Understanding African easterly waves: a moist singular vector approach

Moist singular vectors (MSV) have been applied successfully to predicting mid-latitude storms growing in association with latent heat of condensation. Tropical cyclone sensitivity has also been assessed. Extending this approach to more general tropical weather systems here, MSVs are evaluated for understanding and predicting African easterly waves, given the importance of moist processes in their development. First results, without initial moisture perturbations, suggest MSVs may be used advantageously. Perturbations bear similar structural and energy profiles to previous idealised non-linear studies and observations. Strong sensitivities prevail in the metrics and trajectories chosen, and benefits of initial moisture perturbations should be appraised. Copyright © 2009 Royal Meteorological Society

A singular vector perspective of 4DVAR: The spatial structure and evolution of baroclinic weather systems

The extent to which the four-dimensional variational data assimilation (4DVAR) is able to use information about the time evolution of the atmosphere to infer the vertical spatial structure of baroclinic weather systems is investigated. The singular value decomposition (SVD) of the 4DVAR observability matrix is introduced as a novel technique to examine the spatial structure of analysis increments. Specific results are illustrated using 4DVAR analyses and SVD within an idealized 2D Eady model setting. Three different aspects are investigated. The first aspect considers correcting errors that result in normal-mode growth or decay. The results show that 4DVAR performs well at correcting growing errors but not decaying errors. Although it is possible for 4DVAR to correct decaying errors, the assimilation of observations can be detrimental to a forecast because 4DVAR is likely to add growing errors instead of correcting decaying errors. The second aspect shows that the singular values of the observability matrix are a useful tool to identify the optimal spatial and temporal locations for the observations. The results show that the ability to extract the time-evolution information can be maximized by placing the observations far apart in time. The third aspect considers correcting errors that result in nonmodal rapid growth. 4DVAR is able to use the model dynamics to infer some of the vertical structure. However, the specification of the case-dependent background error variances plays a crucial role.

A singular vector perspective of 4D-Var: Filtering and interpolation

Four-dimensional variational data assimilation (4D-Var) combines the information from a time sequence of observations with the model dynamics and a background state to produce an analysis. In this paper, a new mathematical insight into the behaviour of 4D-Var is gained from an extension of concepts that are used to assess the qualitative information content of observations in satellite retrievals. It is shown that the 4D-Var analysis increments can be written as a linear combination of the singular vectors of a matrix which is a function of both the observational and the forecast model systems. This formulation is used to consider the filtering and interpolating aspects of 4D-Var using idealized case-studies based on a simple model of baroclinic instability. The results of the 4D-Var case-studies exhibit the reconstruction of the state in unobserved regions as a consequence of the interpolation of observations through time. The results also exhibit the filtering of components with small spatial scales that correspond to noise, and the filtering of structures in unobserved regions. The singular vector perspective gives a very clear view of this filtering and interpolating by the 4D-Var algorithm and shows that the appropriate specification of the a priori statistics is vital to extract the largest possible amount of useful information from the observations. Copyright © 2005 Royal Meteorological Society

Singular vector ensemble forecasting systems and the prediction of flow dependent uncertainty

The ECMWF ensemble weather forecasts are generated by perturbing the initial conditions of the forecast using a subset of the singular vectors of the linearised propagator. Previous results show that when creating probabilistic forecasts from this ensemble better forecasts are obtained if the mean of the spread and the variability of the spread are calibrated separately. We show results from a simple linear model that suggest that this may be a generic property for all singular vector based ensemble forecasting systems based on only a subset of the full set of singular vectors.

Bayesian estimation and selection of nonlinear vector error correction models: The case of the sugar-ethanol-oil nexus in Brazil

Nonlinear adjustment toward long-run price equilibrium relationships in the sugar-ethanol-oil nexus in Brazil is examined. We develop generalized bivariate error correction models that allow for cointegration between sugar, ethanol, and oil prices, where dynamic adjustments are potentially nonlinear functions of the disequilibrium errors. A range of models are estimated using Bayesian Monte Carlo Markov Chain algorithms and compared using Bayesian model selection methods. The results suggest that the long-run drivers of Brazilian sugar prices are oil prices and that there are nonlinearities in the adjustment processes of sugar and ethanol prices to oil price but linear adjustment between ethanol and sugar prices.

Consumption of welfare-friendly food products in Great Britain, Italy and Sweden, and how it may be influenced by consumer attitudes to, and behaviour towards, animal welfare attributes

The interest in animal welfare and welfare-friendly food products has been increasing in Europe over the last 10 years. The media, highlighting traditional farming methods and food scares such as those related to salmonella, bovine spongiform encephalopathy/variant Creutzfeldt-Jakob disease (BSE) and avian influenza, have brought the methods of animal farming to public attention. Concerns about farm animal welfare are reflected in the increase in the number of vegetarians and vegans and an increase in consumers wishing to purchase food which is more animal welfare-friendly. This paper considers consumers’ attitudes to animal welfare and to marketing practices, such as product labelling, welfare grading systems and food assurance marks using comparative data collected in a survey of around 1500 consumers in each of Great Britain, Italy and Sweden as part of the EU-funded Welfare Quality research project. The findings suggest a need for the provision of improved consumer information on the welfare provenance of food using appropriate product labelling and other methods.

