Experience of domestic violence by women attending an inner city accident and emergency department.

OBJECTIVES: To identify the prevalence of domestic violence (DV) (defined as physical abuse perpetrated by intimate partners) in women attending an inner city accident and emergency department and to elicit women's response about being asked routinely about domestic violence in this setting. METHODS: 22 nursing shifts were purposefully sampled to be representative of day, night, and weekends. A questionnaire was administered to 198 consenting women who were not intoxicated, confused, or critically ill. RESULTS: The prevalence of acute trauma in women attributable to DV was 1% (95%CI 0.14 to 3.6), the prevalence of lifetime physical abuse was 34.8% (95%CI 28.2 to 41.5), of past year physical abuse was 6.1% (95%CI 3.2 to 10.3), and of lifetime life threatening physical abuse was 10.6% (95%CI 6.3 to 14.9). Seventy six per cent of women felt comfortable about being asked about DV and 60.5% of women felt that they should always or usually be asked about DV in this setting. CONCLUSION: This cross sectional survey adds to the body of knowledge showing that the prevalence of DV in women attending an accident and emergency department is high. Most women were in favour of being asked, and disclosure was associated with discomfort in few women. This sensitive area of history taking and referral could be undertaken by health professionals using a supportive approach

A novel approach to study realistic navigations on networks

We consider navigation or search schemes on networks which are realistic in the sense that not all search chains can be completed. We show that the quantity $\mu = \rho/s_d$, where $s_d$ is the average dynamic shortest distance and $\rho$ the success rate of completion of a search, is a consistent measure for the quality of a search strategy. Taking the example of realistic searches on scale-free networks, we find that $\mu$ scales with the system size $N$ as $N^{-\delta}$, where $\delta$ decreases as the searching strategy is improved. This measure is also shown to be sensitive to the distintinguishing characteristics of networks. In this new approach, a dynamic small world (DSW) effect is said to exist when $\delta \approx 0$. We show that such a DSW indeed exists in social networks in which the linking probability is dependent on social distances.Comment: Text revised, references added; accepted version in Journal of Statistical Mechanic

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

Spreading and shortest paths in systems with sparse long-range connections

Spreading according to simple rules (e.g. of fire or diseases), and shortest-path distances are studied on d-dimensional systems with a small density p per site of long-range connections (``Small-World'' lattices). The volume V(t) covered by the spreading quantity on an infinite system is exactly calculated in all dimensions. We find that V(t) grows initially as t^d/d for t>t^*$, generalizing a previous result in one dimension. Using the properties of V(t), the average shortest-path distance \ell(r) can be calculated as a function of Euclidean distance r. It is found that \ell(r) = r for r<r_c=(2p \Gamma_d (d-1)!)^{-1/d} log(2p \Gamma_d L^d), and \ell(r) = r_c for r>r_c. The characteristic length r_c, which governs the behavior of shortest-path lengths, diverges with system size for all p>0. Therefore the mean separation s \sim p^{-1/d} between shortcut-ends is not a relevant internal length-scale for shortest-path lengths. We notice however that the globally averaged shortest-path length, divided by L, is a function of L/s only.Comment: 4 pages, 1 eps fig. Uses psfi

Non-nequilibrium model on Apollonian networks

We investigate the Majority-Vote Model with two states ($-1,+1$) and a noise $q$ on Apollonian networks. The main result found here is the presence of the phase transition as a function of the noise parameter $q$. We also studies de effect of redirecting a fraction $p$ of the links of the network. By means of Monte Carlo simulations, we obtained the exponent ratio $\gamma/\nu$, $\beta/\nu$, and $1/\nu$ for several values of rewiring probability $p$. The critical noise was determined $q_{c}$ and $U^{*}$ also was calculated. The effective dimensionality of the system was observed to be independent on $p$, and the value $D_{eff} \approx1.0$ is observed for these networks. Previous results on the Ising model in Apollonian Networks have reported no presence of a phase transition. Therefore, the results present here demonstrate that the Majority-Vote Model belongs to a different universality class as the equilibrium Ising Model on Apollonian Network.Comment: 5 pages, 5 figure

Mountain trail formation and the active walker model

We extend the active walker model to address the formation of paths on gradients, which have been observed to have a zigzag form. Our extension includes a new rule which prohibits direct descent or ascent on steep inclines, simulating aversion to falling. Further augmentation of the model stops walkers from changing direction very rapidly as that would likely lead to a fall. The extended model predicts paths with qualitatively similar forms to the observed trails, but only if the terms suppressing sudden direction changes are included. The need to include terms into the model that stop rapid direction change when simulating mountain trails indicates that a similar rule should also be included in the standard active walker model.Comment: Introduction improved. Analysis of discretization errors added. Calculations from alternative scheme include

Magnetar oscillations pose challenges for strange stars

Compact relativistic stars allow us to study the nature of matter under extreme conditions, probing regions of parameter space that are otherwise inaccessible. Nuclear theory in this regime is not well constrained: one key issue is whether neutron stars are in fact composed primarily of strange quark matter. Distinguishing the two possibilities, however, has been difficult. The recent detection of seismic vibrations in the aftermath of giant flares from two magnetars (highly magnetized compact stars) is a major breakthrough. The oscillations excited seem likely to involve the stellar crust, the properties of which differ dramatically for strange stars. We show that the resulting mode frequencies cannot be reconciled with the observations for reasonable magnetar parameters. Ruling out strange star models would place a strong constraint on models of dense quark matter.Comment: Parameter space expanded, 5 pages, 3 figures, MNRAS Letters in pres

Characterization and control of small-world networks

Recently Watts and Strogatz have given an interesting model of small-world networks. Here we concretise the concept of a ``far away'' connection in a network by defining a {\it far edge}. Our definition is algorithmic and independent of underlying topology of the network. We show that it is possible to control spread of an epidemic by using the knowledge of far edges. We also suggest a model for better advertisement using the far edges. Our findings indicate that the number of far edges can be a good intrinsic parameter to characterize small-world phenomena.Comment: 9 pages and 6 figure

Analysis of Nonlinear Synchronization Dynamics of Oscillator Networks by Laplacian Spectral Methods

We analyze the synchronization dynamics of phase oscillators far from the synchronization manifold, including the onset of synchronization on scale-free networks with low and high clustering coefficients. We use normal coordinates and corresponding time-averaged velocities derived from the Laplacian matrix, which reflects the network's topology. In terms of these coordinates, synchronization manifests itself as a contraction of the dynamics onto progressively lower-dimensional submanifolds of phase space spanned by Laplacian eigenvectors with lower eigenvalues. Differences between high and low clustering networks can be correlated with features of the Laplacian spectrum. For example, the inhibition of full synchoronization at high clustering is associated with a group of low-lying modes that fail to lock even at strong coupling, while the advanced partial synchronizationat low coupling noted elsewhere is associated with high-eigenvalue modes.Comment: Revised version: References added, introduction rewritten, additional minor changes for clarit