Dog breeders invest a lot of time and money into breeding efforts and it is important for veterinarians to assist clients in achieving a successful outcome of a breeding attempt. Being able to predict when a bitch is likely to whelp will assist the owner in managing the pre-parturient bitch optimally—via a well-timed restricted observation period which would allow for a timely intervention, when needed, to prevent unnecessary foetal loss. Studies aimed at predicting the parturition dates in bitches used foetal measurements and applied formulas to specific breeds or bitches in predetermined weight categories. The aim of this study was to predict the parturition date in bitches based on measurements, taken during the ampullary phase of gestation, which are not influenced by the size of the foetus, which in turn is influenced by the breed and size of the sire and dam. Various measurements of extrafoetal fluid compartments of the conceptus in an axial longitudinal view (ALV) and in an equatorial transverse view (ETV) were recorded daily between 17 and 32 days after the onset of cytological dioestrus. Measurements were categorised as direct variables (a measured datum) or relative variables (the relationship between measured data) . A linear function was used to generate models to predict the day of parturition using either the direct or relative predictor variables. Some of the measurements were excluded from the data used to generate the models, and these values were used to test the accuracy of the generated models in predicting the day of parturition in bitches. This study, using the model for direct variables, predicted the day of parturition accurately in 62% of bitches, within one day in 94% of bitches and within two days in all bitches. The model for relative variable predicted the day of parturition within one day in 56% of bitches, within two days in 81% of bitches and within three days in all bitches. / Mini Dissertation (MMedVet)--University of Pretoria, 2020. / Production Animal Studies / MMedVet / Unrestricted

Being able to predict a merger or acquisition before it takes place could lead to an investor earning a premium, if they owned shares of the targeted firm before the merger or acquisition attempt is announced. On average acquiring firms pay a premium when acquiring or merging with a targeted firm. This study uses publicly available financial information for 7,267 attempted takeover targets and 52,343 non-targeted firms for the period January 3, 2000 through December 31, 2007 to estimate (using logit) predictive models. Financial ratios are constructed based on six hypotheses found in the literature. Although statistical evidence supports a few of the hypotheses, the low predictive power of the models does not indicate the ability to accurately predict targeted firms ahead of time, let alone with any economic significance.

To calculate flow or depth in a waterway, it is necessary to accurately determine the flow resistance. Past research has made considerable progress in predicting the roughness of nonvegetated uniform channels based on both theoretical and experimental investigations. However, to determine the flow resistance associated with vegetated compound flow channels and floodplains, the effects of the vegetation must be considered. Recent advancements have led to greater understanding of the effects of partially submerged uniform vegetation in a waterway. However, to accurately determine flow resistance, it is imperative that the effects of both submerged and partially submerged vegetation be taken into account. It is also critical to account for the effects of multiple species and densities of vegetation throughout the waterway. Extensive testing of both partially submerged and fully submerged vegetation was completed in the laboratory. Multiple species were tested together to represent various ecosystems commonly found in floodplains throughout the country. Results of the testing show that both geometric and biomechanical properties of the plants must be accounted for when determining vegetation resistance. Methods and procedures were developed to quantify these properties. Equations were also developed that provide a basis by which to quantify vegetation resistance. The results of this study were compared to several sets of actual field data. The resistance values predicted by the equations were very close to those measured in the field. Use of the developed equations and procedures now provides those involved in the field of flood control a far more accurate tool by which to predict vegetation resistance than was previously available.

No description available.

Individuals with Alzheimer Disease (AD) exhibit deficits across multiple cognitive domains years before clinical diagnosis, when they are in the preclinical stages of the disease. Four studies were conducted to (a) examine the preclinical neuropsychological characteristics of English- and French-speaking Alzheimer Disease (AD) participants from the Canadian Study of Health and Aging (CSHA) and (b) determine the utility of select CSHA neuropsychological and demographic measures in predicting AD over a five-year period. Both English- and French-speaking AD participants demonstrated cognitive changes on episodic memory, verbal fluency, and speeded visuomotor processing tasks five years prior to diagnosis, however declines in performance between initial- and re-assessment were not uniform across these domains for either language group. Advanced age and declines in delayed episodic memory were the most significant indicators of progression to AD over a five-year period for both language groups. A validation study was conducted to investigate how well the predictors of AD prognosticate diagnostic outcome for an independent group of at-risk English-speaking participants. The best predictors of AD for the English-speaking group (age, episodic memory, and speeded visuomotor processing) accurately classified close to 70% of individuals from the at-risk sample. The present findings will contribute to diagnostic decisions regarding AD in older English- and French-speaking Canadian adults.

