Objective 1 was to investigate effects of heat stress and breed on milk and component yield for Holstein and Jersey cows on the same farm. Objective 2 was to determine the effects of breed on udder health as measured by somatic cell count (SCC) during times of heat stress. Data were collected from DHIA records of 142 Jersey cows and 586 Holstein cows from the University herd at Mississippi State University. During heat stress Jersey milk yield and 4% fat corrected milk (FCM) increased (P<0.01). Holstein milk yield and FCM decreased during heat stress (P<0.01). Heat stress affected somatic cell count (SCC) although effects varied by intensity of heat stress. Breed did not have an affect on SCC. Milk fat and protein percentages declined for both breeds in heat stress conditions. Milk fat but not milk protein of Jersey cows increased as stress increased from mild to severe.

In this episode, we visit some ancient Sumerians so we can expand our view of finger counting and see how this applies to counting with transistors. From this, we will have the basis for unsigned binary integers and the humble binary digit or bit. We also show how to calculate the upper limit to which a fixed number of transistors can count.

The evaluation of policy-relevant economic research requires an ethical foundation. Classical liberal theory provides the requisite foundation for this dissertation, which uses various econometric tools to estimate the effects of shifting some of the property tax from buildings to land in 15 cities in Pennsylvania. Economic theory predicts that such a shift will lead to higher building activity. However, this prediction has been supported little by empirical evidence so far. The first part of the dissertation examines the effect of the land-building tax differential on the number of building permits that were issued in 219 municipalities in Pennsylvania between 1972 and 1994. For such count data a conventional analysis based on a continuous distribution leads to incorrect results; a discrete maximum likelihood analysis with a negative binomial distribution is more appropriate. Two models, a non-linear and a fixed effects model, are developed to examine the influence of the tax differential. Both models suggest that this influence is positive, albeit not statistically significant. Application of maximum likelihood techniques is computationally cumbersome if the assumed distribution of the data cannot be written in closed form. The negative binomial distribution is the only discrete distribution with a variance that is larger than its mean that can easily be applied, although it might not be the best approximation of the true distribution of the data. The second part of the dissertation uses a Markov Chain Monte Carlo method to examine the influence of the tax differential on the number of building permits, under the assumption that building permits are generated by a Poisson process whose parameter varies lognormally. Contrary to the analysis in the first part, the tax is shown to have a strong and significantly positive impact on the number of permits. The third part of the dissertation uses a fixed-effects weighted least squares method to estimate the effect of the tax differential on the value per building permit. The tax coefficient is not significantly different from zero. Still, the overall impact of the tax differential on the total value of construction is shown to be positive and statistically significant. / Ph. D.

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Analyses based upon rank correlation methods, such as Spearman's Rho and Kendall's Tau, can provide quick insights into large biological data sets. Comparing expression levels between different technologies and models is problematic due to the different units of measure. Here again, rank correlation provides an effective means of comparison between the two techniques. Massively Parallel Signature Sequencing (MPSS) transcript abundance levels to microarray signal intensities for Arabidopsis thaliana are compared. Rank correlations can be applied to subsets as well as the entire set. Results of subset comparisons can be used to improve the capabilities of predictive models, such as Predicted Highly Expressed (PHX). This is done for Escherichia coli. Methods are given to combine predictive models based upon feedback from experimental data. The problem of feature selection in supervised learning situations is also considered, where all features are drawn from a common domain and are best interpreted via ordinal comparisons with other features, rather than as numerical values. This is done for synthetic data as well as for microarray experiments examining the life cycle of Drosophila melanogaster and human leukemia cells. Two novel methods are presented based upon Rho and Tau, and their efficacy is tested with synthetic and real world data. The method based upon Spearman's Rho is shown to be more effective. / Ph. D.

Vårdrelaterade infektioner (VRI) är ett ökande problem inom hälso- och sjukvården. På neonatalavdelningen på Länssjukhuset Ryhov i Jönköping har det förekommit inkonsekventa odlingsresultat vid misstänkt VRI orsakad av Staphylococcus aureus. Att förebygga VRI samt värna om patientsäkerheten kräver känsliga och pålitliga laboratorieanalyser. Syftet med studien var att bestämma och jämföra lägsta detektionsintervall för metoderna odling och qPCR med och utan anrikning i MAMSA-buljong, av S. aureus. Seriespädningar av S. aureus tillreddes och koncentrationer för ursprungsrören uträknades via viable count (VC). Odling på blodagar samt qPCR med och utan anrikning i MAMSA-buljong utfördes. Resultaten användes för att bestämma ett lägsta detektionsintervall. Odling gav ett lägsta detektionsintervall mellan 0,5–62 CFU/ml, och qPCR mellan 6400–140 000 CFU/ml. Anrikning med MAMSA-buljong innan qPCR-analys gav ett lägsta detektionsintervall mellan 0,6–140 CFU/ml. För detektion via odling räcker enstaka till tiotals CFU/ml i analysprovet. Vid qPCR behövs tusentals till hundratusentals CFU/ml i analysprovet, men vid qPCR med MAMSA-anrikning kan detektionsintervallet sänkas till nivåer jämförbara med odling. För att kunna applicera studiens resultat på den laborativa verksamheten krävs vidare studier med fler bakteriearter och replikat. / Hospital-acquired infections (HAI) are an increasing problem in health care facilities. In the neonatal intensive care unit at Länssjukhuset Ryhov in Jönköping, inconsistent cultivation results have been observed for suspected HAI caused by Staphylococcus aureus. To prevent HAI and to maintain patient safety, sensitive and reliable laboratory tests are essential. The aim of the study was to determine and compare the lowest range of detection for cultivation and qPCR with and without enrichment in MAMSA broth, for S. aureus. Serial dilutions of S. aureus were made, and the original concentration was determined through viable count. Cultivation on blood agar and qPCR with and without enrichment in MAMSA broth was performed. The results were used to determine a minimum detection range. For cultivation, a minimum detection range of 0,5–62 CFU/ml was determined and for qPCR a range of 6400–140 000 CFU/ml. For qPCR after enrichment in MAMSA broth, a lowest detection range of 0,6–140 CFU/ml was determined. For detection with cultivation single to tenths of CFU/ml were needed in the sample. For qPCR thousands to tenths of thousands of CFU/ml were needed. For qPCR with enrichment in MAMSA broth the detection range could be lowered to levels comparable with cultivation. For clinical application, further studies are needed with more bacterial species and replicates.

