19,262 research outputs found
Hidden in plain sight: exploring men’s use of complementary and alternative medicine
Despite the increased attention given to the relationship between masculinity and health, the analysis of men’s use of complementary and alternative medicine (CAM) is relatively underdeveloped compared to studies of female use.
Through the thematic synthesis of existing research studies, this paper collates and analyses patterns of, and motivations for, male usage of CAM. We reveal that there are significant levels of male use of CAM which cannot be explained by recourse to general or gendered patterns of health seeking behaviour or health status. Men who use CAM tend to exhibit similar demographic characteristics to female users, but also show patterns of engagement that both reinforce and challenge hegemonic masculinity.
The paper suggests that there remains a need to investigate the nuances and complexities of the motivations behind male usage patterns, and interrogate how these intersect with the performance of masculine selves
A network-based threshold model for the spreading of fads in society and markets
We investigate the behavior of a threshold model for the spreading of fads
and similar phenomena in society. The model is giving the fad dynamics and is
intended to be confined to an underlying network structure. We investigate the
whole parameter space of the fad dynamics on three types of network models. The
dynamics we discover is rich and highly dependent on the underlying network
structure. For some range of the parameter space, for all types of substrate
networks, there are a great variety of sizes and life-lengths of the fads --
what one see in real-world social and economical systems
Dynamics of opinion formation in a small-world network
The dynamical process of opinion formation within a model using a local
majority opinion updating rule is studied numerically in networks with the
small-world geometrical property. The network is one in which shortcuts are
added to randomly chosen pairs of nodes in an underlying regular lattice. The
presence of a small number of shortcuts is found to shorten the time to reach a
consensus significantly. The effects of having shortcuts in a lattice of fixed
spatial dimension are shown to be analogous to that of increasing the spatial
dimension in regular lattices. The shortening of the consensus time is shown to
be related to the shortening of the mean shortest path as shortcuts are added.
Results can also be translated into that of the dynamics of a spin system in a
small-world network.Comment: 10 pages, 5 figure
Identity and Search in Social Networks
Social networks have the surprising property of being "searchable": Ordinary
people are capable of directing messages through their network of acquaintances
to reach a specific but distant target person in only a few steps. We present a
model that offers an explanation of social network searchability in terms of
recognizable personal identities: sets of characteristics measured along a
number of social dimensions. Our model defines a class of searchable networks
and a method for searching them that may be applicable to many network search
problems, including the location of data files in peer-to-peer networks, pages
on the World Wide Web, and information in distributed databases.Comment: 4 page, 3 figures, revte
Depression and anxiety in prostate cancer: a systematic review and meta-analysis of prevalence rates
ObjectivesTo systematically review the literature pertaining to the prevalence of depression and anxiety in patients with prostate cancer as a function of treatment stage.DesignSystematic review and meta-analysis.Participants4494 patients with prostate cancer from primary research investigations.Primary outcome measureThe prevalence of clinical depression and anxiety in patients with prostate cancer as a function of treatment stage.ResultsWe identified 27 full journal articles that met the inclusion criteria for entry into the meta-analysis resulting in a pooled sample size of 4494 patients. The meta-analysis of prevalence rates identified pretreatment, on-treatment and post-treatment depression prevalences of 17.27% (95% CI 15.06% to 19.72%), 14.70% (95% CI 11.92% to 17.99%) and 18.44% (95% CI 15.18% to 22.22%), respectively. Pretreatment, on-treatment and post-treatment anxiety prevalences were 27.04% (95% CI 24.26% to 30.01%), 15.09% (95% CI 12.15% to 18.60%) and 18.49% (95% CI 13.81% to 24.31%), respectively.ConclusionsOur findings suggest that the prevalence of depression and anxiety in men with prostate cancer, across the treatment spectrum, is relatively high. In light of the growing emphasis placed on cancer survivorship, we consider that further research within this area is warranted to ensure that psychological distress in patients with prostate cancer is not underdiagnosed and undertreated
Scale-free networks with tunable degree distribution exponents
We propose and study a model of scale-free growing networks that gives a
degree distribution dominated by a power-law behavior with a model-dependent,
hence tunable, exponent. The model represents a hybrid of the growing networks
based on popularity-driven and fitness-driven preferential attachments. As the
network grows, a newly added node establishes new links to existing nodes
with a probability based on popularity of the existing nodes and a
probability based on fitness of the existing nodes. An explicit form of
the degree distribution is derived within a mean field approach. For
reasonably large , , where the
function is dominated by the behavior of for small
values of and becomes -independent as , and is a
model-dependent exponent. The degree distribution and the exponent
are found to be in good agreement with results obtained by extensive numerical
simulations.Comment: 12 pages, 2 figures, submitted to PR
Numerical Investigation of Graph Spectra and Information Interpretability of Eigenvalues
We undertake an extensive numerical investigation of the graph spectra of
thousands regular graphs, a set of random Erd\"os-R\'enyi graphs, the two most
popular types of complex networks and an evolving genetic network by using
novel conceptual and experimental tools. Our objective in so doing is to
contribute to an understanding of the meaning of the Eigenvalues of a graph
relative to its topological and information-theoretic properties. We introduce
a technique for identifying the most informative Eigenvalues of evolving
networks by comparing graph spectra behavior to their algorithmic complexity.
We suggest that extending techniques can be used to further investigate the
behavior of evolving biological networks. In the extended version of this paper
we apply these techniques to seven tissue specific regulatory networks as
static example and network of a na\"ive pluripotent immune cell in the process
of differentiating towards a Th17 cell as evolving example, finding the most
and least informative Eigenvalues at every stage.Comment: Forthcoming in 3rd International Work-Conference on Bioinformatics
and Biomedical Engineering (IWBBIO), Lecture Notes in Bioinformatics, 201
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_
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Today's problems with the evaluation methods of full lightning impulse parameters as described in IEC 60060-1
In this paper the present problems with the evaluation methods for lightning impulse parameters, as defined in IEC 60060-1, are described. Also the current practice of evaluation in many laboratories world-wide, that is obtained by a questionnaire, is presented. Some of the work performed up the present time and the initial conclusions are reported, then some recommendations are made for future work
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