Typification of farming systems for constructing representative farm models: two illustrations of the application of multi-variate analyses in Chile and Pakistan

If the fundamental precepts of Farming Systems Research were to be taken literally then it would imply that for each farm 'unique' solutions should be sought. This is an unrealistic expectation, but it has led to the idea of a recommendation domain, implying creating a taxonomy of farms, in order to increase the general applicability of recommendations. Mathematical programming models are an established means of generating recommended solutions, but for such models to be effective they have to be constructed for 'truly' typical or representative situations. The multi-variate statistical techniques provide a means of creating the required typologies, particularly when an exhaustive database is available. This paper illustrates the application of this methodology in two different studies that shared the common purpose of identifying types of farming systems in their respective study areas. The issues related with the use of factor and cluster analyses for farm typification prior to building representative mathematical programming models for Chile and Pakistan are highlighted. (C) 2003 Elsevier Science Ltd. All rights reserved.

Surface geometry of Cu{531}

We present a combined quantitative low-energy electron diffraction (LEED) and density-functional theory (DFT) study of the chiral Cu{531} surface. The surface shows large inward relaxations with respect to the bulk interlayer distance of the first two layers and a large expansion of the distance between the fourth and fifth layers. (The latter is the first layer having the same coordination as the Cu atoms in the bulk.) Additional calculations have been performed to study the likelihood of faceting by comparing surface energies of possible facet terminations. No overall significant reduction in energy with respect to planar {531} could be found for any of the tested combinations of facets, which is in agreement with the experimental findings.

The local adsorption geometry and electronic structure of alanine on Cu{110}

The adsorption of alanine on Cu {110} was studied by a combination of near edge X-ray absorption fine structure (NEXAFS) spectroscopy, X-ray photoelectron spectroscopy (XPS) and density functional theory (DFT). Large chemical shifts in the C 1s, N 1s, and O 1s XP spectra were found between the alanine multilayer and the chemisorbed and pseudo-(3 x 2) alaninate layers. From C, N, and O K-shell NEXAFS spectra the tilt angles of the carboxylate group (approximate to 26 degrees in plane with respect to [1 (1) over bar0] and approximate to 45 degrees out of plane) and the C-N bond angle with respect to [1 (1) over bar0] could be determined for the pseudo-(3 x 2) overlayer. Using this information three adsorption geometries could be eliminated from five p(3 x 2) structures which lead to almost identical heats of adsorption in the DFT calculations between 1.40 and 1.47 eV/molecule. Due to the small energy difference between the remaining two structures it is not unlikely that these coexist on the surface at room temperature. (c) 2006 Elsevier B.V. All rights reserved.

The adsorption geometry of sulphur on Ir{100}: a quantitative LEED study

A quantitative low energy electron diffraction (LEED) analysis has been performed for the p(2 x 2)-S and c(2 x 2)-S surface structures formed by exposing the (1 x 1) phase of Ir{100} to H2S at 750 K. S is found to adsorb on the fourfold hollow sites in both structures leading to Pendry R-factor values of 0.17 for the p(2 x 2)-S and 0.16 for the c(2 x 2)-S structures. The distances between S and the nearest and next-nearest Ir atoms were found to be similar in both structures: 2.36 +/- 0.01 angstrom and 3.33 +/- 0.01 angstrom, respectively. The buckling in the second substrate layer is consistent with other structural studies for S adsorption on fcc{100} transition metal surfaces: 0.09 angstrom for p(2 x 2)-S and 0.02 angstrom for c(2 x 2)-S structures. The (1 x 5) reconstruction, which is the most stable phase for clean Ir{100}, is completely lifted and a c(2 x 2)-S overlayer is formed after exposure to H,S at 300 K followed by annealing to 520 K. CO temperature-programmed desorption (TPD) experiments indicate that the major factor in the poisoning of Ir by S is site blocking. (c) 2005 Elsevier B.V. All rights reserved.

Key performance indicators (KPIs) and priority setting in using the multi-attribute approach for assessing sustainable intelligent buildings

The main objectives of this paper are to: firstly, identify key issues related to sustainable intelligent buildings (environmental, social, economic and technological factors); develop a conceptual model for the selection of the appropriate KPIs; secondly, test critically stakeholder's perceptions and values of selected KPIs intelligent buildings; and thirdly develop a new model for measuring the level of sustainability for sustainable intelligent buildings. This paper uses a consensus-based model (Sustainable Built Environment Tool- SuBETool), which is analysed using the analytical hierarchical process (AHP) for multi-criteria decision-making. The use of the multi-attribute model for priority setting in the sustainability assessment of intelligent buildings is introduced. The paper commences by reviewing the literature on sustainable intelligent buildings research and presents a pilot-study investigating the problems of complexity and subjectivity. This study is based upon a survey perceptions held by selected stakeholders and the value they attribute to selected KPIs. It is argued that the benefit of the new proposed model (SuBETool) is a ‘tool’ for ‘comparative’ rather than an absolute measurement. It has the potential to provide useful lessons from current sustainability assessment methods for strategic future of sustainable intelligent buildings in order to improve a building's performance and to deliver objective outcomes. Findings of this survey enrich the field of intelligent buildings in two ways. Firstly, it gives a detailed insight into the selection of sustainable building indicators, as well as their degree of importance. Secondly, it tesst critically stakeholder's perceptions and values of selected KPIs intelligent buildings. It is concluded that the priority levels for selected criteria is largely dependent on the integrated design team, which includes the client, architects, engineers and facilities managers.

