An exploration of social participation in Caribbean student nurses' use of social media in their learning journey

Aims: To identify how social participation facilitates pre-registration student nurses learning and professional development using social media. Design: A social survey using thematic analysis to explore Caribbean student nurses' views of social media usage from an open-ended question in a survey. Methods: A qualitative analysis of student nurses from Jamaica and Trinidad and Tobago, who completed an open-ended question in a survey. Data were analysed using thematic analysis. Results/Findings: The three themes identified were: (1) Social media and communica-tion; (2) Social media and self-care; and (3) Social media and learning. Conclusion: This paper used qualitative evidence to identify and report a new way of viewing SoMe in nursing education as a student- centred educational learning tool. SoMe can improve the effectiveness of student nurses learning, while developing fundamen-tal skills (open- mindedness, critical thinking, professionalism and decision- making) for nursing practice. Social participation and connectivism theory are embedded in student nurses' learning journey. However, it has been used by student nurses outside the tradi-tional university teaching and their capacity to own their personal learning. To meet the new generation of student nurses' learning needs, it is important that higher education institutions develop guidance, support and use of social media for learning to support student nurses in their education as students and also future professionals. Impact: This study addresses how social participation is used in social media to con-tribute to Caribbean student nurses' education. The main finding is the introduction of a new learning theory supporting learning using social media. This study has an impact on using social media for learning. Patient or Public Contribution: No patient or public contribution

Career guidance in communities

Career guidance in communities, by Rie Thomsen, Aarhus, Denmark, Aarhus University Press, 2012, 256 pp., £34.78 (paperback), ISBN 9788771240122 Reviewed by Tristram Hooley, Reader in Career Development, University of Derby, UK. Email: [email protected]/

Phase behavior of weakly polydisperse sticky hard spheres: Perturbation theory for the Percus-Yevick solution

We study the effects of size polydispersity on the gas-liquid phase behaviour of mixtures of sticky hard spheres. To achieve this, the system of coupled quadratic equations for the contact values of the partial cavity functions of the Percus-Yevick solution is solved within a perturbation expansion in the polydispersity, i.e. the normalized width of the size distribution. This allows us to make predictions for various thermodynamic quantities which can be tested against numerical simulations and experiments. In particular, we determine the leading-order effects of size polydispersity on the cloud curve delimiting the region of two-phase coexistence and on the associated shadow curve; we also study the extent of size fractionation between the coexisting phases. Different choices for the size-dependence of the adhesion strengths are examined carefully; the Asakura-Oosawa model of a mixture of polydisperse colloids and small polymers is studied as a specific example.Comment: 43 pages, 12 figures, and 1 tabl

Relativistic Doppler effect: universal spectra and zeptosecond pulses

We report on a numerical observation of the train of zeptosecond pulses produced by reflection of a relativistically intense femtosecond laser pulse from the oscillating boundary of an overdense plasma because of the Doppler effect. These pulses promise to become a unique experimental and technological tool since their length is of the order of the Bohr radius and the intensity is extremely high $\propto 10^{19}$ W/cm$^2$. We present the physical mechanism, analytical theory, and direct particle-in-cell simulations. We show that the harmonic spectrum is universal: the intensity of $n$th harmonic scales as $1/n^{p}$ for $n < 4\gamma^2$, where $\gamma$ is the largest $\gamma$--factor of the electron fluid boundary, $p=3$ and $p=5/2$ for the broadband and quasimonochromatic laser pulses respectively.Comment: 4 figure

Spectral analysis of deformed random networks

We study spectral behavior of sparsely connected random networks under the random matrix framework. Sub-networks without any connection among them form a network having perfect community structure. As connections among the sub-networks are introduced, the spacing distribution shows a transition from the Poisson statistics to the Gaussian orthogonal ensemble statistics of random matrix theory. The eigenvalue density distribution shows a transition to the Wigner's semicircular behavior for a completely deformed network. The range for which spectral rigidity, measured by the Dyson-Mehta $\Delta_3$ statistics, follows the Gaussian orthogonal ensemble statistics depends upon the deformation of the network from the perfect community structure. The spacing distribution is particularly useful to track very slight deformations of the network from a perfect community structure, whereas the density distribution and the $\Delta_3$ statistics remain identical to the undeformed network. On the other hand the $\Delta_3$ statistics is useful for the larger deformation strengths. Finally, we analyze the spectrum of a protein-protein interaction network for Helicobacter, and compare the spectral behavior with those of the model networks.Comment: accepted for publication in Phys. Rev. E (replaced with the final version

Navigability is a Robust Property

The Small World phenomenon has inspired researchers across a number of fields. A breakthrough in its understanding was made by Kleinberg who introduced Rank Based Augmentation (RBA): add to each vertex independently an arc to a random destination selected from a carefully crafted probability distribution. Kleinberg proved that RBA makes many networks navigable, i.e., it allows greedy routing to successfully deliver messages between any two vertices in a polylogarithmic number of steps. We prove that navigability is an inherent property of many random networks, arising without coordination, or even independence assumptions

Random matrix analysis of complex networks

We study complex networks under random matrix theory (RMT) framework. Using nearest-neighbor and next-nearest-neighbor spacing distributions we analyze the eigenvalues of adjacency matrix of various model networks, namely, random, scale-free and small-world networks. These distributions follow Gaussian orthogonal ensemble statistic of RMT. To probe long-range correlations in the eigenvalues we study spectral rigidity via $\Delta_3$ statistic of RMT as well. It follows RMT prediction of linear behavior in semi-logarithmic scale with slope being $\sim 1/\pi^2$. Random and scale-free networks follow RMT prediction for very large scale. Small-world network follows it for sufficiently large scale, but much less than the random and scale-free networks.Comment: accepted in Phys. Rev. E (replaced with the final version

Mapping dynamical systems onto complex networks

A procedure to characterize chaotic dynamical systems with concepts of complex networks is pursued, in which a dynamical system is mapped onto a network. The nodes represent the regions of space visited by the system, while edges represent the transitions between these regions. Parameters used to quantify the properties of complex networks, including those related to higher order neighborhoods, are used in the analysis. The methodology is tested for the logistic map, focusing the onset of chaos and chaotic regimes. It is found that the corresponding networks show distinct features, which are associated to the particular type of dynamics that have generated them.Comment: 13 pages, 8 eps files in 5 figure

Bias reduction in traceroute sampling: towards a more accurate map of the Internet

Traceroute sampling is an important technique in exploring the internet router graph and the autonomous system graph. Although it is one of the primary techniques used in calculating statistics about the internet, it can introduce bias that corrupts these estimates. This paper reports on a theoretical and experimental investigation of a new technique to reduce the bias of traceroute sampling when estimating the degree distribution. We develop a new estimator for the degree of a node in a traceroute-sampled graph; validate the estimator theoretically in Erdos-Renyi graphs and, through computer experiments, for a wider range of graphs; and apply it to produce a new picture of the degree distribution of the autonomous system graph.Comment: 12 pages, 3 figure