GDASH: a grid-enabled program for structure solution from powder diffraction data

The simulated annealing approach to structure solution from powder diffraction data, as implemented in the DASH program, is easily amenable to parallelization at the individual run level. Very large scale increases in speed of execution can therefore be achieved by distributing individual DASH runs over a network of computers. The GDASH program achieves this by packaging DASH in a form that enables it to run under the Univa UD Grid MP system, which harnesses networks of existing computing resources to perform calculations.

Observed atmospheric electricity effect on clouds

The atmosphere's fair weather electric field is a permanent feature, arising from the combination of distant thunderstorms, Earth's conducting surface, a charged ionosphere and cosmic ray ionization. Despite its ubiquity, no fair weather electricity effect on clouds has been hitherto demonstrated. Here we report surface measurements of radiation emitted and scattered by extensive thin continental cloud, which, after ~2 min delay, shows changes closely following the fair weather electric field. For typical fluctuations in the fair weather electric field, changes of about 10% are subsequently induced in the diffuse short-wave radiation. These observations are consistent with enhanced production of large cloud droplets from charging at layer cloud edges.

Post-neoliberal electricity market ‘re-reforms’ in Argentina: Diverging from market prescriptions?

This paper focuses upon the policy and institutional change that has taken place within the Argentine electricity market since the country’s economic and social crisis of 2001/2. As one of the first less developed countries (LDCs) to liberalise and privatise its electricity industry, Argentina has since moved away from the orthodox market model after consumer prices were frozen by the Government in early 2002 when the national currency was devalued by 70%. Although its reforms were widely praised during the 1990s, the electricity market has undergone a number of interventions, ostensibly to keep consumer prices low and to avert the much-discussed energy ‘crisis’ caused by a dearth of new investment combined with rising demand levels. This paper explores how the economic crisis and its consequences have both enabled and legitimised these policy and institutional amendments, while drawing upon the specifics of the post-neoliberal market ‘re-reforms’ to consider the extent to which the Government appears to be moving away from market-based prescriptions. In addition, this paper contributes to sector-specific understandings of how, despite these changes, neoliberal ideas and assumptions continue to dominate Argentine public policy well beyond the postcrisis era.

Illustration of micro-scale advection using grid-pattern mini-lysimeters

Twenty-five small soil-filled perspex boxes arranged in a square, with dwarf sunflowers growing in them, were used to study micro-scale advection. Hydrological heterogeneity was introduced by applying two different amounts of irrigation water (low-irrigation, L, versus high-irrigation, H). The nine central boxes (4 H, 4 L and I bare box) were precision weighing lysimeters, yielding diurnal measurements of evaporation. After the onset of soil water stress, a large difference in latent heat flux (up to 4-fold) was observed between the lysimeters of the H and L treatments, mainly caused by large differences between H and L stomatal conductance values. This resulted in micro-advection, causing H soil-sunflower systems to evaporate well above equilibrium latent heat flux. The occurrence of micro-advective enhancement was reflected in large values of the Priestley-Taylor constant (often larger than 2.0) and generally negative values of sensible heat flux for the H treatment. (c) 2005 Elsevier B.V. All rights reserved.

The seasonal forecast of electricity demand: A hierarchical Bayesian model with climatological weather generator

In this paper we focus on the one year ahead prediction of the electricity peak-demand daily trajectory during the winter season in Central England and Wales. We define a Bayesian hierarchical model for predicting the winter trajectories and present results based on the past observed weather. Thanks to the flexibility of the Bayesian approach, we are able to produce the marginal posterior distributions of all the predictands of interest. This is a fundamental progress with respect to the classical methods. The results are encouraging in both skill and representation of uncertainty. Further extensions are straightforward at least in principle. The main two of those consist in conditioning the weather generator model with respect to additional information like the knowledge of the first part of the winter and/or the seasonal weather forecast. Copyright (C) 2006 John Wiley & Sons, Ltd.