Individuals with Alzheimer Disease (AD) exhibit deficits across multiple cognitive domains years before clinical diagnosis, when they are in the preclinical stages of the disease. Four studies were conducted to (a) examine the preclinical neuropsychological characteristics of English- and French-speaking Alzheimer Disease (AD) participants from the Canadian Study of Health and Aging (CSHA) and (b) determine the utility of select CSHA neuropsychological and demographic measures in predicting AD over a five-year period. Both English- and French-speaking AD participants demonstrated cognitive changes on episodic memory, verbal fluency, and speeded visuomotor processing tasks five years prior to diagnosis, however declines in performance between initial- and re-assessment were not uniform across these domains for either language group. Advanced age and declines in delayed episodic memory were the most significant indicators of progression to AD over a five-year period for both language groups. A validation study was conducted to investigate how well the predictors of AD prognosticate diagnostic outcome for an independent group of at-risk English-speaking participants. The best predictors of AD for the English-speaking group (age, episodic memory, and speeded visuomotor processing) accurately classified close to 70% of individuals from the at-risk sample. The present findings will contribute to diagnostic decisions regarding AD in older English- and French-speaking Canadian adults.

No description available.

The Dairy industry requires accurate detection of oestrus(heat) in dairy cows to maximise output of the animals. Traditionally this is a process dependant on human observation and interpretation of the various signs of heat. Many areas of the dairy industry can be automated, however the detection of oestrus is an area that still requires human experts. This thesis investigates the application of Machine Learning classification techniques, on dairy cow milking data provided by the Livestock Improvement Corporation, to predict oestrus. The usefulness of various ensemble learning algorithms such as Bagging and Boosting are explored as well as specific skewed data techniques. An empirical study into the effectiveness of classifiers designed to target skewed data is included as a significant part of the investigation. Roughly Balanced Bagging and the novel Under Bagging classifiers are explored in considerable detail and found to perform quite favourably over the SMOTE technique for the datasets selected. This study uses non-dairy, commonplace, Machine Learning datasets; many of which are found in the UCI Machine Learning Repository.

Contrary to traditional teaching, patients with Primary Spontaneous Pneumothorax (PSP) do not have normal lungs. Emphysema-like change (ELC) and inflammation are common. However, the natural history of ELC and its significance in terms of future disease is not known. Current management of pneumothorax is generic and not personalised. This thesis updates the UK epidemiology of pneumothorax, describes the use of two novel methods to examine the lungs, a method of predicting early treatment failure, the association of CT findings and recurrence, and a systematic review of chemical pleurodesis to reduce recurrence. Analysis of fifty years' data on ~150,000 admissions demonstrated that the incidence of pneumothorax is increasing, and established a method to identify primary from secondary pneumothoraces and their relative risk of recurrence. Reduced ventilation of hyperpolarised Xenon on enhanced-Magnetic Resonance Imaging (MRI) was seen in those PSP patients with greater low attenuation areas on Computed Tomography (CT) and with reduced pulmonary function. A model of lung inhomogeneity found that metrics of lung ventilation distinguished pneumothorax patients from healthy volunteers and Chronic Obstructive Pulmonary Disease (COPD) patients. This may represent subtle or mild disease, not identified on standard testing, which may be exacerbated by smoking. CT scanning found that mild emphysema and cystic airspaces were common in PSP patients. Ex- or current smokers had more (and larger) cysts. Emphysema was more common in smokers and patients with a history of previous pneumothorax: who were at higher risk of recurrence. However, variation in number and size of cysts were seen in both those patients with and without recurrence. As such, no single algorithm to predict recurrence was identified. Airflow measurement early in the patient pathway has the potential to identify those likely to fail treatment, potentially allowing early triage to surgery. The addition of talc or minocycline as an adjunct to surgery provides the lowest recurrence rates, but physician-led talc poudrage may be similarly effective. Those in whom surgery is not suitable, chemical pleurodesis could be offered via chest drain. Data presented in this thesis thus provides insights into the underlying abnormalities in PSP and lays the groundwork for strategies to fundamentally alter the management paradigm.

Harmonic vibrational frequencies of several small organic molecules which were used to validate the scaled quantum mechanical (SQM) force field procedure of Pulay et al. were calculated using six popular density functional (DFT) methods and compared with experimental results. The combination of Becke's exchange with either Lee-Yang-Parr (BLYP) or Perdew's correlation functional (BP86) reproduces the observed frequencies satisfactorily with deviations similar to those of the Hartree-Fock SQM methods. Three hybrid DFT methods are found to yield frequencies which were generally higher than the observed fundamental frequencies. When the calculated frequencies were compared with 'experimental' harmonic frequencies however, Becke's three-parameter hybrid method with Lee-Yang-Parr correlation functional is found to be slightly more accurate, especially for C-H stretching modes. The results indicate that BLYP calculation is a very promising approach for understanding the observed spectral features.