9,061 research outputs found
Porcine reproductive and respiratory syndrome virus (PRRSV) in GB pig herds : farm characteristics associated with heterogeneity in seroprevalence
Background: The between- and within-herd variability of porcine reproductive and respiratory syndrome virus (PRRSV) antibodies were investigated in a cross-sectional study of 103 British pig herds conducted 2003–2004. Fifty pigs from each farm were tested for anti-PRRSV antibodies using
ELISA. A binomial logistic model was used to investigate management risks for farms with and without pigs with PRRSV antibodies and multilevel statistical models were used to investigate variability in pigs' log ELISA IRPC (relative index × 100) in positive herds.
Results: Thirty-five herds (34.0%) were seronegative, 41 (39.8%) were seropositive and 27 (26.2%) were vaccinated. Herds were more likely to be seronegative if they had < 250 sows (OR 3.86 (95% CI 1.46, 10.19)) and if the nearest pig herd was ≥ 2 miles away (OR 3.42 (95% CI 1.29, 9.12)). The
mean log IRPC in seropositive herds was 3.02 (range, 0.83 – 5.58). Sixteen seropositive herds had only seropositive adult pigs. In these herds, pigs had -0.06 (95% CI -0.10, -0.01) lower log IRPC for every mile increase in distance to the nearest pig unit, and -0.56 (95% CI -1.02, -0.10) lower log IRPC when quarantine facilities were present. For 25 herds with seropositive young stock and adults, lower log IRPC were associated with isolating purchased stock for ≥ 6 days (coefficient - 0.46, 95% CI -0.81, -0.11), requesting ≥ 48 hours 'pig-free time' from humans (coefficient -0.44, 95% CI -0.79, -0.10) and purchasing gilts (coefficient -0.61, 95% CI -0.92, -0.29).
Conclusion: These patterns are consistent with PRRSV failing to persist indefinitely on some infected farms, with fadeout more likely in smaller herds with little/no reintroduction of infectious stock. Persistence of infection may be associated with large herds in pig-dense regions with repeated reintroduction
The control of Corynebacterium pseudotuberculosis infection in sheep flocks : a mathematical model of the impact of vaccination, serological testing, clinical examination and lancing of abscesses
A mathematical model of Corynebacterium pseudotuberculosis infection in sheep flocks was used to evaluate strategies for control and elimination of caseous lymphadenitis (CIA). Control strategies tested were vaccination, serological testing and removal of seropositives, clinical examination and removal of sheep with abscesses, lancing abscesses, and appropriate combinations. Three different infection rates with and without replacement of culled ewes were used to evaluate the control options. Controls were either implemented immediately after infection was detected in a flock or once CIA was at endemic equilibrium, and with different frequencies of examination or testing. Elimination of infection was defined as 99% confidence that no sheep were infected with C. pseudo tuberculosis. The control strategies were evaluated by estimating the reduction in infection or probability of elimination and the number of ewes culled from the flock.
Lancing abscesses reduced the prevalence of infection when the initial prevalence was 0.90, but vaccination combined with clinical examination reduced infection rapidly with little impact on lamb productivity. Further research is required to develop a diagnostic test with at least 0.90 specificity and sensitivity under field conditions before any methods of control can be recommended with confidence
Evaluation activity in the conceptual phase of the engineering design process
Chapter 4 describes the synthesis and development of a Conceptual Design Evaluation Method (CDEM) that is an amalgam of a number of methods and approaches taken principally from the probability, reliability, and quality domains. Decomposition of design is employed to enable evaluation at design characteristic level with the total design evaluation being achieved via recomposition by means of Conceptual Design Factor Ratings (CDFR) and Conceptual Design Solution Ratings (CDSR).
This methodology is next tested, within a controlled design environment, in order that its validity can be assessed. The experimental approach used is described in Chapter 5. The results of this experiment, which uses students along with technical and academic staff from the Department of Mechanical Engineering at the University of Glasgow as subjects, indicate that the developed Conceptual Design Evaluation Methodology does exhibit validity within the limits of the experimental environment. It is shown that the CDEM can match expert selection of preferred concept options thus offering the potential of enhancing novice capability and of providing advisory support to experienced designers. The experiment also exposes the problem of objectivity in design evaluation however it is also shown that the CDEM approach acts to mitigate against this tendency by effectively reminding the designer of the benefits of a range of conceptual options. In parallel, the experiment also exposes the limits of human objective evaluation in terms of the complexity of criteria addressed as well as the number of conceptual options considered. Once again CDEM is shown to enable evaluative objectivity to be maintained with increasing complexity.
