Solar change and climate: an update in the light of the current exceptional solar minimum

Solar outputs during the current solar minimum are setting record low values for the space age. Evidence is here reviewed that this is part of a decline in solar activity from a grand solar maximum and that the Sun has returned to a state that last prevailed in 1924. Recent research into what this means, and does not mean, for climate change is reviewed.

Analytical potentials for triatomic molecules from spectroscopic data VI. On choosing internal coordinates to describe triatomic potential energy surfaces with more than one minimum

Orthogonal internal coordinates are defined which have useful properties for constructing the potential energy functions of triatomic molecules with two or three minima on the surface. The coordinates are used to obtain ground state potentials of ClOO and HOF, both of which have three minima.

The maintenance requirement of domestic drakes

1. Mature domestic drakes of 7 genotypes, ranging in live weight from 1.1to 5.1 kg, were each given a daily allowance of feed just below the level of recorded ad libitum intake. 2. House temperature was maintained at 26 degrees C for 16 weeks and then at 10 degrees C for a further 8 weeks. 3. Under these conditions, live weight quickly adjusted to the level of feed supplied and then remained stable. 4. Regression of metabolisable energy intake on live weight (W) yielded estimates of maintenance requirement of 583 kJ/kg W-0.75 center dot d at 10 degrees C and 523 kJ/kg W-0.75 center dot d at 26 degrees C.

Predicting the profile of nutrients available for absorption: from nutrient requirement to animal response and environmental impact

Current feed evaluation systems for dairy cattle aim to match nutrient requirements with nutrient intake at pre-defined production levels. These systems were not developed to address, and are not suitable to predict, the responses to dietary changes in terms of production level and product composition, excretion of nutrients to the environment, and nutrition related disorders. The change from a requirement to a response system to meet the needs of various stakeholders requires prediction of the profile of absorbed nutrients and its subsequent utilisation for various purposes. This contribution examines the challenges to predicting the profile of nutrients available for absorption in dairy cattle and provides guidelines for further improved prediction with regard to animal production responses and environmental pollution. The profile of nutrients available for absorption comprises volatile fatty acids, long-chain fatty acids, amino acids and glucose. Thus the importance of processes in the reticulo-rumen is obvious. Much research into rumen fermentation is aimed at determination of substrate degradation rates. Quantitative knowledge on rates of passage of nutrients out of the rumen is rather limited compared with that on degradation rates, and thus should be an important theme in future research. Current systems largely ignore microbial metabolic variation, and extant mechanistic models of rumen fermentation give only limited attention to explicit representation of microbial metabolic activity. Recent molecular techniques indicate that knowledge on the presence and activity of various microbial species is far from complete. Such techniques may give a wealth of information, but to include such findings in systems predicting the nutrient profile requires close collaboration between molecular scientists and mathematical modellers on interpreting and evaluating quantitative data. Protozoal metabolism is of particular interest here given the paucity of quantitative data. Empirical models lack the biological basis necessary to evaluate mitigation strategies to reduce excretion of waste, including nitrogen, phosphorus and methane. Such models may have little predictive value when comparing various feeding strategies. Examples include the Intergovernmental Panel on Climate Change (IPCC) Tier II models to quantify methane emissions and current protein evaluation systems to evaluate low protein diets to reduce nitrogen losses to the environment. Nutrient based mechanistic models can address such issues. Since environmental issues generally attract more funding from governmental offices, further development of nutrient based models may well take place within an environmental framework.

