The efficacy of neem seed extract (Azadirachta indica) to control tick infestation in Tswana, Simmentaler and Brahman cattle

The aim of this experiment was to evaluate the use of neem seed extract for controlling common cattle ticks of the Ixodidae species. Three bulls and three cows of the Tswana, Brahman and Simmentaler breeds were cleared of ticks using ether and hand-picking techniques. Each animal was then naturally infested with ticks. A 5% (w/v) water extract of neem seed kernel was applied at a rate of 5 g/kg body weight to various anatomical sites on the animals allocated to the experimental treatment, while the control treatment animals were sprayed with tap water. Treated and control animals grazed together and were mustered at weekly intervals for examination. Tick population densities on animals treated with neem seed extract were lower than on untreated animals. Indigenous Tswana cattle harboured fewer ticks during periods of tick abundance than Brahman or Simmentaler cattle. It was concluded that neem seed extract is effective in controlling ectoparasites on livestock. South African Journal of Animal Science Vol.32(1) 2002: 1-

Effect of age and season on sperm morphology of Friesland bulls at an artificial insemination centre in South Africa

No Abstract. South African Journal of Animal Science Vol. 34 (1) 2004: pp.62-6

Effect of electrical stimulation of carcasses from Dorper sheep with two permanent incisors on the consumer acceptance of mutton: review article

The inconsistency in the eating quality characteristics of meats, predominantly tenderness, is probably the most critical problem faced by the meat industry worldwide. Consumers consider tenderness to be the single most important component of meat quality. An alternative method for increasing meat tenderness may exist in the form of electrical stimulation of the carcass shortly following slaughter. The aim of this research was to study the effect of electrical stimulation on the consumer acceptance of, preference for and consumption intent regarding mutton of the recently introduced class-AB sheep carcasses (carcasses from sheep with one to two permanent incisors) in South Africa. A total of 22 wethers of class-AB, weighing between 45 and 50 kg, was selected from a homogeneous group of Dorpers. Carcasses were divided into two groups, one was electrically stimulated (0.4 amp/h for 45 sec) and the other group not stimulated. Samples of the left M. longissimus thoracis et lumborum of both groups were oven roasted and a consumer panel evaluated the acceptability of the mutton regarding certain sensory characteristics. Three consumer sensory tests, namely the hedonic rating of the acceptability of each sensory attribute, a preference test and a food action rating test, were conducted in sequence. The acceptability of the juiciness, tenderness, flavour and overall acceptability were not significantly influenced by the electrical stimulation of carcasses. Samples from both the electrically stimulated and non-stimulated carcasses were highly acceptable to consumers. No significant differences in preference or percentage cooking losses were obtained. The present results indicate that electrical stimulation of class-AB carcasses did not have a significant influence on the consumer's acceptance of, nor consumption intent towards the class-AB mutton. This study shows that consumers revealed a positive attitude by declaring their intention to eat samples from both electrically stimulated and non-electrically stimulated carcasses once a week. Moreover, the variation in shear force values of meat samples from the electrically stimulated group was less compared to that of the non-stimulated group, indicating that electrical stimulation can successfully be applied to reduce the variation in tenderness within the class-AB mutton. Keywords: Class AB-mutton, Electrical stimulation, Consumer acceptance, Tenderness South African Journal of Animal Science Vol.33(3) 2003: 206-21

Effect of selection for lean growth on gonadal development of commercial pig genotypes in South Africa

A primary objective of commercial pig production is lean meat yield in order to satisfy consumer needs. The majority of the commercial pig breeds in South Africa have been selected for high lean growth potential and reduced backfat thickness. There are indications that selection for high lean meat yield may affect the gonadal development and possibly reproductive potential of commercial pig genotypes, because both testicular and ovarian growth appear to be important indicators of reproductive performance in boars and gilts, respectively. The effects of selection for lean growth on gonadal development were studied in five South African commercial pig genotypes (1, 2, 3, 4 and 5) from 116 to 214 days of age. Gonadal growth and development were measured and compared in 112 gilts and 112 boars. Differences between means were tested using genotype and age as fixed effects, while the relationships between gonadal parameters were evaluated by means of correlation analysis. Gilts from genotype 1 had a significantly shorter ovary length than those from genotypes 2 and 3. Gilts from genotype 3 also had heavier ovaries and larger ovary volumes than gilts from genotype 1. However, genotype did not influence ovary width or height. Correlations between P2 backfat thickness and gonadal development were generally poor in gilts. In boars, genotype 3 had significantly heavier testes than boars from genotype 1. Testes volume of genotype 1 also tended to be smaller compared to genotype 3. Correlations between gonadal measurements and P2 backfat thickness of boars were positive and moderately high (0.560 ≤ r ≤ 0.587). It is concluded from the study that there are differences between commercial pig genotypes in terms of gonadal development. These results suggest that selecting against backfat thickness may delay gonadal development and sexual maturation in boars, while the results are not conclusive in sows. Keywords: Pig; growth; backfat thickness; gonadal development; reproduction South African Journal of Animal Science Vol. 36 (5) 2006: pp.26-2

