Development and validation of an ELISA for detecting antibodies to Eimeria tenella in chickens

The aim of this study was to develop and validate an ELISA for detecting chicken antibodies to Eimeria tenella. An initial comparison of merozoite and sporozoite antigen preparations revealed few differences in their ability to monitor the onset, kinetics and magnitude of the antibody response suggesting that both antigens would be equally useful for development of an ELISA. Furthermore the cross-reactivity of these antigens with sera from birds infected with chicken Eimeria species was similar. The merozoite antigen was selected for further evaluation because it was easier to prepare. Discrimination between sera from birds experimentally infected with E. tenella and birds maintained in an Eimeria-free isolation facility was excellent. In sera collected from free-range layers and commercial broilers there also appeared to be clear discrimination between infected and uninfected birds. The ELISA should prove useful for monitoring infectivity in vaccination programmes in layer and breeder flocks and for assessing the effectiveness of biosecurity measures in broiler flocks.

Validation of a Competitive Enzyme-Linked Immunosorbent Assay for Detection of Babesia bigemina Antibodies in Cattle

A competitive enzyme-linked immunosorbent assay (cELISA) based on a broadly conserved, species-specific, B-cell epitope within the C terminus of Babesia bigemina rhoptry-associated protein 1a was validated for international use. Receiver operating characteristic analysis revealed 16% inhibition as the threshold for a negative result, with an associated specificity of 98.3% and sensitivity of 94.7%. Increasing the threshold to 21% increased the specificity to 100% but modestly decreased the sensitivity to 87.2%. By using 21% inhibition, the positive predictive values ranged from 90.7% (10% prevalence) to 100% (95% prevalence) and the negative predictive values ranged from 97.0% (10% prevalence) to 48.2% (95% prevalence). The assay was able to detect serum antibody as early as 7 days after intravenous inoculation. The cELISA was distributed to five different laboratories along with a reference set of 100 defined bovine serum samples, including known positive, known negative, and field samples. The pairwise concordance among the five laboratories ranged from 100% to 97%, and all kappa values were above 0.8, indicating a high degree of reliability. Overall, the cELISA appears to have the attributes necessary for international application.

Validation-Based Sparse Gaussian Process Classifier Design

Gaussian processes (GPs) are promising Bayesian methods for classification and regression problems. Design of a GP classifier and making predictions using it is, however, computationally demanding, especially when the training set size is large. Sparse GP classifiers are known to overcome this limitation. In this letter, we propose and study a validation-based method for sparse GP classifier design. The proposed method uses a negative log predictive (NLP) loss measure, which is easy to compute for GP models. We use this measure for both basis vector selection and hyperparameter adaptation. The experimental results on several real-world benchmark data sets show better orcomparable generalization performance over existing methods.

Confirmation of QTL mapping and marker validation for partial seedling resistance to crown rot in wheat line '2-49'

We have tested the efficacy of putative microsatellite single sequence repeat (SSR) markers, previously identified in a 2-49 (Gluyas Early/Gala) × Janz doubled haploid wheat (Triticum aestivum) population, as being linked to partial seedling resistance to crown rot disease caused by Fusarium pseudograminearum. The quantitative trait loci (QTLs) delineated by these markers have been tested for linkage to resistance in an independent Gluyas Early × Janz doubled haploid population. The presence of a major QTL on chromosome 1DL (QCr.usq-1D1) and a minor QTL on chromosome 2BS (QCr.usq-2B1) was confirmed. However, a putative minor QTL on chromosome 2A was not confirmed. The QTL on 1D was inherited from Gluyas Early, a direct parent of 2-49, whereas the 2B QTL was inherited from Janz. Three other putative QTLs identified in 2-49 × Janz (on 1AL, 4BL, and 7BS) were inherited by 2-49 from Gala and were not able to be confirmed in this study. The screening of SSR markers on a small sample of elite wheat genotypes indicated that not all of the most tightly linked SSR markers flanking the major QTLs on 1D and 1A were polymorphic in all backgrounds, indicating the need for additional flanking markers when backcrossing into some elite pedigrees. Comparison of SSR haplotypes with those of other genotypes exhibiting partial crown rot resistance suggests that additional, novel sources of crown rot resistance are available.

