To study the association between SCC and bacteria numbers and milk composition in farm bulk milk supplied to Tui Milk Products Company for 1992/3 season : a thesis presented in partial fulfilment of the requirements for the degree of Master of Agricultural Science at Massey University

The association between bulk milk SCC and bacteria numbers and milk composition were studied using data containing test records of 12OO farms which supplied bulk milk to TUI Milk Company Limited, for 1992/93 season. Three data sets were created, (1) data set A (N = 4623) with all measurements recorded for each herd for the same milk sample; (2) data B (N = 30 120) with all measurements of BMSCC and milk composition recorded for each herd within a 10 day period but not necessarily on the same sample of bulk milk; and (3) data set C (N = 33 800) with all measurements of bulk milk bacteria numbers and milk composition recorded for each herd within a 10 day period but not necessarily on the same sample of bulk milk. Correlation was used to determine the association between bulk milk SCC and bacteria numbers and milk composition. Multiple regression analysis was also carried to determine the association between bacteria numbers (dependent variable) and SCC and milk composition for early lactation and whole lactation. The results showed the overall average of the mean BMSCC of 280 000 cells/ml of all the farms studied. Approximately 85 % of the farms supplied bulk milk with SCC 5OO OO0 cells/ml. Both bulk milk SCC and bacteria numbers were higher in early and late parts of lactation. Highly significant but low positive corretations occurred between the mean bulk milk SCC and bacteria number in early (r = o.24; r2 = 0.06; P<0.001) and whole lactation(r = 0.15; r2 = 0.02; p<0.001). Thus 2 to 6 % of the variation observed in bacteria count was accounted for by variation in bulk milk SCC.The mean fat %, protein % and total solids % increased from mid-lactation to the end of lactation. In contrast, the mean lactose % showed a decrease as the lactation progressed. On the average for the whole lactation, low positive correlations occurred between the mean bulk milk SCC and fat % (r = 0.18), protein % (r = 0.26) and total solids % (r = 0.15). However, a moderate but highly significant negative correlation occurred between bulk milk SCC and lactose %(r= -0.43; P<0.001). In conclusion the overall low average BMSCC suggests that good quality bulk milk was supplied to the company, which also meets the EC standards. Significant low correlation between BMSCC and bacteria numbers suggests that mastitis bacteria were only a small but significant contributor to the high bacteria count in the bulk milk particularly in early lactation, with dirty milking machines or poor cooling being the most likely major contributor. Finally, lactose % was more sensitive to mastitis effective than fat %, protein % and total solids % in the bulk milk

Taxation and Fiscal Reform in Ghana

Fiscal policy, Taxation, Ghana, Sub-Saharan Africa

Household Water Coping Behaviour and Costs in the Volta Basin of Ghana

Ghana is abundant in water resources but frequently experiences seasonal and periodic water scarcities. Households therefore adopt coping strategies and various activities to ensure continuous flow of adequate safe water at the household level. These strategies involve opportunity costs and some amount of financial outlay. Using revealed preference data for 20 randomly selected rural communities in the Volta basin of Ghana this paper employs the coping costs approach to derive the costs of coping with water insecurity. Explicit costs in the form of investments in water storage facilities and costs of water treatment are estimated. Implicit costs (opportunity cost of time) associated with water collection, which varies by season and ecological zone, is valued using the average basic hourly wage of rural women engaged in agriculture. The results of the study show that costs of coping with water insecurity are higher in the dry season and for forest ecology households. The often-stated claim that rural households cannot and should not pay for the full cost of water delivery is not supported by this study. The paper concludes that rural consumers are paying at least as much as their urban consumers for unimproved water. Hence, this paper is of the view that rural consumers have the ability to pay for improved water but may not be willing to do so probably due to their perceptions and attitudes concerning the public good nature and benefits of improved water supply.Resource /Energy Economics and Policy,

The HIPC Initiative and Poverty Reduction in Ghana: An Assessment

Debt , Poverty reduction, Government expenditure

Tax Reforms in Ghana

tax reforms, poverty, Ghana

Classical r-matrices via semidualisation

We study the interplay between double cross sum decompositions of a given Lie algebra and classical r-matrices for its semidual. For a class of Lie algebras which can be obtained by a process of generalised complexification we derive an expression for classical r-matrices of the semidual Lie bialgebra in terms of the data which determines the decomposition of the original Lie algebra. Applied to the local isometry Lie algebras arising in three-dimensional gravity, decomposition and semidualisation yields the main class of non-trivial r-matrices for the Euclidean and Poincare group in three dimensions. In addition, the construction links the r-matrices with the Bianchi classification of three dimensional real Lie algebras.Comment: 21 pages, 1 figure, typos correcte

Classical r-matrices for the generalised Chern-Simons formulation of 3d gravity

We study the conditions for classical r-matrices to be compatible with the generalised Chern-Simons action for 3d gravity. Compatibility means solving the classical Yang-Baxter equations with a prescribed symmetric part for each of the real Lie algebras and bilinear pairings arising in the generalised Chern-Simons action. We give a new construction of r-matrices via a generalised complexification and derive a non-linear set of matrix equations determining the most general compatible r-matrix. We exhibit new families of solutions and show that they contain known solutions for special parameter valuesComment: 20 pages, minor corrections and comments added in v

Relevance of Health-Related Hashtags on Twitter: A Text Mining Approach

BACKGROUND Social media platforms facilitate user interaction and impact decision making. Users prefer to use hashtags while sharing posts. Knowing the sentiment towards diabetes, bloodpressure, and obesity is fundamental to understanding the impact of these information on patients and their families. The study seeks to determine the relevance of health-related hashtags on Twitter and analyze sentiments about diabetes, obesity, blood pressure. METHOD Tweets were retrieved using synonyms for “diabetes”, “hypertension” and “obesity”. The extended knowledge discovery in data mining (KDDM) model guided our research with research objectives defined in the ‘research problem understanding’ phase. The ‘information seeking’ from Uses and Gratifications Theory (UGT) determined the success and text mining assessment criteria. Text pre-processing was done using tokenization, stop word removal, and stemming. The research objectives, text mining goals, and success criteria were answered using ‘Uses and Gratifications Theory’ (UGT). RESULTS Total 6749 tweets were extracted using RStudio. 36.41% were about blood pressure, 0.25%- diabetes, 24.43% -obesity and 6.99% -combination of two or more terms. Additional topics such as cholesterol, chia seeds, postpartum, diet, exercise were identified. Upcoming conferences like ‘#ipna’, ‘#review’, ‘#APCH2019’, ‘#cardiotwitter’ were identified. Increased user engagement – about managing blood pressure, diabetes, obesity across different age groups, as well as the consequences of increased cardio exercise for obese and diabetic users were encouraging. Tweets about advertisements specific to clothing for oversized individuals-initiated conversation among users about monitoring self-health. CONCLUSIONS Sentiment analysis can thus increase our understanding about user engagement on such platforms and potentially help improve managing public health strategically.https://scholarscompass.vcu.edu/gradposters/1105/thumbnail.jp