Nutrition of chicks and layers

When formulating least-cost poultry diets, ME concentration should be optimised by an iterative procedure, not entered as a fixed value. This iteration must calculate profit margins by taking into account the way in which feed intake and saleable outputs vary with ME concentration. In the case of broilers, adjustment of critical amino acid contents in direct proportion to ME concentration does not result in birds of equal fatness. To avoid an increase in fat deposition at higher energy levels, it is proposed that amino acid specifications should be adjusted in proportion to changes in the net energy supplied by the feed. A model is available which will both interpret responses to amino acids in laying trials and give economically optimal estimates of amino acid inputs for practical feed formulation. Flocks coming into lay and flocks nearing the end of the pullet year have bimodal distributions of rates of lay, with the result that calculations of requirement based on mean output will underestimate the optimal amino acid input for the flock. Chick diets containing surplus protein can lead to impaired utilisation of the first-limiting amino acid. This difficulty can be avoided by stating amino acid requirements as a proportion of the protein.

Modelling of Johne's disease control options in beef cattle: a decision support approach

Johne's disease in cattle is a contagious wasting disease caused by Mycobacterium avium subspecies paratuberculosis (MAP). Johne's infection is characterised by a long subclinical phase and can therefore go undetected for long periods of time during which substantial production losses can occur. The protracted nature of Johne's infection therefore presents a challenge for both veterinarians and farmers when discussing control options due to a paucity of information and limited test performance when screening for the disease. The objectives were to model Johne's control decisions in suckler beef cattle using a decision support approach, thus implying equal focus on ‘end user’ (veterinarian) participation whilst still focusing on the technical disease modelling aspects during the decision support model development. The model shows how Johne's disease is likely to affect a herd over time both in terms of physical and financial impacts. In addition, the model simulates the effect on production from two different Johne's control strategies; herd management measures and test and cull measures. The article also provides and discusses results from a sensitivity analysis to assess the effects on production from improving the currently available test performance. Output from running the model shows that a combination of management improvements to reduce routes of infection and testing and culling to remove infected and infectious animals is likely to be the least-cost control strategy.

Poor survival on an artificial diet of two genotypes of the aphid Myzus persicae: a fitness cost of insecticide resistance?

A fully susceptible genotype (4106A) of Myzus persicae survived the longest on an artificial diet and, in several of the eight replicates, monitoring was terminated when the culture was still thriving. A genotype with elevated carboxylesterase FE4 at the R3 level (800F) had a mean survival of only 98.13 days, whereas 794J, which combines R3 E4 carboxylesterase with target-site resistance (knockdown resistance), survived for the even shorter mean time of 84.38 days. The poorer survival of the two genotypes with extremely elevated carboxylesterase-resistance was not the result of a reluctance to transfer to new diet at each diet change. Although available for only two replicates, a revertant clone of 794J (794Jrev), which has the same genotype as 794J but the amplified E4 genes are not expressed leading to a fully susceptible phenotype, did not appear to survive any better than this clone. This suggests that the poor survival on an artificial diet of the extreme-carboxylesterase genotypes is not the result of the cost of over-producing the enzyme. The frequency of insecticide-resistant genotypes is low in the population until insecticide is applied, indicating that they have reduced fitness, although this does not necessarily reflect a direct cost of expressing the resistance mechanism.

An evaluation of the use of Cottonseed cake in the diet of growing pigs

An experiment was conducted to determine the effects of including cottonseed cake in rations for weaned growing pigs. Thirty-two Landrace x Large White pigs, weighing 20-24 kg, were included in four blocks formed on the basis of initial weight within sex in an otherwise completely randomized block design. The pigs were killed when they reached a live weight of 75.0 +/- 2.0 kg and the half careases were analysed into cuts and the weights of the organs were recorded. An estimate of the productivity of the pigs on each diet was calculated. Cottonseed cake reduced the voluntary feed intake (p < 0.001) and live weight gains (p < 0.001) and increased the heart, kidney and liver weights (p < 0.01). The pigs on the soya bean-based control diet took the shortest time to reach slaughter weight. The result was probably in part due to lysine deficiency and in part to the effect of free gossypol. It was found that it is at present cost-effective to include cottonseed cake in pig weaner grower diets up to 300 g/kg in Cameroon.

