Electron optical and X-ray powder diffraction study of synthetic and natural potassic cordierites

The microstructural and X-ray diffraction characteristics of natural K-bearing cordierites in buchites (Blaue Kuppe, Germany), and paralavas (Bokaro, India) are compared to those of three suites of synthetic, K-bearing Mg-cordierite, studied after annealing glasses of the requisite compositions for durations between 5 min and 255 days at 1,290° C and 1 bar. In analogy to pure Mg-cordierite, hexagonal high-cordierite initially crystallizes from the glass and subsequently transforms to orthorhombic low-cordierite. After annealing for 30–60 min, the crystals develop tweed-structure. With prolonged annealing, the pattern coarsens and develops into lamellar twinning. Higher K-contents favour earlier development of tweed-contrast. Distortion indices obtained by X-ray powder diffraction show a sharp initial increase of with annealing time, followed by a levelling off after approximately 10 h. Higher K-contents delay this initial increase, and decrease drastically the maximum distortion index that can be attained. The contrasting observations with respect to increasing K-content are due to the different levels of information yielded by TEM and X-ray diffraction. Analyses of electron diffraction patterns indicate that the metric state of individual crystals in any single sample annealed for more than one hour is highly heterogeneous, while no compositional differences could be detected. Hexagonal and variously distored crystals coexist. Thus intermediate structural states of cordierite in the classical sense are shown to exist, although intermediate distortion indices obtained by routine X-ray powder diffraction are largely due to a summation effect over such structurally heterogeneous populations. Although distinct differences in microstructure between the synthetic and the natural Fe²⁺-bearing cordierites exist, the Bokaro samples most closely resemble the early (1–10 h) tweed-structure of the synthetic products, whereas the Blaue Kuppe samples are comparable to a more mature (1–3 days) stage. It is thus concluded that the cordierite-bearing Bokaro paralavas cooled considerably faster than the Blaue Kuppe buchites.     

Learning to trade ethically: Knowledgeable capitalism, retailers and contested commodity chains

This paper explores what happens when corporations engage explicitly in practices of organisational learning not only to become better capitalists by generating ever more innovative ways of maintaining profitability, improving competitiveness and maximising shareholder value, but also to become more responsible corporate citizens in their business practices. In particular, I evaluate the ways in which UK food and clothing retailers are learning to develop their ethical trading programmes in response to political calls for more responsible trading. Thrift’s [Thrift, N., 2005. Knowing Capitalism. Sage, London] notion of ‘knowledgeable, or soft, capitalism’ is adopted to understand the creative and experimental ways in which retailers and their mentors (ethical consultancies, social auditors and multi-stakeholder organisations) are learning to trade ethically. Two specific examples of formal learning spaces experienced by UK food and clothing retailers are examined: (i) training courses on social auditing and (ii) corporate awareness-raising courses on ethical trade. These courses are shown to encompass various participative and affective practices of learning. And while particular limits to the success of these courses are argued to exist, ethical learning practices discussed in this paper are nonetheless suggested to play a role in the making of new, albeit moderate, forms of responsible capitalism.     

Hyper Redundancy for Accuracy Enhancement in Automated Close Range Photogrammetry

A generic network design in close range photogrammetry is one where optimal multi-ray intersection geometry is obtained with as few camera stations as practicable. Hyper redundancy is a concept whereby, once the generic network is in place, many additional images are recorded, with the beneficial impact upon object point precision being equivalent to the presence of multiple exposures at each camera position within the generic network. The effective number of images per station within a hyper redundant network might well be in the range of 10 to 20 or more. As is apparent when it is considered that a hyper redundant network may comprise hundreds of images, the concept is only applicable in practice to fully automatic vision metrology systems, where it proves to be a very effective means of enhancing measurement accuracy at the cost of minimal additional work in the image recording phase. This paper briefly reviews the network design and accuracy aspects of hyper redundancy and illustrates the technique by way of the photogrammetric measurement of surface deformation of a radio telescope of 26 m diameter. This project required an object point measurement accuracy of σ  = 0·065 mm, or 1/400 000 of the diameter of the reflector.     

UK seismology – 2002 and beyond

Alex Brisbourne reports on a one-day discussion meeting organized by SEIS-UK for seismologists to discuss current seismological research undertaken in the UK and to consider how the provision of new seismic equipment and training facility may enhance that work.     

Comparison of statistically downscaled precipitation in terms of future climate indices and daily variability for southern Ontario and Quebec,Canada

Given the coarse resolution of global climate models, downscaling techniques are often needed to generate finer scale projections of variables affected by local-scale processes such as precipitation. However, classical statistical downscaling experiments for future climate rely on the time-invariance assumption as one cannot know the true change in the variable of interest, nor validate the models with data not yet observed. Our experimental setup involves using the Canadian regional climate model (CRCM) outputs as pseudo-observations to estimate model performance in the context of future climate projections by replacing historical and future observations with model simulations from the CRCM, nested within the domain of the Canadian global climate model (CGCM). In particular, we evaluated statistically downscaled daily precipitation time series in terms of the Peirce skill score, mean absolute errors, and climate indices. Specifically, we used a variety of linear and nonlinear methods such as artificial neural networks (ANN), decision trees and ensembles, multiple linear regression, and k-nearest neighbors to generate present and future daily precipitation occurrences and amounts. We obtained the predictors from the CGCM 3.1 20C3M (1971–2000) and A2 (2041–2070) simulations, and precipitation outputs from the CRCM 4.2 (forced with the CGCM 3.1 boundary conditions) as predictands. Overall, ANN models and tree ensembles outscored the linear models and simple nonlinear models in terms of precipitation occurrences, without performance deteriorating in future climate. In contrast, for the precipitation amounts and related climate indices, the performance of downscaling models deteriorated in future climate.