Expert Identity in Development of Core-Task-Oriented Working Practices for Mastering Demanding Situations

The point of departure in this dissertation was the practical safety problem of unanticipated, unfamiliar events and unexpected changes in the environment, the demanding situations which the operators should take care of in the complex socio-technical systems. The aim of this thesis was to increase the understanding of demanding situations and of the resources for coping with these situations by presenting a new construct, a conceptual model called Expert Identity (ExId) as a way to open up new solutions to the problem of demanding situations and by testing the model in empirical studies on operator work. The premises of the Core-Task Analysis (CTA) framework were adopted as a starting point: core-task oriented working practices promote the system efficiency (incl. safety, productivity and well-being targets) and that should be supported. The negative effects of stress were summarised and the possible countermeasures related to the operators' personal resources such as experience, expertise, sense of control, conceptions of work and self etc. were considered. ExId was proposed as a way to bring emotional-energetic depth into the work analysis and to supplement CTA-based practical methods to discover development challenges and to contribute to the development of complex socio-technical systems. The potential of ExId to promote understanding of operator work was demonstrated in the context of the six empirical studies on operator work. Each of these studies had its own practical objectives within the corresponding quite broad focuses of the studies. The concluding research questions were: 1) Are the assumptions made in ExId on the basis of the different theories and previous studies supported by the empirical findings? 2) Does the ExId construct promote understanding of the operator work in empirical studies? 3) What are the strengths and weaknesses of the ExId construct? The layers and the assumptions of the development of expert identity appeared to gain evidence. The new conceptual model worked as a part of an analysis of different kinds of data, as a part of different methods used for different purposes, in different work contexts. The results showed that the operators had problems in taking care of the core task resulting from the discrepancy between the demands and resources (either personal or external). The changes of work, the difficulties in reaching the real content of work in the organisation and the limits of the practical means of support had complicated the problem and limited the possibilities of the development actions within the case organisations. Personal resources seemed to be sensitive to the changes, adaptation is taking place, but not deeply or quickly enough. Furthermore, the results showed several characteristics of the studied contexts that complicated the operators' possibilities to grow into or with the demands and to develop practices, expertise and expert identity matching the core task. They were: discontinuation of the work demands, discrepancy between conceptions of work held in the other parts of organisation, visions and the reality faced by the operators, emphasis on the individual efforts and situational solutions. The potential of ExId to open up new paths to solving the problem of the demanding situations and its ability to enable studies on practices in the field was considered in the discussion. The results were interpreted as promising enough to encourage the conduction of further studies on ExId. This dissertation proposes especially contribution to supporting the workers in recognising the changing demands and their possibilities for growing with them when aiming to support human performance in complex socio-technical systems, both in designing the systems and solving the existing problems.

Influence of validation schemes in a laser Doppler anemometer period timing device for frequency measurement

The short duration of the Doppler signal and noise content in it necessitate a validation scheme to be incorporated in the electronic processor used for frequency measurement, There are several different validation schemes that can be employed in period timing devices. A detailed study of the influence of these validation schemes on the measured frequency has been reported here. These studies were carried out by using a combination of a fast A/D converter and computer. Doppler bursts obtained from an air flow were digitised and stored on magnetic discs. Suitable computer programs were then used to simulate the performance of period timing devices with different validation schemes and the frequency of the stored bursts were evaluated. It is found that best results are obtained when the validation scheme enables frequency measurement to be made over a large number of cycles within the burst.

