4,702 research outputs found
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
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