years.,Computed tomography and magnetic resonance imaging scans showed a,paravertebral tumor of approximately 86 mm × 109 mm × 116 mm, where the,adjacent T5 and T6 vertebral bodies were invaded by the tumor, the right intervertebral,foramen was enlarged, and the tumor had invaded the spinal canal to,compress the thoracic medulla. The preoperative puncture biopsy diagnosed a,benign schwannoma. Complete resection of the tumor was achieved by a two-step,operation. In the first step, the thoracic surgeon adopted a lateral approach to,separate the thoracic tumor from the lung. In the second step, a spine surgeon,performed a posterior midline approach to dissect the tumor from the vertebral,junction through removal of the tumor from the posterior side and further,resection of the entire T5 and T6 vertebral bodies. The large bone defect was,reconstructed with titanium mesh, and the posterior root arch was nail-fixed. Due,to the large amount of intraoperative bleeding, we performed tumor angioembolization,before surgery to reduce and avoid large intraoperative bleeding. The,postoperative diagnosis of benign schwannoma was confirmed by histochemical,examination. There was no sign of tumor recurrence or spinal instability during,the 2-year follow-up.,CONCLUSION,Giant schwannoma is uncommon. In this case, a complete surgical resection of a,giant thoracic nerve sheath tumor that invaded part of the vertebral body and,compressed the spinal cord was safe and effective

Tissue-specific regulation of Na+ and K+ transporters explains genotypic differences in salinity stress tolerance in rice

Rice (Oryza sativa) is a staple food that feeds more than half the world population. As rice is highly sensitive to soil salinity, current trends in soil salinization threaten global food security. To better understand the mechanistic basis of salinity tolerance in rice, three contrasting rice cultivars - Reiziq (tolerant), Doongara (moderately tolerant), and Koshihikari (sensitive) - were examined and the differences in operation of key ion transporters mediating ionic homeostasis in these genotypes were evaluated. Tolerant varieties had reduced Na+ translocation from roots to shoots. Electrophysiological and quantitative reverse transcription PCR experiments showed that tolerant genotypes possessed 2-fold higher net Na+ efflux capacity in the root elongation zone. Interestingly, this efflux was only partially mediated by the plasma membrane Na+/H+ antiporter (OsSOS1), suggesting involvement of some other exclusion mechanisms. No significant difference in Na+ exclusion from the mature root zones was found between cultivars, and the transcriptional changes in the salt overly sensitive signaling pathway genes in the elongation zone were not correlated with the genetic variability in salinity tolerance amongst genotypes. The most important hallmark of differential salinity tolerance was in the ability of the plant to retain K+ in both root zones. This trait was conferred by at least three complementary mechanisms: (1) its superior ability to activate H+-ATPase pump operation, both at transcriptional and functional levels; (2) reduced sensitivity of K+ efflux channels to reactive oxygen species; and (3) smaller upregulation in OsGORK and higher upregulation of OsAKT1 in tolerant cultivars in response to salt stress. These traits should be targeted in breeding programs aimed to improve salinity tolerance in commercial rice cultivars

A predictive model of users’ behavior and values of smart energy meters using PLS-SEM

© Springer Nature Switzerland AG 2020. A smart energy metering system is an IoT device that connects several electrical household devices and record, monitor, estimate, control in-house energy consumption in a real-time basis. Although smart energy meters have great capabilities, this technology is still in infancy stages in many developing countries, and little is known about what perceived values are associated with smart meters from residents’ perspectives. Therefore, this research aimed to fill this gap by examining the impact of six different types of perceived values on residents’ intentions to use smart meters in UAE. The study followed a quantitative approach by gathering 266 survey responses which were tested by using Partial Least Squares-Structural Equation Modeling (PLS-SEM). The statistical results genuinely indicated that perceived epistemic values, environmental values, emotional values, and convenience values can significantly impact residents’ intention to use smart meter, whereas social values and monetary values found to have no significant impact on their intentions to use this technology. Theoretical and practical implications are indicated, and directions of future research are specified afterwards

Emergence of scale-free close-knit friendship structure in online social networks

Despite the structural properties of online social networks have attracted much attention, the properties of the close-knit friendship structures remain an important question. Here, we mainly focus on how these mesoscale structures are affected by the local and global structural properties. Analyzing the data of four large-scale online social networks reveals several common structural properties. It is found that not only the local structures given by the indegree, outdegree, and reciprocal degree distributions follow a similar scaling behavior, the mesoscale structures represented by the distributions of close-knit friendship structures also exhibit a similar scaling law. The degree correlation is very weak over a wide range of the degrees. We propose a simple directed network model that captures the observed properties. The model incorporates two mechanisms: reciprocation and preferential attachment. Through rate equation analysis of our model, the local-scale and mesoscale structural properties are derived. In the local-scale, the same scaling behavior of indegree and outdegree distributions stems from indegree and outdegree of nodes both growing as the same function of the introduction time, and the reciprocal degree distribution also shows the same power-law due to the linear relationship between the reciprocal degree and in/outdegree of nodes. In the mesoscale, the distributions of four closed triples representing close-knit friendship structures are found to exhibit identical power-laws, a behavior attributed to the negligible degree correlations. Intriguingly, all the power-law exponents of the distributions in the local-scale and mesoscale depend only on one global parameter -- the mean in/outdegree, while both the mean in/outdegree and the reciprocity together determine the ratio of the reciprocal degree of a node to its in/outdegree.Comment: 48 pages, 34 figure

Tag-Aware Recommender Systems: A State-of-the-art Survey

In the past decade, Social Tagging Systems have attracted increasing attention from both physical and computer science communities. Besides the underlying structure and dynamics of tagging systems, many efforts have been addressed to unify tagging information to reveal user behaviors and preferences, extract the latent semantic relations among items, make recommendations, and so on. Specifically, this article summarizes recent progress about tag-aware recommender systems, emphasizing on the contributions from three mainstream perspectives and approaches: network-based methods, tensor-based methods, and the topic-based methods. Finally, we outline some other tag-related works and future challenges of tag-aware recommendation algorithms.Comment: 19 pages, 3 figure

Detecting rich-club ordering in complex networks

Uncovering the hidden regularities and organizational principles of networks arising in physical systems ranging from the molecular level to the scale of large communication infrastructures is the key issue for the understanding of their fabric and dynamical properties [1-5]. The ``rich-club'' phenomenon refers to the tendency of nodes with high centrality, the dominant elements of the system, to form tightly interconnected communities and it is one of the crucial properties accounting for the formation of dominant communities in both computer and social sciences [4-8]. Here we provide the analytical expression and the correct null models which allow for a quantitative discussion of the rich-club phenomenon. The presented analysis enables the measurement of the rich-club ordering and its relation with the function and dynamics of networks in examples drawn from the biological, social and technological domains.Comment: 1 table, 3 figure