1,592 research outputs found

    Effectiveness of a social support intervention on infant feeding practices : randomised controlled trial

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    Background: To assess whether monthly home visits from trained volunteers could improve infant feeding practices at age 12 months, a randomised controlled trial was carried out in two disadvantaged inner city London boroughs. Methods: Women attending baby clinics with their infants (312) were randomised to receive monthly home visits from trained volunteers over a 9-month period (intervention group) or standard professional care only (control group). The primary outcome was vitamin C intakes from fruit. Secondary outcomes included selected macro and micro-nutrients, infant feeding habits, supine length and weight. Data were collected at baseline when infants were aged approximately 10 weeks, and subsequently when the child was 12 and 18 months old. Results: Two-hundred and twelve women (68%) completed the trial. At both follow-up points no significant differences were found between the groups for vitamin C intakes from fruit or other nutrients. At first follow-up, however, infants in the intervention group were significantly less likely to be given goats’ or soya milks, and were more likely to have three solid meals per day. At the second follow-up, intervention group children were significantly less likely to be still using a bottle. At both follow-up points, intervention group children also consumed significantly more specific fruit and vegetables. Conclusions: Home visits from trained volunteers had no significant effect on nutrient intakes but did promote some other recommended infant feeding practices

    Combined single-molecule force and fluorescence measurements for biology

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    Recent advances in single-molecule techniques allow the application of force to an individual biomolecule whilst simultaneously monitoring its response using fluorescent probes. The effects of applied mechanical load on single-enzyme turnovers, biomolecular interactions and conformational changes can now be studied with nanometer precision and millisecond time resolution

    Self-avoiding walks on scale-free networks

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    Several kinds of walks on complex networks are currently used to analyze search and navigation in different systems. Many analytical and computational results are known for random walks on such networks. Self-avoiding walks (SAWs) are expected to be more suitable than unrestricted random walks to explore various kinds of real-life networks. Here we study long-range properties of random SAWs on scale-free networks, characterized by a degree distribution P(k)kγP(k) \sim k^{-\gamma}. In the limit of large networks (system size NN \to \infty), the average number sns_n of SAWs starting from a generic site increases as μn\mu^n, with μ=/1\mu = / - 1. For finite NN, sns_n is reduced due to the presence of loops in the network, which causes the emergence of attrition of the paths. For kinetic growth walks, the average maximum length, , increases as a power of the system size: Nα \sim N^{\alpha}, with an exponent α\alpha increasing as the parameter γ\gamma is raised. We discuss the dependence of α\alpha on the minimum allowed degree in the network. A similar power-law dependence is found for the mean self-intersection length of non-reversal random walks. Simulation results support our approximate analytical calculations.Comment: 9 pages, 7 figure

    The entropy of randomized network ensembles

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    Randomized network ensembles are the null models of real networks and are extensivelly used to compare a real system to a null hypothesis. In this paper we study network ensembles with the same degree distribution, the same degree-correlations or the same community structure of any given real network. We characterize these randomized network ensembles by their entropy, i.e. the normalized logarithm of the total number of networks which are part of these ensembles. We estimate the entropy of randomized ensembles starting from a large set of real directed and undirected networks. We propose entropy as an indicator to assess the role of each structural feature in a given real network.We observe that the ensembles with fixed scale-free degree distribution have smaller entropy than the ensembles with homogeneous degree distribution indicating a higher level of order in scale-free networks.Comment: (6 pages,1 figure,2 tables

    Percolation in invariant Poisson graphs with i.i.d. degrees

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    Let each point of a homogeneous Poisson process in R^d independently be equipped with a random number of stubs (half-edges) according to a given probability distribution mu on the positive integers. We consider translation-invariant schemes for perfectly matching the stubs to obtain a simple graph with degree distribution mu. Leaving aside degenerate cases, we prove that for any mu there exist schemes that give only finite components as well as schemes that give infinite components. For a particular matching scheme that is a natural extension of Gale-Shapley stable marriage, we give sufficient conditions on mu for the absence and presence of infinite components

    Evolution of scale-free random graphs: Potts model formulation

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    We study the bond percolation problem in random graphs of NN weighted vertices, where each vertex ii has a prescribed weight PiP_i and an edge can connect vertices ii and jj with rate PiPjP_iP_j. The problem is solved by the q1q\to 1 limit of the qq-state Potts model with inhomogeneous interactions for all pairs of spins. We apply this approach to the static model having Piiμ(0<μ<1)P_i\propto i^{-\mu} (0<\mu<1) so that the resulting graph is scale-free with the degree exponent λ=1+1/μ\lambda=1+1/\mu. The number of loops as well as the giant cluster size and the mean cluster size are obtained in the thermodynamic limit as a function of the edge density, and their associated critical exponents are also obtained. Finite-size scaling behaviors are derived using the largest cluster size in the critical regime, which is calculated from the cluster size distribution, and checked against numerical simulation results. We find that the process of forming the giant cluster is qualitatively different between the cases of λ>3\lambda >3 and 2<λ<32 < \lambda <3. While for the former, the giant cluster forms abruptly at the percolation transition, for the latter, however, the formation of the giant cluster is gradual and the mean cluster size for finite NN shows double peaks.Comment: 34 pages, 9 figures, elsart.cls, final version appeared in NP

    The Kerry Babies, criminology, and Reinhart Koselleck

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    The Kerry Babies case was a criminal investigation that followed the discovery of a dead infant on a beach in the southwest of Ireland in April 1984. Charges were laid and dismissed. A tribunal of inquiry into alleged police malpractice followed, and the case returned to the courts 35 years later. This paper takes a multidimensional approach to historical time, drawing on the works of German philosopher Reinhart Koselleck to analyse the case, its legacy, and its implications for criminological theory. A Koselleckian approach – drawing in particular on the role of anachronisms, the mobilisation of memory and the categories of experience and expectation – facilitates a novel perspective on child killing, unmarried motherhood, and policing in 20th-century Ireland
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