The spectrum of minimal defining sets of some Steiner systems

For a design D, define spec(D) = {\M\ \ M is a minimal defining set of D} to be the spectrum of minimal defining sets of D. In this note we give bounds on the size of an element in spec(D) when D is a Steiner system. We also show that the spectrum of minimal defining sets of the Steiner triple system given by the points and lines of PG(3,2) equals {16,17,18,19,20,21,22}, and point out some open questions concerning the Steiner triple systems associated with PG(n, 2) in general. (C) 2002 Elsevier Science B.V. All rights reserved.

Skolem-type difference sets for cycle systems

Cyclic m-cycle systems of order v are constructed for all m greater than or equal to 3, and all v = 1(mod 2m). This result has been settled previously by several authors. In this paper, we provide a different solution, as a consequence of a more general result, which handles all cases using similar methods and which also allows us to prove necessary and sufficient conditions for the existence of a cyclic m-cycle system of K-v - F for all m greater than or equal to 3, and all v = 2(mod 2m).

Oxide ionic conductivity and microstructures of Sm- or La-doped CeO2-based systems

The concept of crystallographic index termed the effective index is suggested and applied to the design of ceria (CeO2)-based electrolytes to maximize oxide ionic conductivity. The suggested index considers the fluorite structure, and combines the expected oxygen vacancy level with the ionic radius mismatch between host and dopant cations. Using this approach, oxide ionic conductivity of Sm- or La-doped CeO2-based system has been optimized and tested under operating conditions of a solid oxide fuel cell. In the observation of microstructure in atomic scale, both Sm-doped CeO2 and La-doped CeO2 electrolytes had large micro-domains over 10 nm in the lattice. On the other hand, Sm or La and alkaline earth co-doped CeO2-based electrolytes with high effective index had small micro-domains around 1-3 nm in the microstructure. The large micro-domain would prevent oxide ion from passing through the lattice. Therefore, it is concluded that the improvement of ionic conductivity is reflected in changes of microstructure in atomic scale. (C) 2002 Elsevier Science B.V. All rights reserved.

Low input tillage/cropping systems for limited resource areas

Agriculture in limited resource areas is characterized by small farms which an generally too small to adequately support the needs of an average farm family. The farming operation can be described as a low input cropping system with the main energy source being manual labor, draught animals and in some areas hand tractors. These farming systems are the most important contributor to the national economy of many developing countries. The role of tillage is similar in dryland agricultural systems in both the high input (HICS) and low input cropping systems (LICS), however, wet cultivation or puddling is unique to lowland rice-based systems in low input cropping systems. Evidence suggest that tillage may result in marginal increases in crop yield in the short term, however, in the longer term it may be neutral or give rise to yield decreases associated with soil structural degradation. On marginal soils, tillage may be required to prepare suitable seedbeds or to release adequate Nitrogen through mineralization, but in the longer term, however, tillage reduces soil organic matter content, increases soil erodibility and the emission of greenhouse gases. Tillage in low input cropping systems involves a very large proportion of the population and any changes: in current practices such as increased mechanization will have a large social impact such as increased unemployment and increasing feminization of poverty, as mechanization may actually reduce jobs for women. Rapid mechanization is likely to result in failures, but slower change, accompanied by measures to provide alternative rural employment, might be beneficial. Agriculture in limited resource areas must produce the food and fiber needs of their community, and its future depends on the development of sustainable tillage/cropping systems that are suitable for the soil and climatic conditions. These should be based on sound biophysical principles and meet the needs of and he acceptable to the farming communities. Some of the principle requirements for a sustainable system includes the maintenance of soil health, an increase in the rain water use efficiency of the system, increased use of fertilizer and the prevention of erosion. The maintenance of crop residues on the surface is paramount for meeting these requirements, and the competing use of crop residues must be met from other sources. These requirements can be met within a zonal tillage system combined with suitable agroforestry, which will reduce the need for crop residues. It is, however, essential that farmers participate in the development of any new technologies to ensure adoption of the new system. (C) 2001 Elsevier Science B.V. All rights reserved.

Assessment of bioelectrical impedance analysis for the prediction of total body water in cystic fibrosis

The aim of this study was to compare the measurement of total body water (TBW) by deuterium ((H2O)-H-2) dilution and bioelectrical impedance analysis (BIA) in patients with cystic fibrosis (CF) and healthy controls. Thirty-six clinically stable patients with CF (age 25.4 +/- 5.6 yrs) and 42 healthy controls (age 25.4 +/- 4.8) were recruited into this study. TBW was measured by (H2O)-H-2 dilution and predicted by BIA in patients and controls. The TBW predicted from BIA was significantly different from TBW as measured using (H2O)-H-2 in patients (P

Learning the dynamics of embedded clauses

Recent work by Siegelmann has shown that the computational power of recurrent neural networks matches that of Turing Machines. One important implication is that complex language classes (infinite languages with embedded clauses) can be represented in neural networks. Proofs are based on a fractal encoding of states to simulate the memory and operations of stacks. In the present work, it is shown that similar stack-like dynamics can be learned in recurrent neural networks from simple sequence prediction tasks. Two main types of network solutions are found and described qualitatively as dynamical systems: damped oscillation and entangled spiraling around fixed points. The potential and limitations of each solution type are established in terms of generalization on two different context-free languages. Both solution types constitute novel stack implementations - generally in line with Siegelmann's theoretical work - which supply insights into how embedded structures of languages can be handled in analog hardware.