Hitting emissions targets with (statistical) confidence in multi-instrument Emissions Trading Schemes

A means of assessing, monitoring and controlling aggregate emissions from multi-instrument Emissions Trading Schemes is proposed. The approach allows contributions from different instruments with different forms of emissions targets to be integrated. Where Emissions Trading Schemes are helping meet specific national targets, the approach allows the entry requirements of new participants to be calculated and set at a level that will achieve these targets. The approach is multi-levelled, and may be extended downwards to support pooling of participants within instruments, or upwards to embed Emissions Trading Schemes within a wider suite of policies and measures with hard and soft targets. Aggregate emissions from each instrument are treated stochastically. Emissions from the scheme as a whole are then the joint probability distribution formed by integrating the emissions from its instruments. Because a Bayesian approach is adopted, qualitative and semi-qualitative data from expert opinion can be used where quantitative data is not currently available, or is incomplete. This approach helps government retain sufficient control over emissions trading scheme targets to allow them to meet their emissions reduction obligations, while minimising the need for retrospectively adjusting existing participants’ conditions of entry. This maintains participant confidence, while providing the necessary policy levers for good governance.

Development of multi-electrode array screening for anticonvulsants in acute rat brain slices

The acute hippocampal brain slice preparation is an important in vitro screening tool for potential anticonvulsants. Application of 4-aminopyridine (4-AP) or removal of external Mg2+ ions induces epileptiform bursting in slices which is analogous to electrical brain activity seen in status epilepticus states. We have developed these epileptiform models for use with multi-electrode arrays (MEAs), allowing recording across the hippocampal slice surface from 59 points. We present validation of this novel approach and analyses using two anticonvulsants, felbamate and phenobarbital, the effects of which have already been assessed in these models using conventional extracellular recordings. In addition to assessing drug effects on commonly described parameters (duration, amplitude and frequency), we describe novel methods using the MEA to assess burst propagation speeds and the underlying frequencies that contribute to the epileptiform activity seen. Contour plots are also used as a method of illustrating burst activity. Finally, we describe hitherto unreported properties of epileptiform, bursting induced by 100 mu M 4-AP or removal of external Mg2+ ions. Specifically, we observed decreases over time in burst amplitude and increase over time in burst frequency in the absence of additional pharmacological interventions. These MEA methods enhance the depth, quality and range of data that can be derived from the hippocampal slice preparation compared to conventional extracellular recordings. it may also uncover additional modes of action that contribute to anti-epileptiform drug effects. (C) 2009 Elsevier B.V. All rights reserved.

A fuzzy multi-criteria decision approach for enhanced auto-tracking of seismic events

The main activity carried out by the geophysicist when interpreting seismic data, in terms of both importance and time spent is tracking (or picking) seismic events. in practice, this activity turns out to be rather challenging, particularly when the targeted event is interrupted by discontinuities such as geological faults or exhibits lateral changes in seismic character. In recent years, several automated schemes, known as auto-trackers, have been developed to assist the interpreter in this tedious and time-consuming task. The automatic tracking tool available in modem interpretation software packages often employs artificial neural networks (ANN's) to identify seismic picks belonging to target events through a pattern recognition process. The ability of ANNs to track horizons across discontinuities largely depends on how reliably data patterns characterise these horizons. While seismic attributes are commonly used to characterise amplitude peaks forming a seismic horizon, some researchers in the field claim that inherent seismic information is lost in the attribute extraction process and advocate instead the use of raw data (amplitude samples). This paper investigates the performance of ANNs using either characterisation methods, and demonstrates how the complementarity of both seismic attributes and raw data can be exploited in conjunction with other geological information in a fuzzy inference system (FIS) to achieve an enhanced auto-tracking performance.

The geometry of optimal control solutions on some six dimensional lie groups

This paper examines optimal solutions of control systems with drift defined on the orthonormal frame bundle of particular Riemannian manifolds of constant curvature. The manifolds considered here are the space forms Euclidean space E-3, the spheres S-3 and the hyperboloids H-3 with the corresponding frame bundles equal to the Euclidean group of motions SE(3), the rotation group SO(4) and the Lorentz group SO(1,3). The optimal controls of these systems are solved explicitly in terms of elliptic functions. In this paper, a geometric interpretation of the extremal solutions is given with particular emphasis to a singularity in the explicit solutions. Using a reduced form of the Casimir functions the geometry of these solutions are illustrated.

MTR: the multi-tasking rover - a new concept in rover design

In this paper we present the novel concepts incorporated in a planetary surface exploration rover design that is currently under development. The Multitasking Rover (MTR) aims to demonstrate functionality that will cover many of the current and future needs such as rough-terrain mobility, modularity and upgradeability. The rover system has enhanced mobility characteristics. It operates in conjunction with Science Packs (SPs) and Tool Packs (TPs)-modules attached to the main frame of the rover, which are either special tools or science instruments and alter the operation capabilities of the system.