Representing complex data using localized principal components with application to astronomical data

Often the relation between the variables constituting a multivariate data space might be characterized by one or more of the terms: ``nonlinear'', ``branched'', ``disconnected'', ``bended'', ``curved'', ``heterogeneous'', or, more general, ``complex''. In these cases, simple principal component analysis (PCA) as a tool for dimension reduction can fail badly. Of the many alternative approaches proposed so far, local approximations of PCA are among the most promising. This paper will give a short review of localized versions of PCA, focusing on local principal curves and local partitioning algorithms. Furthermore we discuss projections other than the local principal components. When performing local dimension reduction for regression or classification problems it is important to focus not only on the manifold structure of the covariates, but also on the response variable(s). Local principal components only achieve the former, whereas localized regression approaches concentrate on the latter. Local projection directions derived from the partial least squares (PLS) algorithm offer an interesting trade-off between these two objectives. We apply these methods to several real data sets. In particular, we consider simulated astrophysical data from the future Galactic survey mission Gaia.Comment: 25 pages. In "Principal Manifolds for Data Visualization and Dimension Reduction", A. Gorban, B. Kegl, D. Wunsch, and A. Zinovyev (eds), Lecture Notes in Computational Science and Engineering, Springer, 2007, pp. 180--204, http://www.springer.com/dal/home/generic/search/results?SGWID=1-40109-22-173750210-

The convective storm initiation project

Copyright @ 2007 AMSThe Convective Storm Initiation Project (CSIP) is an international project to understand precisely where, when, and how convective clouds form and develop into showers in the mainly maritime environment of southern England. A major aim of CSIP is to compare the results of the very high resolution Met Office weather forecasting model with detailed observations of the early stages of convective clouds and to use the newly gained understanding to improve the predictions of the model. A large array of ground-based instruments plus two instrumented aircraft, from the U.K. National Centre for Atmospheric Science (NCAS) and the German Institute for Meteorology and Climate Research (IMK), Karlsruhe, were deployed in southern England, over an area centered on the meteorological radars at Chilbolton, during the summers of 2004 and 2005. In addition to a variety of ground-based remote-sensing instruments, numerous rawin-sondes were released at one- to two-hourly intervals from six closely spaced sites. The Met Office weather radar network and Meteosat satellite imagery were used to provide context for the observations made by the instruments deployed during CSIP. This article presents an overview of the CSIP field campaign and examples from CSIP of the types of convective initiation phenomena that are typical in the United Kingdom. It shows the way in which certain kinds of observational data are able to reveal these phenomena and gives an explanation of how the analyses of data from the field campaign will be used in the development of an improved very high resolution NWP model for operational use.This work is funded by the National Environment Research Council following an initial award from the HEFCE Joint Infrastructure Fund

A syndrome of altered cardiovascular, craniofacial, neurocognitive and skeletal development caused by mutations in TGFBR1 or TGFBR2

A

Discriminative structural approaches for enzyme active-site prediction

<p>Abstract</p> <p>Background</p> <p>Predicting enzyme active-sites in proteins is an important issue not only for protein sciences but also for a variety of practical applications such as drug design. Because enzyme reaction mechanisms are based on the local structures of enzyme active-sites, various template-based methods that compare local structures in proteins have been developed to date. In comparing such local sites, a simple measurement, RMSD, has been used so far.</p> <p>Results</p> <p>This paper introduces new machine learning algorithms that refine the similarity/deviation for comparison of local structures. The similarity/deviation is applied to two types of applications, single template analysis and multiple template analysis. In the single template analysis, a single template is used as a query to search proteins for active sites, whereas a protein structure is examined as a query to discover the possible active-sites using a set of templates in the multiple template analysis.</p> <p>Conclusions</p> <p>This paper experimentally illustrates that the machine learning algorithms effectively improve the similarity/deviation measurements for both the analyses.</p