A review and simplification of the in vitro incubation medium

The requirement to rapidly and efficiently evaluate ruminant feedstuffs places increased emphasis on in vitro systems. However, despite the developmental work undertaken and widespread application of such techniques, little attention has been paid to the incubation medium. Considerable research using in vitro systems is conducted in resource-poor developing countries that often have difficulties associated with technical expertise, sourcing chemicals and/or funding to cover analytical and equipment costs. Such limitations have, to date, restricted vital feed evaluation programmes in these regions. This paper examines the function and relevance of the buffer, nutrient, and reducing solution components within current in vitro media, with the aim of identifying where simplification can be achieved. The review, supported by experimental work, identified no requirement to change the carbonate or phosphate salts, which comprise the main buffer components. The inclusion of microminerals provided few additional nutrients over that already supplied by the rumen fluid and substrate, and so may be omitted. Nitrogen associated with the inoculum was insufficient to support degradation and a level of 25 mg N/g substrate is recommended. A sulphur inclusion level of 4-5 mg S/g substrate is proposed, with S levels lowered through omission of sodium sulphide and replacement of magnesium sulphate with magnesium chloride. It was confirmed that a highly reduced medium was not required, provided that anaerobic conditions were rapidly established. This allows sodium sulphide, part of the reducing solution, to be omitted. Further, as gassing with CO2 directly influences the quantity of gas released, it is recommended that minimum CO, levels be used and that gas flow and duration, together with the volume of medium treated, are detailed in experimental procedures. It is considered that these simplifications will improve safety and reduce costs and problems associated with sourcing components, while maintaining analytical precision. (c) 2005 Elsevier B.V. All rights reserved.

Measuring the functional responses of farmland birds: an example for a declining seed-feeding bunting

1. Many farmland bird species have undergone significant declines. It is important to predict the effect of agricultural change on these birds and their response to conservation measures. This requirement could be met by mechanistic models that predict population size from the optimal foraging behaviour and fates of individuals within populations. A key component of these models is the functional response, the relationship between food and competitor density and feeding rate. 2. This paper describes a method for measuring functional responses of farmland birds, and applies this method to a declining farmland bird, the corn bunting Miliaria calandra L. We derive five alternative models to predict the functional responses of farmland birds and parameterize these for corn bunting. We also assess the minimum sample sizes required to predict accurately the functional response. 3. We show that the functional response of corn bunting can be predicted accurately from a few behavioural parameters (searching rate, handling time, vigilance time) that are straightforward to measure in the field. These parameters can be measured more quickly than the alternative of measuring the functional response directly. 4. While corn bunting violated some of the assumptions of Holling's disk equation (model 1 in our study), it still provided the most accurate fit to the observed feeding rates while remaining the most statistically simple model tested. Our other models may be more applicable to other species, or corn bunting feeding in other locations. 5. Although further tests are required, our study shows how functional responses can be predicted, simplifying the development of mechanistic models of farmland bird populations.

Minimum aberration construction results for nonregular two-level fractional factorial designs

Nonregular two-level fractional factorial designs are designs which cannot be specified in terms of a set of defining contrasts. The aliasing properties of nonregular designs can be compared by using a generalisation of the minimum aberration criterion called minimum G2-aberration.Until now, the only nontrivial designs that are known to have minimum G2-aberration are designs for n runs and m n–5 factors. In this paper, a number of construction results are presented which allow minimum G2-aberration designs to be found for many of the cases with n = 16, 24, 32, 48, 64 and 96 runs and m n/2–2 factors.

Some theory for constructing minimum aberration fractional factorial designs

Minimum aberration is the most established criterion for selecting a regular fractional factorial design of maximum resolution. Minimum aberration designs for n runs and n/2 less than or equal to m < n factors have previously been constructed using the novel idea of complementary designs. In this paper, an alternative method of construction is developed by relating the wordlength pattern of designs to the so-called 'confounding between experimental runs'. This allows minimum aberration designs to be constructed for n runs and 5n/16 less than or equal to m less than or equal to n/2 factors as well as for n/2 less than or equal to m < n.

Description of a "Phoenix" phenomenon in the growth of Campylobacter jejuni at temperatures close to the minimum for growth

When Campylobacter jejuni cultures that had been grown in broth at 39degreesC were subcultured into fresh medium at 30degreesC, there was a transient period of growth followed by a decline in viable-cell numbers before growth resumed once more. We propose that this complex behavior is the net effect of the growth of inoculum cells followed by a loss of viability due to oxidative stress and the subsequent emergence of a spontaneously arising mutant population that takes over the culture.