Sexing Sirenians: Validation of Visual and Molecular Sex Determination in Both Wild Dugongs (Dugong dugon) and Florida Manatees (Trichechus manatus latirostris)

Sexing wild marine mammals that show little to no sexual dimorphism is challenging. For sirenians that are difficult to catch or approach closely, molecular sexing from tissue biopsies offers an alternative method to visual discrimination. This paper reports the results of a field study to validate the use of two sexing methods: (1) visual discrimination of sex vs (2) molecular sexing based on a multiplex PCR assay which amplifies the male-specific SRY gene and differentiates ZFX and ZFY gametologues. Skin samples from 628 dugongs (Dugong dugon) and 100 Florida manatees (Trichechus manatus latirostris) were analysed and assigned as male or female based on molecular sex. These individuals were also assigned a sex based on either direct observation of the genitalia and/or the association of the individual with a calf. Individuals of both species showed 93 to 96% congruence between visual and molecular sexing. For the remaining 4 to 7%, the discrepancies could be explained by human error. To mitigate this error rate, we recommend using both of these robust techniques, with routine inclusion of sex primers into microsatellite panels employed for identity, along with trained field observers and stringent sample handling.

Validation and development of PigBal model

This project involves validating and upgrading the PigBal model to improve the accuracy of manure production predictions from intensive piggery operations.

Eliciting and encoding expert knowledge on variable selection into classical or Bayesian species distribution models

The quality of species distribution models (SDMs) relies to a large degree on the quality of the input data, from bioclimatic indices to environmental and habitat descriptors (Austin, 2002). Recent reviews of SDM techniques, have sought to optimize predictive performance e.g. Elith et al., 2006. In general SDMs employ one of three approaches to variable selection. The simplest approach relies on the expert to select the variables, as in environmental niche models Nix, 1986 or a generalized linear model without variable selection (Miller and Franklin, 2002). A second approach explicitly incorporates variable selection into model fitting, which allows examination of particular combinations of variables. Examples include generalized linear or additive models with variable selection (Hastie et al. 2002); or classification trees with complexity or model based pruning (Breiman et al., 1984, Zeileis, 2008). A third approach uses model averaging, to summarize the overall contribution of a variable, without considering particular combinations. Examples include neural networks, boosted or bagged regression trees and Maximum Entropy as compared in Elith et al. 2006. Typically, users of SDMs will either consider a small number of variable sets, via the first approach, or else supply all of the candidate variables (often numbering more than a hundred) to the second or third approaches. Bayesian SDMs exist, with several methods for eliciting and encoding priors on model parameters (see review in Low Choy et al. 2010). However few methods have been published for informative variable selection; one example is Bayesian trees (O’Leary 2008). Here we report an elicitation protocol that helps makes explicit a priori expert judgements on the quality of candidate variables. This protocol can be flexibly applied to any of the three approaches to variable selection, described above, Bayesian or otherwise. We demonstrate how this information can be obtained then used to guide variable selection in classical or machine learning SDMs, or to define priors within Bayesian SDMs.

Validation and development of PigBal model - Stage 2

The proposed project involves validate and upgrading the PigBal model to improve the accuracy of manure and GHG production predictions.

Ageing validation of northern carp populations

The Carp is considered a threat to our native river fish and ecosystems by its ability to adapt to almost any fresh water body and through its feeding and breeding habits, change environmental parameters such as turbidity, light and water temperatures. This project forms part of the Invasive Animal CRC's freshwater program and is part of a strategy to develop control measures for carp. The age and size at maturity for carp in the northern part of their range (ie. Queensland) is currently unknown.

Automatic Lameness Detection in a Milking Robot : Instrumentation, measurement software, algorithms for data analysis and a neural network model

