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.

Attitudes of landscape professionals towards naturalistic versus formal urban landscapes in the UK

The last 30 years have seen a tide of interest sweeping across Europe in the development of nature in cities, and an increasing amount of landscape development in urban areas has involved the use of 'naturalistic' styles. This is an increasing attempt to find ways for urbanism and nature to co-exist. However, there have been considerable discussions among professionals regarding the advantages and disadvantages of 'naturalistic' styles in urban areas. This research examines professional attitudes to 'naturalistic' landscape styles in Britain, in contrast to more traditional, formal landscape styles, and aims to find out whether the interest in natural landscapes is really a fashion among landscape professionals. A self-administered postal survey was carried out using both quantitative and qualitative data collection techniques and analysis. The survey included 500 professionals from parks and recreation departments of local authorities, private landscape practices and conservation trusts, and resulted in a satisfactory response rate of 53 %. The results of this study suggested that professionals recognise most of the values attached to naturalistic landscapes in urban areas. However, possible benefits that natural areas may have for urban people are not attached to naturalistic landscapes alone. The study also revealed that the naturalistic style is highly popular among conservation trusts but is less so among professionals from local authorities and private landscape practices who seem to appreciate both styles and believe that these styles are not separable from each other and should co-exist in an urban environment. (C) 2006 Elsevier B.V. All rights reserved.

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.

Characterization and classification of tumor lesions using computerized fractal-based texture analysis and support vector machines in digital mammograms

Objective: This paper presents a detailed study of fractal-based methods for texture characterization of mammographic mass lesions and architectural distortion. The purpose of this study is to explore the use of fractal and lacunarity analysis for the characterization and classification of both tumor lesions and normal breast parenchyma in mammography. Materials and methods: We conducted comparative evaluations of five popular fractal dimension estimation methods for the characterization of the texture of mass lesions and architectural distortion. We applied the concept of lacunarity to the description of the spatial distribution of the pixel intensities in mammographic images. These methods were tested with a set of 57 breast masses and 60 normal breast parenchyma (dataset1), and with another set of 19 architectural distortions and 41 normal breast parenchyma (dataset2). Support vector machines (SVM) were used as a pattern classification method for tumor classification. Results: Experimental results showed that the fractal dimension of region of interest (ROIs) depicting mass lesions and architectural distortion was statistically significantly lower than that of normal breast parenchyma for all five methods. Receiver operating characteristic (ROC) analysis showed that fractional Brownian motion (FBM) method generated the highest area under ROC curve (A z = 0.839 for dataset1, 0.828 for dataset2, respectively) among five methods for both datasets. Lacunarity analysis showed that the ROIs depicting mass lesions and architectural distortion had higher lacunarities than those of ROIs depicting normal breast parenchyma. The combination of FBM fractal dimension and lacunarity yielded the highest A z value (0.903 and 0.875, respectively) than those based on single feature alone for both given datasets. The application of the SVM improved the performance of the fractal-based features in differentiating tumor lesions from normal breast parenchyma by generating higher A z value. Conclusion: FBM texture model is the most appropriate model for characterizing mammographic images due to self-affinity assumption of the method being a better approximation. Lacunarity is an effective counterpart measure of the fractal dimension in texture feature extraction in mammographic images. The classification results obtained in this work suggest that the SVM is an effective method with great potential for classification in mammographic image analysis.

Finding the point on Bezier Curves with the normal vector passing an external point

Two algorithms for finding the point on non-rational/rational Bezier curves of which the normal vector passes through a given external point are presented. The algorithms are based on Bezier curves generation algorithms of de Casteljau's algorithm for non-rational Bezier curve or Farin's recursion for rational Bezier curve, respectively. Orthogonal projections from the external point are used to guide the directional search used in the proposed iterative algorithms. Using Lyapunov's method, it is shown that each algorithm is able to converge to a local minimum for each case of non-rational/rational Bezier curves. It is also shown that on convergence the distance between the point on curves to the external point reaches a local minimum for both approaches. Illustrative examples are included to demonstrate the effectiveness of the proposed approaches.

Resource availability and the persistence of seed-eating bird populations in agricultural landscapes – a mechanistic modelling approach

1. Reductions in resource availability, associated with land-use change and agricultural intensification in the UK and Europe, have been linked with the widespread decline of many farmland bird species over recent decades. However, the underlying ecological processes which link resource availability and population trends are poorly understood. 2. We construct a spatial depletion model to investigate the relationship between the population persistence of granivorous birds within the agricultural landscape and the temporal dynamics of stubble field availability, an important source of winter food for many of those species. 3. The model is capable of accurately predicting the distribution of a given number of finches and buntings amongst patches of different stubble types in an agricultural landscape over the course of a winter and assessing the relative value of different landscapes in terms of resource availability. 4. Sensitivity analyses showed that the model is relatively robust to estimates of energetic requirements, search efficiency and handling time but that daily seed survival estimates have a strong influence on model fit. Understanding resource dynamics in agricultural landscapes is highlighted as a key area for further research. 5. There was a positive relationship between the predicted number of bird days supported by a landscape over-winter and the breeding population trend for yellowhammer Emberiza citrinella, a species for which survival has been identified as the primary driver of population dynamics, but not for linnet Carduelis cannabina, a species for which productivity has been identified as the primary driver of population dynamics. 6. Synthesis and applications. We believe this model can be used to guide the effective delivery of over-winter food resources under agri-environment schemes and to assess the impacts on granivorous birds of changing resource availability associated with novel changes in land use. This could be very important in the future as farming adapts to an increasingly dynamic trading environment, in which demands for increased agricultural production must be reconciled with objectives for environmental protection, including biodiversity conservation.