A knowledge-based evolution strategy for the multi-objective minimum spanning tree problem

A fast Knowledge-based Evolution Strategy, KES, for the multi-objective minimum spanning tree, is presented. The proposed algorithm is validated, for the bi-objective case, with an exhaustive search for small problems (4-10 nodes), and compared with a deterministic algorithm, EPDA and NSGA-II for larger problems (up to 100 nodes) using benchmark hard instances. Experimental results show that KES finds the true Pareto fronts for small instances of the problem and calculates good approximation Pareto sets for larger instances tested. It is shown that the fronts calculated by YES are superior to NSGA-II fronts and almost as good as those established by EPDA. KES is designed to be scalable to multi-objective problems and fast due to its small complexity.

A hybridised evolutionary algorithm for multi-criterion minimum spanning tree problems

A hybridised and Knowledge-based Evolutionary Algorithm (KEA) is applied to the multi-criterion minimum spanning tree problems. Hybridisation is used across its three phases. In the first phase a deterministic single objective optimization algorithm finds the extreme points of the Pareto front. In the second phase a K-best approach finds the first neighbours of the extreme points, which serve as an elitist parent population to an evolutionary algorithm in the third phase. A knowledge-based mutation operator is applied in each generation to reproduce individuals that are at least as good as the unique parent. The advantages of KEA over previous algorithms include its speed (making it applicable to large real-world problems), its scalability to more than two criteria, and its ability to find both the supported and unsupported optimal solutions.

Dimension and coverage of multiple-models structures using clustering techniques

In this work a method for building multiple-model structures is presented. A clustering algorithm that uses data from the system is employed to define the architecture of the multiple-model, including the size of the region covered by each model, and the number of models. A heating ventilation and air conditioning system is used as a testbed of the proposed method.

Turbo channel estimation and equalisation for a superposition-based cooperative system

This study investigates the superposition-based cooperative transmission system. In this system, a key point is for the relay node to detect data transmitted from the source node. This issued was less considered in the existing literature as the channel is usually assumed to be flat fading and a priori known. In practice, however, the channel is not only a priori unknown but subject to frequency selective fading. Channel estimation is thus necessary. Of particular interest is the channel estimation at the relay node which imposes extra requirement for the system resources. The authors propose a novel turbo least-square channel estimator by exploring the superposition structure of the transmission data. The proposed channel estimator not only requires no pilot symbols but also has significantly better performance than the classic approach. The soft-in-soft-out minimum mean square error (MMSE) equaliser is also re-derived to match the superimposed data structure. Finally computer simulation results are shown to verify the proposed algorithm.

OFDM joint data detection and phase noise cancellation based on minimum mean square prediction error

This paper proposes a new iterative algorithm for orthogonal frequency division multiplexing (OFDM) joint data detection and phase noise (PHN) cancellation based on minimum mean square prediction error. We particularly highlight the relatively less studied problem of "overfitting" such that the iterative approach may converge to a trivial solution. Specifically, we apply a hard-decision procedure at every iterative step to overcome the overfitting. Moreover, compared with existing algorithms, a more accurate Pade approximation is used to represent the PHN, and finally a more robust and compact fast process based on Givens rotation is proposed to reduce the complexity to a practical level. Numerical Simulations are also given to verify the proposed algorithm. (C) 2008 Elsevier B.V. All rights reserved.

Design of a minimum variance multiple input-multiple output neuro self-tuning proportional-integral-derivative controller for non-linear dynamic systems

In this study a minimum variance neuro self-tuning proportional-integral-derivative (PID) controller is designed for complex multiple input-multiple output (MIMO) dynamic systems. An approximation model is constructed, which consists of two functional blocks. The first block uses a linear submodel to approximate dominant system dynamics around a selected number of operating points. The second block is used as an error agent, implemented by a neural network, to accommodate the inaccuracy possibly introduced by the linear submodel approximation, various complexities/uncertainties, and complicated coupling effects frequently exhibited in non-linear MIMO dynamic systems. With the proposed model structure, controller design of an MIMO plant with n inputs and n outputs could be, for example, decomposed into n independent single input-single output (SISO) subsystem designs. The effectiveness of the controller design procedure is initially verified through simulations of industrial examples.