Cassini detection of Enceladus' cold water-group plume ionosphere

This study reports direct detection by the Cassini plasma spectrometer of freshly-produced water-group ions (O+, OH+, H2O+, H3O+) and heavier water dimer ions (HxO(2))(+) very close to Enceladus where the plasma begins to emerge from the plume. The data were obtained during two close ( 52 and 25 km) flybys of Enceladus in 2008 and are similar to ion data in cometary comas. The ions are observed in detectors looking in the Cassini ram direction exhibiting energies consistent with the Cassini speed, indicative of a nearly stagnant plasma flow in the plume. North of Enceladus the plasma slowing commences about 4 to 6 Enceladus radii away, while south of Enceladus signatures of the plasma interaction with the plume are detected 22 Enceladus radii away. Citation: Tokar, R. L., R. E. Johnson, M. F. Thomsen, R. J. Wilson, D. T. Young, F. J. Crary, A. J. Coates, G. H. Jones, and C. S. Paty ( 2009), Cassini detection of Enceladus' cold water-group plume ionosphere, Geophys. Res. Lett., 36, L13203, doi:10.1029/2009GL038923

Finite-size and correlation-induced effects in Mean-field Dynamics

The brain's activity is characterized by the interaction of a very large number of neurons that are strongly affected by noise. However, signals often arise at macroscopic scales integrating the effect of many neurons into a reliable pattern of activity. In order to study such large neuronal assemblies, one is often led to derive mean-field limits summarizing the effect of the interaction of a large number of neurons into an effective signal. Classical mean-field approaches consider the evolution of a deterministic variable, the mean activity, thus neglecting the stochastic nature of neural behavior. In this article, we build upon two recent approaches that include correlations and higher order moments in mean-field equations, and study how these stochastic effects influence the solutions of the mean-field equations, both in the limit of an infinite number of neurons and for large yet finite networks. We introduce a new model, the infinite model, which arises from both equations by a rescaling of the variables and, which is invertible for finite-size networks, and hence, provides equivalent equations to those previously derived models. The study of this model allows us to understand qualitative behavior of such large-scale networks. We show that, though the solutions of the deterministic mean-field equation constitute uncorrelated solutions of the new mean-field equations, the stability properties of limit cycles are modified by the presence of correlations, and additional non-trivial behaviors including periodic orbits appear when there were none in the mean field. The origin of all these behaviors is then explored in finite-size networks where interesting mesoscopic scale effects appear. This study leads us to show that the infinite-size system appears as a singular limit of the network equations, and for any finite network, the system will differ from the infinite system

Inter-rater reliability of the Dysexecutive Questionnaire (DEX): comparative data from non-clinician respondents – all raters are not equal

Primary objective: The Dysexecutive Questionnaire (DEX) is used to obtain information about executive and emotional problems after neuropathology. The DEX is self-completed by the patient (DEX-S) and an independent rater such as a family member (DEX-I). This study examined the level of inter-rater agreement between either two or three non-clinician raters on the DEX-I in order to establish the reliability of DEX-I ratings. Methods and procedures: Family members and/or carers of 60 people with mixed neuropathology completed the DEX-I. For each patient, DEX-I ratings were obtained from either two or three raters who knew the person well prior to brain injury. Main outcomes and results: We obtained two independent-ratings for 60 patients and three independent-ratings for 36 patients. Intra-class correlations revealed that there was only a modest level of agreement for items, subscale and total DEX scores between raters for their particular family member. Several individual DEX items had low reliability and ratings for the emotion sub-scale had the lowest level of agreement. Conclusions: Independent DEX ratings completed by two or more non-clinician raters show only moderate correlation. Suggestions are made for improving the reliability of DEX-I ratings.</p

Experiences of challenges and support among family members of people with acquired brain injury: a qualitative study in the UK