Strategies, effectiveness and rationale of vector-borne disease control in the pastoralist system of south-western Uganda

In Uganda, control of vector-borne diseases is mainly in form of vector control, and chemotherapy. There have been reports that acaricides are being misused in the pastoralist systems in Uganda. This is because of the belief by scientists that intensive application of acaricide is uneconomical and unsustainable particularly in the indigenous cattle. The objective of this study was to investigate the strategies, rationale and effectiveness of vector-borne disease control by pastoralists. To systematically carry out these investigations, a combination of qualitative and quantitative research methods was used, in both the collection and the analysis of data. Cattle keepers were found to control tick-borne diseases (TBDs) mainly through spraying, in contrast with the control of trypanosomosis for which the main method of control was by chemotherapy. The majority of herders applied acaricides weekly and used an acaricide of lower strength than recommended by the manufacturers. They used very little acaricide wash, and spraying was preferred to dipping. Furthermore, pastoralists either treated sick animals themselves or did nothing at all, rather than using veterinary personnel. Oxytetracycline (OTC) was the drug commonly used in the treatment of TBDs. Nevertheless, although pastoralists may not have been following recommended practices in their control of ticks and tick-borne diseases, they were neither wasteful nor uneconomical and their methods appeared to be effective. Trypanosomosis was not a problem either in Sembabule or Mbarara district. Those who used trypanocides were found to use more drugs than were necessary.

The effect of the functional attributes of objects within the caged environment on interaction time in laboratory rats

Determining rat preferences for, and behaviour towards, environmental enrichment objects allows us to provide evidence-based information about how the caged environment may be enriched. In recent years there have been many studies investigating the preferences of laboratory rodents for a wide variety of environmental enrichment objects and materials. While these have provided important information regarding the animals' perception of the items, very few studies have attempted to systematically investigate the precise attributes that constitute a preferred object and the behaviour that these objects afford. We have designed a research program to systematically study rats' motivation to interact with enrichment objects. Here we present the results from two experiments which examined the time rats spent with objects that only differed in size. This showed that rats spent longer with large objects rather than small ones, even though objects were presented individually. We also investigated the rats' behaviour with the objects in an open field and found that rats spent longer climbing on top of the large object. This behaviour continued when the large objects were laid on their sides instead of placed upright in the arena, suggesting that the rats were not simply climbing on the objects to investigate the top of the arena and thus an escape route, but instead were genuinely motivated to climb. This suggests that rat welfare could be enhanced by the addition to their cages of objects that permit climbing. (C) 2009 Elsevier B.V. All rights reserved.

Perceptions of psychological content in the GP consultation - the role of practice, personal and prescribing attributes

Objective: The aim of the present study was to determine the relationship between the characteristics of general practices and the perceptions of the psychological content of consultations by GPs in those practices. Methods: A cross-sectional survey was conducted of all GPs (22 GPs based in nine practices) serving a discrete inner city community of 41 000 residents. GPs were asked to complete a log-diary over a period of five working days, rating their perception of the psychological content of each consultation on a 4-point Likert scale, ranging from 0 (no psychological content) to 3 (entirely psychological in content). The influence of GP and practice characteristics on psychological content scores was examined. Results: Data were available for every surgery-based consultation (n = 2206) conducted by all 22 participating GPs over the study period. The mean psychological content score was 0.58 (SD 0.33). Sixty-four percent of consultations were recorded as being without any psychological content; 6% were entirely psychological in content. Higher psychological content scores were significantly associated with younger GPs, training practices (n = 3), group practices (n = 4), the presence of on-site mental health workers (n = 5), higher antidepressant prescribing volumes and the achievement of vaccine and smear targets. Training status had the greatest predictive power, explaining 51% of the variation in psychological content. Neither practice consultation rates, GP list size, annual psychiatric referral rates nor volumes of benzodiazepine prescribing were related to psychological content scores. Conclusion: Increased awareness by GPs of the psychological dimension within a consultation may be a feature of the educational environment of training practices.

Investigation of support vector machine for the detection of architectural distortion in mammographic images

This paper investigates detection of architectural distortion in mammographic images using support vector machine. Hausdorff dimension is used to characterise the texture feature of mammographic images. Support vector machine, a learning machine based on statistical learning theory, is trained through supervised learning to detect architectural distortion. Compared to the Radial Basis Function neural networks, SVM produced more accurate classification results in distinguishing architectural distortion abnormality from normal breast parenchyma.

An empirical study of process-related attributes in segmented software cost-estimation relationships

Parametric software effort estimation models consisting on a single mathematical relationship suffer from poor adjustment and predictive characteristics in cases in which the historical database considered contains data coming from projects of a heterogeneous nature. The segmentation of the input domain according to clusters obtained from the database of historical projects serves as a tool for more realistic models that use several local estimation relationships. Nonetheless, it may be hypothesized that using clustering algorithms without previous consideration of the influence of well-known project attributes misses the opportunity to obtain more realistic segments. In this paper, we describe the results of an empirical study using the ISBSG-8 database and the EM clustering algorithm that studies the influence of the consideration of two process-related attributes as drivers of the clustering process: the use of engineering methodologies and the use of CASE tools. The results provide evidence that such consideration conditions significantly the final model obtained, even though the resulting predictive quality is of a similar magnitude.