O objetivo do trabalho foi avaliar a utilização da metodologia de citometria de fluxo na determinação da contagem bacteriana total (CBT) do leite cru. No primeiro estudo foi avaliado o efeito da temperatura de armazenamento, da idade da amostra e do tipo conservante sobre a CBT. Também foi estudada a possibilidade de se utilizar uma única amostra de leite para a realização das análises previstas na Instrução Normativa 51 (IN-51). Foram testadas, três temperaturas de armazenamento (0oC - congelado, 7oC - resfriamento e 24 oC - ambiente), três conservantes (bronopol, azidiol e sem conservante) e quatro tempos entre a coleta e a análise (idade da amostra) (um (D1), três (D3), cinco (D5) e sete (D7) dias). Foi considerado tratamento controle para análise de CBT, amostras refrigeradas, com azidiol e com um dia de idade. Para as análises de composição e CCS, o tratamento controle foram amostras refrigeradas, com bronopol e com um dia de idade. Os resultados indicaram que será necessária a coleta de duas amostras, uma destinada à determinação de CCS e composição, contendo bronopol e, outra, para CBT, contendo azidiol. A amostra para CBT poderá ser analisada em até sete dias após a coleta, desde que mantida sob refrigeração à 7ºC. Deve-se evitar o aquecimento ou o congelamento da amostra para CBT, bem como garantir a adição do azidiol. O segundo estudo teve como objetivo estabelecer a correlação entre os métodos de referência e de citometria de fluxo na determinação da CBT. Amostras coletadas nos meses de junho à setembro (n=155) foram agrupadas considerando-se estação da seca e as coletadas nos meses de novembro e dezembro (n=68), estação das águas. Foram realizadas análises simultâneas pelos métodos de referência (contagem padrão em placas) e de citometria de fluxo (equipamento Bactocount), sendo os resultados expressos em unidades formadoras de colônia (UFC) e contagem individual de bactérias (CIB), respectivamente. As equações lineares de correlação entre a CIB e UFC foram semelhantes nas estações, indicando que uma única equação pode ser utilizada ao longo do ano para transformar os resultados de CIB para UFC. A equação linear obtida foi: log(UFC) = log(CIB) x 0,7224 + 1,4617 com coeficiente de correlação de 0,8125. A acurácia do equipamento Bactocount na estimativa do valor de referência, expressa pelo erro padrão (s(y,x)), foi de 0,309 log UFC/mL. Os resultados mostraram que o equipamento Bactocount pode ser calibrado para expressar os resultados em UFC e com isso ser utilizado no monitoramento da qualidade do leite. / The objective of this study was to evaluate the utilization of electronic flow cytometry to determine total bacterial count (TBC) of raw milk. In the first experiment, the effect of storage temperature, sample age and milk preservative type on TBC were evaluated. Additionally, the use of a single milk sample to performance regulatory milk analysis under the Normative Instruction 51 (NI-51) was tested. Effects were standardized as: three storage temperatures (0ºC - freezer, 7ºC - refrigerator and 24ºC - room temperature), four sample ages (1 (D1), 3 (D3), 5 (D5) and 7 (D7) days) and three milk preservatives (bronopol, azidiol and no preservative). Control treatment for TBC analysis was defined as refrigerated milk samples containing azidiol with 1 day of storage. For determination of milk components and somatic cell count (SCC), control treatment was defined as refrigerated milk samples containing bronopol with 1 day of storage. Results of the first experiment showed that two milk samples are necessary to performance regulatory milk analysis under the NI-51; one containing bronopol should be used for determination of milk components and SCC, and other containing azidiol for TBC. Milk samples used for TBC can be tested until 7 days after sampling when they are kept at 7ºC. Freezing or heating milk samples for TBC analysis should be avoided and addition of azidiol is always necessary. The second experiment was designed to determine a correlation between two methods of TBC, electronic flow cytometry and standard plate count. Milk samples collected from June to September (n = 155) were named as dry season samples and milk samples collected in November and December (n = 68) were named as rainy season samples. Each milk sample was used to run both methods of TBC. Results were expressed as individual bacterial count (IBC) and colony forming unit (CFU) for electronic flow cytometry (Bactocount) and standard plate count, respectively. The linear equations of correlation between IBC and CFU had similar patterns in both seasons, dry and rainy, indicating that a single equation can be used to transform IBC results in CFU along the year. The linear equation was defined as log(CFU) = 0.7224 x log(IBC) + 1.4617 with coefficient of correlation of 0.8125. The accuracy of Bactocount in estimating reference values, denoted by the standard error (s(y,x)), was 0.309 log CFU/mL. The results showed that Bactocount can be calibrated to express TBC readings in CFU and, consequently, be used to monitor milk quality.