Primary objective: Family members (FM) are affected by the impact of an Acquired Brain Injury (ABI) upon their relatives and play an important role in rehabilitation and long-term support. This study explores how families are affected and integrates their views on the formal/informal support received as a consequence of ABI. Research design: A qualitative research design was employed to capture the lived experience of FM of people with ABI. Method: Semi-structured interviews were conducted with 16 FM of people with severe ABI. Participants were chosen from respondents to a UK national online survey of affected individuals. Interview data were analysed using inductive thematic analysis. Results: Family members’ experiences are complex, enduring and are affected by the context in which the ABI occurs as well as by formal/informal support. The grief experienced by FM is ambiguous, develops over time and FM perceive little option but to remain involved. Experience of formal and informal support is noted to vary significantly in availability and quality, poor support exacerbates difficulties and isolates family members. Conclusion: Greater understanding of the lived experience of FM is needed to support more effective responses to both them and the individual with ABI, integrating services and families to improve quality-of-life

Bayesian design and analysis of external pilot trials for complex interventions

External pilot trials of complex interventions are used to help determine if and how a confirmatory trial should be undertaken, providing estimates of parameters such as recruitment, retention, and adherence rates. The decision to progress to the confirmatory trial is typically made by comparing these estimates to pre‐specified thresholds known as progression criteria, although the statistical properties of such decision rules are rarely assessed. Such assessment is complicated by several methodological challenges, including the simultaneous evaluation of multiple endpoints, complex multi‐level models, small sample sizes, and uncertainty in nuisance parameters. In response to these challenges, we describe a Bayesian approach to the design and analysis of external pilot trials. We show how progression decisions can be made by minimizing the expected value of a loss function, defined over the whole parameter space to allow for preferences and trade‐offs between multiple parameters to be articulated and used in the decision‐making process. The assessment of preferences is kept feasible by using a piecewise constant parametrization of the loss function, the parameters of which are chosen at the design stage to lead to desirable operating characteristics. We describe a flexible, yet computationally intensive, nested Monte Carlo algorithm for estimating operating characteristics. The method is used to revisit the design of an external pilot trial of a complex intervention designed to increase the physical activity of care home residents

Efficient and flexible simulation-based sample size determination for clinical trials with multiple design parameters

Simulation offers a simple and flexible way to estimate the power of a clinical trial when analytic formulae are not available. The computational burden of using simulation has, however, restricted its application to only the simplest of sample size determination problems, often minimising a single parameter (the overall sample size) subject to power being above a target level. We describe a general framework for solving simulation-based sample size determination problems with several design parameters over which to optimise and several conflicting criteria to be minimised. The method is based on an established global optimisation algorithm widely used in the design and analysis of computer experiments, using a non-parametric regression model as an approximation of the true underlying power function. The method is flexible, can be used for almost any problem for which power can be estimated using simulation, and can be implemented using existing statistical software packages. We illustrate its application to a sample size determination problem involving complex clustering structures, two primary endpoints and small sample considerations

Mixed RG Flows and Hydrodynamics at Finite Holographic Screen

We consider quark-gluon plasma with chemical potential and study renormalization group flows of transport coefficients in the framework of gauge/gravity duality. We first study them using the flow equations and compare the results with hydrodynamic results by calculating the Green functions on the arbitrary slice. Two results match exactly. Transport coefficients at arbitrary scale is ontained by calculating hydrodynamics Green functions. When either momentum or charge vanishes, transport coefficients decouple from each other.Comment: 22 pages, 6 figure

Immunological characterization of chromogranins A and B and secretogranin II in the bovine pancreatic islet

Antisera against chromogranin A and B and secretogranin II were used for analysing the bovine pancreas by immunoblotting and immunohistochemistry. All three antigens were found in extracts of fetal pancreas by one dimensional immunoblotting. A comparison with the soluble proteins of chromaffin granules revealed that in adrenal medulla and in pancreas antigens which migrated identically in electrophoresis were present. In immunohistochemistry, chromogranin A was found in all pancreatic endocrine cell types with the exception of most pancreatic polypeptide-(PP-) producing cells. For chromogranin B, only a faint immunostaining was obtained. For secretorgranin II, A-and B-cells were faintly positive, whereas the majority of PP-cells exhibited a strong immunostaining for this antigen. These results establish that chromogranins A and B and secretogranin II are present in the endocrine pancreas, but that they exhibit a distinct cellular localization