Democratizing deliberative systems

'Deliberative democracy' is often dismissed as a set of small-scale, academic experiments. This volume seeks to demonstrate how the deliberative ideal can work as a theory of democracy on a larger scale. It provides a new way of thinking about democratic engagement across the spectrum of political action, from towns and villages to nation states, and from local networks to transnational, even global systems. Written by a team of the world's leading deliberative theorists, Deliberative Systems explains the principles of this new approach, which seeks ways of ensuring that a division of deliberative labour in a system nonetheless meets both deliberative and democratic norms. Rather than simply elaborating the theory, the contributors examine the problems of implementation in a real world of competing norms, competing institutions and competing powerful interests. This pioneering book will inspire an exciting new phase of deliberative research, both theoretical and empirical

Sensitivity of a climatologically-driven sea ice model to the ocean heat flux

Ocean heat flux sensitivity was studied on a numerical model of sea ice covering the Weddell Sea region of the southern ocean. The model is driven by mean monthly climatological atmospheric variables. For each model run, the ocean heat flux is uniform in both space and time. Ocean heat fluxes below 20 W m to the minus 2 power do not provide sufficient energy to allow the ice to melt to its summertime thicknesses and concentrations by the end of the 14 month simulation, whereas ocean heat fluxes of 30 W m to the minus 2 power and above result in too much ice melt, producing the almost total disappearance of ice in the Weddell Sea by the end of the 14 months. These results are dependent on the atmospheric forcing fields

Constraining the dark fluid

Cosmological observations are normally fit under the assumption that the dark sector can be decomposed into dark matter and dark energy components. However, as long as the probes remain purely gravitational, there is no unique decomposition and observations can only constrain a single dark fluid; this is known as the dark degeneracy. We use observations to directly constrain this dark fluid in a model-independent way, demonstrating in particular that the data cannot be fit by a dark fluid with a single constant equation of state. Parameterizing the dark fluid equation of state by a variety of polynomials in the scale factor $a$, we use current kinematical data to constrain the parameters. While the simplest interpretation of the dark fluid remains that it is comprised of separate dark matter and cosmological constant contributions, our results cover other model types including unified dark energy/matter scenarios.Comment: 5 pages, 5 figures incorporated. Updated to new observational data including SHOES determination of H0; new citations adde

Unified dark energy and dark matter from a scalar field different from quintessence

We explore unification of dark matter and dark energy in a theory containing a scalar field of non-Lagrangian type, obtained by direct insertion of a kinetic term into the energy-momentum tensor. This scalar is different from quintessence, having an equation of state between -1 and 0 and a zero sound speed in its rest frame. We solve the equations of motion for an exponential potential via a rewriting as an autonomous system, and demonstrate the observational viability of the scenario, for sufficiently small exponential potential parameter \lambda, by comparison to a compilation of kinematical cosmological data.Comment: 10 pages RevTeX4 with 5 figures incorporate

Reconstructing thawing quintessence with multiple datasets

In this work we model the quintessence potential in a Taylor series expansion, up to second order, around the present-day value of the scalar field. The field is evolved in a thawing regime assuming zero initial velocity. We use the latest data from the Planck satellite, baryonic acoustic oscillations observations from the Sloan Digital Sky Survey, and Supernovae luminosity distance information from Union2.1 to constrain our models parameters, and also include perturbation growth data from the WiggleZ, BOSS and the 6dF surveys. The supernova data provide the strongest individual constraint on the potential parameters. We show that the growth data performance is competitive with the other datasets in constraining the dark energy parameters we introduce. We also conclude that the combined constraints we obtain for our model parameters, when compared to previous works of nearly a decade ago, have shown only modest improvement, even with new growth of structure data added to previously-existent types of data.Comment: 9 pages, 4 figures and 1 table. Version 2 with minor changes to match Physical Review D accepted versio

Diisopropylamide and TMP turbo-grignard reagents : a structural rationale for their contrasting reactivities

A neutral dimeric molecule in crystal form, the diisopropylamido turbo-Grignard reagent "(iPr2N)MgCl⋅LiCl" (see structure; blue N, red O, green Mg, yellow Cl, black C) separates into several charged ate species in dynamic exchange with each other in THF solution as determined by a combination of EXSY and DOSY NMR studies

Optimizing future dark energy surveys for model selection goals

We demonstrate a methodology for optimizing the ability of future dark energy surveys to answer model selection questions, such as `Is acceleration due to a cosmological constant or a dynamical dark energy model?'. Model selection Figures of Merit are defined, exploiting the Bayes factor, and surveys optimized over their design parameter space via a Monte Carlo method. As a specific example we apply our methods to generic multi-fibre baryon acoustic oscillation spectroscopic surveys, comparable to that proposed for SuMIRe PFS, and present implementations based on the Savage-Dickey Density Ratio that are both accurate and practical for use in optimization. It is shown that whilst the optimal surveys using model selection agree with those found using the Dark Energy Task Force (DETF) Figure of Merit, they provide better informed flexibility of survey configuration and an absolute scale for performance; for example, we find survey configurations with close to optimal model selection performance despite their corresponding DETF Figure of Merit being at only 50% of its maximum. This Bayes factor approach allows us to interpret the survey configurations that will be good enough for the task at hand, vital especially when wanting to add extra science goals and in dealing with time restrictions or multiple probes within the same project.Comment: 12 pages, 16 figure