35 resultados para Katz, Jay


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Background:  Some contend that attachment insecurity increases risk for the development of externalizing behavior problems in children. Method:  Latent-growth curve analyses were applied to data on 1,364 children from the NICHD Study of Early Child Care to evaluate the association between early attachment and teacher-rated externalizing problems across the primary-school years. Results:  Findings indicate that (a) both avoidant and disorganized attachment predict higher levels of externalizing problems but (b) that effects of disorganized attachment are moderated by family cumulative contextual risk, child gender and child age, with disorganized boys from risky social contexts manifesting increases in behavior problems over time. Conclusions:  These findings highlight the potentially conditional role of early attachment in children’s externalizing behavior problems and the need for further research evaluating causation and mediating mechanisms.

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Variational data assimilation systems for numerical weather prediction rely on a transformation of model variables to a set of control variables that are assumed to be uncorrelated. Most implementations of this transformation are based on the assumption that the balanced part of the flow can be represented by the vorticity. However, this assumption is likely to break down in dynamical regimes characterized by low Burger number. It has recently been proposed that a variable transformation based on potential vorticity should lead to control variables that are uncorrelated over a wider range of regimes. In this paper we test the assumption that a transform based on vorticity and one based on potential vorticity produce an uncorrelated set of control variables. Using a shallow-water model we calculate the correlations between the transformed variables in the different methods. We show that the control variables resulting from a vorticity-based transformation may retain large correlations in some dynamical regimes, whereas a potential vorticity based transformation successfully produces a set of uncorrelated control variables. Calculations of spatial correlations show that the benefit of the potential vorticity transformation is linked to its ability to capture more accurately the balanced component of the flow.

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Objective: The objective of this study was to explore the relationship between low density lipoprotein (LDL) and dendritic cell (DC) activation, based upon the hypothesis that reactive oxygen species (ROS)-mediated modification of proteins that may be present in local DC microenvironments could be important as mediators of this activation. Although LDL are known to be oxidised in vivo, and taken up by macrophages during atherogenesis; their effect on DC has not been explored previously. Methods: Human DCs were prepared from peripheral blood monocytes using GM-CSF and IL-4. Plasma LDLs were isolated by sequential gradient centrifugation, oxidised in CuSO4, and oxidation arrested to yield mild, moderate and highly oxidised LDL forms. DCs exposed to these LDLs were investigated using combined phenotypic, functional (autologous T cell activation), morphological and viability assays. Results: Highly-oxidised LDL increased DC HLA-DR, CD40 and CD86 expression, corroborated by increased DC-induced T cell proliferation. Both native and oxidised LDL induced prominent DC clustering. However, high concentrations of highly-oxidised LDL inhibited DC function, due to increased DC apoptosis. Conclusions: This study supports the hypothesis that oxidised LDL are capable of triggering the transition from sentinel to messenger DC. Furthermore, the DC clustering–activation–apoptosis sequence in the presence of different LDL forms is consistent with a regulatory DC role in immunopathogenesis of atheroma. A sequence of initial accumulation of DC, increasing LDL oxidation, and DC-induced T cell activation, may explain why local breach of tolerance can occur. Above a threshold level, however, supervening DC apoptosis limits this, contributing instead to the central plaque core.

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We propose a new algorithm for summarizing properties of large-scale time-evolving networks. This type of data, recording connections that come and go over time, is being generated in many modern applications, including telecommunications and on-line human social behavior. The algorithm computes a dynamic measure of how well pairs of nodes can communicate by taking account of routes through the network that respect the arrow of time. We take the conventional approach of downweighting for length (messages become corrupted as they are passed along) and add the novel feature of downweighting for age (messages go out of date). This allows us to generalize widely used Katz-style centrality measures that have proved popular in network science to the case of dynamic networks sampled at non-uniform points in time. We illustrate the new approach on synthetic and real data.

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We explore the influence of the choice of attenuation factor on Katz centrality indices for evolving communication networks. For given snapshots of a network observed over a period of time, recently developed communicability indices aim to identify best broadcasters and listeners in the network. In this article, we looked into the sensitivity of communicability indices on the attenuation factor constraint, in relation to spectral radius (the largest eigenvalue) of the network at any point in time and its computation in the case of large networks. We proposed relaxed communicability measures where the spectral radius bound on attenuation factor is relaxed and the adjacency matrix is normalised in order to maintain the convergence of the measure. Using a vitality based measure of both standard and relaxed communicability indices we looked at the ways of establishing the most important individuals for broadcasting and receiving of messages related to community bridging roles. We illustrated our findings with two examples of real-life networks, MIT reality mining data set of daily communications between 106 individuals during one year and UK Twitter mentions network, direct messages on Twitter between 12.4k individuals during one week.

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We describe the approach to be adopted for a major new initiative to derive a homogeneous record of sea surface temperature for 1991–2007 from the observations of the series of three along-track scanning radiometers (ATSRs). This initiative is called (A)RC: (Advanced) ATSR Re-analysis for Climate. The main objectives are to reduce regional biases in retrieved sea surface temperature (SST) to less than 0.1 K for all global oceans, while creating a very homogenous record that is stable in time to within 0.05 K decade−1, with maximum independence of the record from existing analyses of SST used in climate change research. If these stringent targets are achieved, this record will enable significantly improved estimates of surface temperature trends and variability of sufficient quality to advance questions of climate change attribution, climate sensitivity and historical reconstruction of surface temperature changes. The approach includes development of new, consistent estimators for SST for each of the ATSRs, and detailed analysis of overlap periods. Novel aspects of the approach include generation of multiple versions of the record using alternative channel sets and cloud detection techniques, to assess for the first time the effect of such choices. There will be extensive effort in quality control, validation and analysis of the impact on climate SST data sets. Evidence for the plausibility of the 0.1 K target for systematic error is reviewed, as is the need for alternative cloud screening methods in this context.