Reproducibility of a short semi-quantitative food group questionnaire and its performance in estimating nutrient intake compared with a 7-day diet diary in the Million Women Study

Objectives: To assess the short- and long-term reproducibility of a short food group questionnaire, and to compare its performance for estimating nutrient intakes in comparison with a 7-day diet diary. Design: Participants for the reproducibility study completed the food group questionnaire at two time points, up to 2 years apart. Participants for the performance study completed both the food group questionnaire and a 7-day diet diary a few months apart. Reproducibility was assessed by kappa statistics and percentage change between the two questionnaires; performance was assessed by kappa statistics, rank correlations and percentages of participants classified into the same and opposite thirds of intake. Setting: A random sample of participants in the Million Women Study, a population-based prospective study in the UK. Subjects: In total, 12 221 women aged 50-64 years. Results: in the reproducibility study, 75% of the food group items showed at least moderate agreement for all four time-point comparisons. Items showing fair agreement or worse tended to be those where few respondents reported eating them more than once a week, those consumed in small amounts and those relating to types of fat consumed. Compared with the diet diary, the food group questionnaire showed consistently reasonable performance for the nutrients carbohydrate, saturated fat, cholesterol, total sugars, alcohol, fibre, calcium, riboflavin, folate and vitamin C. Conclusions: The short food group questionnaire used in this study has been shown to be reproducible over time and to perform reasonably well for the assessment of a number of dietary nutrients.

Fully complex-valued radial basis function networks for orthogonal least squares regression

We consider a fully complex-valued radial basis function (RBF) network for regression application. The locally regularised orthogonal least squares (LROLS) algorithm with the D-optimality experimental design, originally derived for constructing parsimonious real-valued RBF network models, is extended to the fully complex-valued RBF network. Like its real-valued counterpart, the proposed algorithm aims to achieve maximised model robustness and sparsity by combining two effective and complementary approaches. The LROLS algorithm alone is capable of producing a very parsimonious model with excellent generalisation performance while the D-optimality design criterion further enhances the model efficiency and robustness. By specifying an appropriate weighting for the D-optimality cost in the combined model selecting criterion, the entire model construction procedure becomes automatic. An example of identifying a complex-valued nonlinear channel is used to illustrate the regression application of the proposed fully complex-valued RBF network.

Sparse multioutput radial basis function network construction using combined locally regularised orthogonal least square and D-optimality experimental design

A construction algorithm for multioutput radial basis function (RBF) network modelling is introduced by combining a locally regularised orthogonal least squares (LROLS) model selection with a D-optimality experimental design. The proposed algorithm aims to achieve maximised model robustness and sparsity via two effective and complementary approaches. The LROLS method alone is capable of producing a very parsimonious RBF network model with excellent generalisation performance. The D-optimality design criterion enhances the model efficiency and robustness. A further advantage of the combined approach is that the user only needs to specify a weighting for the D-optimality cost in the combined RBF model selecting criterion and the entire model construction procedure becomes automatic. The value of this weighting does not influence the model selection procedure critically and it can be chosen with ease from a wide range of values.

Sparse kernel regression modeling using combined locally regularized orthogonal least squares and D-optimality experimental design

The note proposes an efficient nonlinear identification algorithm by combining a locally regularized orthogonal least squares (LROLS) model selection with a D-optimality experimental design. The proposed algorithm aims to achieve maximized model robustness and sparsity via two effective and complementary approaches. The LROLS method alone is capable of producing a very parsimonious model with excellent generalization performance. The D-optimality design criterion further enhances the model efficiency and robustness. An added advantage is that the user only needs to specify a weighting for the D-optimality cost in the combined model selecting criterion and the entire model construction procedure becomes automatic. The value of this weighting does not influence the model selection procedure critically and it can be chosen with ease from a wide range of values.