The aim of this thesis is to develop a fully automatic lameness detection system that operates in a milking robot. The instrumentation, measurement software, algorithms for data analysis and a neural network model for lameness detection were developed. Automatic milking has become a common practice in dairy husbandry, and in the year 2006 about 4000 farms worldwide used over 6000 milking robots. There is a worldwide movement with the objective of fully automating every process from feeding to milking. Increase in automation is a consequence of increasing farm sizes, the demand for more efficient production and the growth of labour costs. As the level of automation increases, the time that the cattle keeper uses for monitoring animals often decreases. This has created a need for systems for automatically monitoring the health of farm animals. The popularity of milking robots also offers a new and unique possibility to monitor animals in a single confined space up to four times daily. Lameness is a crucial welfare issue in the modern dairy industry. Limb disorders cause serious welfare, health and economic problems especially in loose housing of cattle. Lameness causes losses in milk production and leads to early culling of animals. These costs could be reduced with early identification and treatment. At present, only a few methods for automatically detecting lameness have been developed, and the most common methods used for lameness detection and assessment are various visual locomotion scoring systems. The problem with locomotion scoring is that it needs experience to be conducted properly, it is labour intensive as an on-farm method and the results are subjective. A four balance system for measuring the leg load distribution of dairy cows during milking in order to detect lameness was developed and set up in the University of Helsinki Research farm Suitia. The leg weights of 73 cows were successfully recorded during almost 10,000 robotic milkings over a period of 5 months. The cows were locomotion scored weekly, and the lame cows were inspected clinically for hoof lesions. Unsuccessful measurements, caused by cows standing outside the balances, were removed from the data with a special algorithm, and the mean leg loads and the number of kicks during milking was calculated. In order to develop an expert system to automatically detect lameness cases, a model was needed. A probabilistic neural network (PNN) classifier model was chosen for the task. The data was divided in two parts and 5,074 measurements from 37 cows were used to train the model. The operation of the model was evaluated for its ability to detect lameness in the validating dataset, which had 4,868 measurements from 36 cows. The model was able to classify 96% of the measurements correctly as sound or lame cows, and 100% of the lameness cases in the validation data were identified. The number of measurements causing false alarms was 1.1%. The developed model has the potential to be used for on-farm decision support and can be used in a real-time lameness monitoring system.

Validation of a partial coherence interferometry method for estimating retinal shape

To validate a simple partial coherence interferometry (PCI) based retinal shape method, estimates of retinal shape were determined in 60 young adults using off-axis PCI, with three stages of modeling using variants of the Le Grand model eye, and magnetic resonance imaging (MRI). Stage 1 and 2 involved a basic model eye without and with surface ray deviation, respectively and Stage 3 used model with individual ocular biometry and ray deviation at surfaces. Considering the theoretical uncertainty of MRI (12-14%), the results of the study indicate good agreement between MRI and all three stages of PCI modeling with <4% and <7% differences in retinal shapes along horizontal and vertical meridians, respectively. Stage 2 and Stage 3 gave slightly different retinal co-ordinates than Stage 1 and we recommend the intermediate Stage 2 as providing a simple and valid method of determining retinal shape from PCI data.

Development and preliminary validation of the Drinking Expectancy Sexual Vulnerabilities Questionnaire (DESV-Q): A purpose-specific instrument for rape-perception research

Background Alcohol expectancies likely play a role in people’s perceptions of alcohol-involved sexual violence. However, no appropriate measure exists to examine this link comprehensively. Objective The aim of this research was to develop an alcohol expectancy measure which captures young adults’ beliefs about alcohol’s role in sexual aggression and victimization. Method Two cross-sectional samples of young Australian adults (18–25 years) were recruited for scale development (Phase 1) and scale validation (Phase 2). In Phase 1, participants (N = 201; 38.3% males) completed an online survey with an initial pool of alcohol expectancy items stated in terms of three targets (self, men, women) to identify the scale’s factor structure and most effective items. A revised alcohol expectancy scale was then administered online to 322 young adults (39.6% males) in Phase 2. To assess the predictive, convergent, and discriminant validity of the scale, participants also completed established measures of personality, social desirability, alcohol use, general and context-specific alcohol expectancies, and impulsiveness. Results Principal axis factoring (Phase 1) and confirmatory factor analysis (Phase 2) resulted in a target-equivalent five-factor structure for the final 66-item Drinking Expectancy Sexual Vulnerabilities Questionnaire (DESV-Q). The factors were labeled: - (1) Sexual Coercion - (2) Sexual Vulnerability - (3) Confidence - (4) Self-Centeredness - (5) Negative Cognitive and Behavioral Changes The measure demonstrated effective items, high internal consistency, and satisfactory predictive, convergent, and discriminant validity. Conclusions The DESV-Q is a purpose-specific instrument that could be used in future research to elucidate people’s attributions for alcohol-involved sexual aggression and victimization.