It is also suggested that the CDEM approach is appropriate for a concurrent engineering environment since it displays a capacity to enhance traceability of design decision making. Finally, conclusions are provided regarding the specific outcomes of the described research along with implications for the wider issues of coherent design research strategy and professional engineering design practice
Invariant tensors and cellular categories
Let U be the quantised enveloping algebra associated to a Cartan matrix of
finite type. Let W be the tensor product of a finite list of highest weight
representations of U. Then the centraliser algebra of W has a basis called the
dual canonical basis which gives an integral form. We show that this integral
form is cellular by using results due to Lusztig.Comment: 6 pages; to appear in Journal of Algebr
Cow, farm, and herd management factors in the dry period associated with raised somatic cell counts in early lactation
This study investigated cow characteristics, farm facilities, and herd management strategies during the dry period to examine their joint influence on somatic cell counts (SCC) in early lactation. Data from 52 commercial dairy farms throughout England and Wales were collected over a 2-yr period. For the purpose of analysis, cows were separated into those housed for the dry period (6,419 cow-dry periods) and those at pasture (7,425 cow-dry periods). Bayesian multilevel models were specified with 2 response variables: ln SCC (continuous) and SCC >199,000 cells/mL (binary), both within 30 d of calving. Cow factors associated with an increased SCC after calving were parity, an SCC >199,000 cells/mL in the 60 d before drying off, increasing milk yield 0 to 30 d before drying off, and reduced DIM after calving at the time of SCC estimation. Herd management factors associated with an increased SCC after calving included procedures at drying off, aspects of bedding management, stocking density, and method of pasture grazing. Posterior predictions were used for model assessment, and these indicated that model fit was generally good. The research demonstrated that specific dry-period management strategies have an important influence on SCC in early lactation
Impact of imperfect test sensitivity on determining risk factors : the case of bovine tuberculosis
Background
Imperfect diagnostic testing reduces the power to detect significant predictors in classical cross-sectional studies. Assuming that the misclassification in diagnosis is random this can be dealt with by increasing the sample size of a study. However, the effects of imperfect tests in longitudinal data analyses are not as straightforward to anticipate, especially if the outcome of the test influences behaviour. The aim of this paper is to investigate the impact of imperfect test sensitivity on the determination of predictor variables in a longitudinal study.
Methodology/Principal Findings
To deal with imperfect test sensitivity affecting the response variable, we transformed the observed response variable into a set of possible temporal patterns of true disease status, whose prior probability was a function of the test sensitivity. We fitted a Bayesian discrete time survival model using an MCMC algorithm that treats the true response patterns as unknown parameters in the model. We applied our approach to epidemiological data of bovine tuberculosis outbreaks in England and investigated the effect of reduced test sensitivity in the determination of risk factors for the disease. We found that reduced test sensitivity led to changes to the collection of risk factors associated with the probability of an outbreak that were chosen in the ‘best’ model and to an increase in the uncertainty surrounding the parameter estimates for a model with a fixed set of risk factors that were associated with the response variable.
Conclusions/Significance
We propose a novel algorithm to fit discrete survival models for longitudinal data where values of the response variable are uncertain. When analysing longitudinal data, uncertainty surrounding the response variable will affect the significance of the predictors and should therefore be accounted for either at the design stage by increasing the sample size or at the post analysis stage by conducting appropriate sensitivity analyses
Management of multi-method engineering design research: a case study
There is a need for a research management methodology that will utilise research methods on an individual basis and when combined in a multi-method approach. An agreed methodology would enable rapid progress in achieving agreement on the main issues within engineering design research. Researchers at the University of Glasgow have developed a conceptual management methodology, testing it on three engineering design research projects. This paper describes the methodology and presents results indicating its ability to enable rigorous triangulation of research results obtained via different methods and across different research projects forming the basis of an effective management tool
The Mod-2 Cohomology Ring of the Third Conway Group is Cohen-Macaulay
By explicit machine computation we obtain the mod-2 cohomology ring of the
third Conway group Co_3. It is Cohen-Macaulay, has dimension 4, and is detected
on the maximal elementary abelian 2-subgroups.Comment: 12 pages; writing style now more concis
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