Fully complex-valued radial basis function networks: orthogonal least squares regression and classification

We consider a fully complex-valued radial basis function (RBF) network for regression and classification applications. For regression problems, the locally regularised orthogonal least squares (LROLS) algorithm aided with the D-optimality experimental design, originally derived for constructing parsimonious real-valued RBF models, is extended to the fully complex-valued RBF (CVRBF) network. Like its real-valued counterpart, the proposed algorithm aims to achieve maximised model robustness and sparsity by combining two effective and complementary approaches. The LROLS algorithm alone is capable of producing a very parsimonious model with excellent generalisation performance while the D-optimality design criterion further enhances the model efficiency and robustness. By specifying an appropriate weighting for the D-optimality cost in the combined model selecting criterion, the entire model construction procedure becomes automatic. An example of identifying a complex-valued nonlinear channel is used to illustrate the regression application of the proposed fully CVRBF network. The proposed fully CVRBF network is also applied to four-class classification problems that are typically encountered in communication systems. A complex-valued orthogonal forward selection algorithm based on the multi-class Fisher ratio of class separability measure is derived for constructing sparse CVRBF classifiers that generalise well. The effectiveness of the proposed algorithm is demonstrated using the example of nonlinear beamforming for multiple-antenna aided communication systems that employ complex-valued quadrature phase shift keying modulation scheme. (C) 2007 Elsevier B.V. All rights reserved.

Nonlinear model structure design and construction using orthogonal least squares and D-optimality design

A very efficient learning algorithm for model subset selection is introduced based on a new composite cost function that simultaneously optimizes the model approximation ability and model robustness and adequacy. The derived model parameters are estimated via forward orthogonal least squares, but the model subset selection cost function includes a D-optimality design criterion that maximizes the determinant of the design matrix of the subset to ensure the model robustness, adequacy, and parsimony of the final model. The proposed approach is based on the forward orthogonal least square (OLS) algorithm, such that new D-optimality-based cost function is constructed based on the orthogonalization process to gain computational advantages and hence to maintain the inherent advantage of computational efficiency associated with the conventional forward OLS approach. Illustrative examples are included to demonstrate the effectiveness of the new approach.

Nonlinear model structure detection using optimum experimental design and orthogonal least squares

A very efficient learning algorithm for model subset selection is introduced based on a new composite cost function that simultaneously optimizes the model approximation ability and model adequacy. The derived model parameters are estimated via forward orthogonal least squares, but the subset selection cost function includes an A-optimality design criterion to minimize the variance of the parameter estimates that ensures the adequacy and parsimony of the final model. An illustrative example is included to demonstrate the effectiveness of the new approach.

Attitudinal and demographic determinants of diet quality and implications for policy targeting

Background:  Poor diet quality is a major public health concern that has prompted governments to introduce a range of measures to promote healthy eating. For these measures to be effective, they should target segments of the population with messages relevant to their needs, aspirations and circumstances. The present study investigates the extent to which attitudes and constraints influence healthy eating, as well as how these vary by demographic characteristics of the UK population. It further considers how such information may be used in segmented diet and health policy messages. Methods:  A survey of 250 UK adults elicited information on conformity to dietary guidelines, attitudes towards healthy eating, constraints to healthy eating and demographic characteristics. Ordered logit regressions were estimated to determine the importance of attitudes and constraints in determining how closely respondents follow healthy eating guidelines. Further regressions explored the demographic characteristics associated with the attitudinal and constraint variables. Results:  People who attach high importance to their own health and appearance eat more healthily than those who do not. Risk-averse people and those able to resist temptation also eat more healthily. Shortage of time is considered an important barrier to healthy eating, although the cost of a healthy diet is not. These variables are associated with a number of demographic characteristics of the population; for example, young adults are more motivated to eat healthily by concerns over their appearance than their health. Conclusions:  The approach employed in the present study could be used to inform future healthy eating campaigns. For example, messages to encourage the young to eat more healthily could focus on the impact of diets on their appearance rather than health.