Integrable impurity spin ladder systems

Two different types of integrable impurities in a spin ladder system are proposed. The impurities are introduced in such a way that the integrability of the models is not violated. The models are solved exactly with the Bethe ansatz equations as well as the energy eigenvalues obtained. We show for both models that a phase transition between gapped and gapless spin excitations occurs at a critical value of the rung coupling J. In addition, the dependence of the impurities on this phase transition is determined explicitly. In one of the models the spin gap decreases by increasing the impurity strength A. Moreover, for a fixed A, a reduction in the spin gap by increasing the impurity concentration is also observed.

Large sets of large sets of Steiner triple systems of order 9

We describe a direct method of partitioning the 840 Steiner triple systems of order 9 into 120 large sets. The method produces partitions in which all of the large sets are isomorphic and we apply the method to each of the two non-isomorphic large sets of STS(9).

Metabolic model for glycogen-accumulating organisms in anaerobic/aerobic activated sludge systems

Glycogen-accumulating organisms (GAO) have the potential to directly compete with polyphosphate-accumulating organisms (PAO) in EBPR systems as both are able to take up VFA anaerobically and grow on the intracellular storage products aerobically. Under anaerobic conditions GAO hydrolyse glycogen to gain energy and reducing equivalents to take up VFA and to synthesise polyhydroxyalkanoate (PHA). In the subsequent aerobic stage, PHA is being oxidised to gain energy for glycogen replenishment (from PHA) and for cell growth. This article describes a complete anaerobic and aerobic model for GAO based on the understanding of their metabolic pathways. The anaerobic model has been developed and reported previously, while the aerobic metabolic model was developed in this study. It is based on the assumption that acetyl-CoA and propionyl-CoA go through the catabolic and anabolic processes independently. Experimental validation shows that the integrated model can predict the anaerobic and aerobic results very well. It was found in this study that at pH 7 the maximum acetate uptake rate of GAO was slower than that reported for PAO in the anaerobic stage. On the other hand, the net biomass production per C-mol acetate added is about 9% higher for GAO than for PAO. This would indicate that PAO and GAO each have certain competitive advantages during different parts of the anaerobic/aerobic process cycle. (C) 2002 Wiley Periodicals, Inc.

On measuring quality of a probabilistic commodity forecast for a system that incorporates seasonal climate forecasts

Regional commodity forecasts are being used increasingly in agricultural industries to enhance their risk management and decision-making processes. These commodity forecasts are probabilistic in nature and are often integrated with a seasonal climate forecast system. The climate forecast system is based on a subset of analogue years drawn from the full climatological distribution. In this study we sought to measure forecast quality for such an integrated system. We investigated the quality of a commodity (i.e. wheat and sugar) forecast based on a subset of analogue years in relation to a standard reference forecast based on the full climatological set. We derived three key dimensions of forecast quality for such probabilistic forecasts: reliability, distribution shift, and change in dispersion. A measure of reliability was required to ensure no bias in the forecast distribution. This was assessed via the slope of the reliability plot, which was derived from examination of probability levels of forecasts and associated frequencies of realizations. The other two dimensions related to changes in features of the forecast distribution relative to the reference distribution. The relationship of 13 published accuracy/skill measures to these dimensions of forecast quality was assessed using principal component analysis in case studies of commodity forecasting using seasonal climate forecasting for the wheat and sugar industries in Australia. There were two orthogonal dimensions of forecast quality: one associated with distribution shift relative to the reference distribution and the other associated with relative distribution dispersion. Although the conventional quality measures aligned with these dimensions, none measured both adequately. We conclude that a multi-dimensional approach to assessment of forecast quality is required and that simple measures of reliability, distribution shift, and change in dispersion provide a means for such assessment. The analysis presented was also relevant to measuring quality of probabilistic seasonal climate forecasting systems. The importance of retaining a focus on the probabilistic nature of the forecast and avoiding simplifying, but erroneous, distortions was discussed in relation to applying this new forecast quality assessment paradigm to seasonal climate forecasts. Copyright (K) 2003 Royal Meteorological Society.