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 $m$ new links to existing nodes with a probability $p$ based on popularity of the existing nodes and a probability $1-p$ based on fitness of the existing nodes. An explicit form of the degree distribution $P(p,k)$ is derived within a mean field approach. For reasonably large $k$, $P(p,k) \sim k^{-\gamma(p)}{\cal F}(k,p)$, where the function ${\cal F}$ is dominated by the behavior of $1/\ln(k/m)$ for small values of $p$ and becomes $k$-independent as $p \to 1$, and $\gamma(p)$ is a model-dependent exponent. The degree distribution and the exponent $\gamma(p)$ 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_

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