The cost of choice: how corporate real estate managers evaluate business space options

Firms are faced with a wider set of choices when they identify a need for new office space. They can build or purchase accommodation, lease space for long or short periods with or without the inclusion of services, or they can use “instant office” solutions provided by serviced office operators. But how do they evaluate these alternatives and are they able to make rational choices? The research found that the shortening of business horizons lead to the desire for more office space on short-term contracts often with the inclusion of at least some facilities management and business support services. The need for greater flexibility, particularly in financial terms, was highlighted as an important criteria when selecting new office accommodation. The current office portfolios held were perceived not to meet these requirements. However, there was often a lack of good quality data available within occupiers which could be used to help them analyse the range of choices in the market. Additionally, there were other organisational constraints to making decisions about inclusive real estate products. These included fragmentation of decisions-making, internal politics and the lack of assessment of business risk alongside real estate risk. Overall therefore, corporate occupiers themselves act as an interial force to the development of new and innovative real estate products.

Wall materials and techniques available for low cost housing in Khartoum from a sustainability point of view

Khartoum like many cities in least developing countries (LDCs) still witnesses huge influx of people. Accommodation of the new comers leads to encroachment on the cultivation land leads to sprawl expansion of Greater Khartoum. The city expanded in diameter from 16.8 km in 1955 to 802.5 km in 1998. Most of this horizontal expansion was residential. In 2008 Khartoum accommodated 29% of the urban population of Sudan. Today Khartoum is considered as one of 43 major cities in Africa that accommodates more than 1 million inhabitants. Most of new comers live in the outskirts of the city e.g. Dar El-Salam and Mayo neighbourhoods. The majority of those new comers built their houses especially the walls from mud, wood, straw and sacks. Selection of building materials usually depends on its price regardless of the environmental impact, quality, thermal performance and life of the material. Most of the time, this results in increasing the cost with variables of impacts over the environment during the life of the building. Therefore, consideration of the environmental impacts, social impacts and economic impacts is crucial in the selection of any building material. Decreasing such impacts could lead to more sustainable housing. Comparing the sustainability of the available wall building materials for low cost housing in Khartoum is carried out through the life cycle assessment (LCA) technique. The purpose of this paper is to compare the most available local building materials for walls for the urban poor of Khartoum from a sustainability point of view by going through the manufacturing of the materials, the use of these materials and then the disposal of the materials after their life comes to an end. Findings reveal that traditional red bricks couldn’t be considered as a sustainable wall building material that will draw the future of the low cost housing in Greater Khartoum. On the other hand, results of the comparison lead to draw attention to the wide range of the soil techniques and to its potentials to be a promising sustainable wall material for urban low cost housing in Khartoum.

Assessing the impact on chronic disease of incorporating the societal cost of greenhouse gases into the price of food: an econometric and comparative risk assessment modelling study

Objectives To model the impact on chronic disease of a tax on UK food and drink that internalises the wider costs to society of greenhouse gas (GHG) emissions and to estimate the potential revenue. Design An econometric and comparative risk assessment modelling study. Setting The UK. Participants The UK adult population. Interventions Two tax scenarios are modelled: (A) a tax of £2.72/tonne carbon dioxide equivalents (tCO2e)/100 g product applied to all food and drink groups with above average GHG emissions. (B) As with scenario (A) but food groups with emissions below average are subsidised to create a tax neutral scenario. Outcome measures Primary outcomes are change in UK population mortality from chronic diseases following the implementation of each taxation strategy, the change in the UK GHG emissions and the predicted revenue. Secondary outcomes are the changes to the micronutrient composition of the UK diet. Results Scenario (A) results in 7770 (95% credible intervals 7150 to 8390) deaths averted and a reduction in GHG emissions of 18 683 (14 665to 22 889) ktCO2e/year. Estimated annual revenue is £2.02 (£1.98 to £2.06) billion. Scenario (B) results in 2685 (1966 to 3402) extra deaths and a reduction in GHG emissions of 15 228 (11 245to 19 492) ktCO2e/year. Conclusions Incorporating the societal cost of GHG into the price of foods could save 7770 lives in the UK each year, reduce food-related GHG emissions and generate substantial tax revenue. The revenue neutral scenario (B) demonstrates that sustainability and health goals are not always aligned. Future work should focus on investigating the health impact by population subgroup and on designing fiscal strategies to promote both sustainable and healthy diets.