Na área da saúde, várias abordagens nos últimos anos têm sido propostas baseadas nos gráficos de controle CUSUM para a detecção de epidemias infecciosas em que a caraterística a ser monitorada é uma série temporal de dados de contagem, como o número de internações. Neste trabalho foram implementados os modelos lineares generalizados (MLG) no monitoramento, por meio dos gráficos CUSUM e Shewhart, da série do número diário de internações por causas respiratórias para pessoas com 65 anos ou mais residentes no município de São Paulo. Por meio de simulações, avaliaram-se a eficiência de cinco estatísticas diferentes para detectar mudanças na média em séries de contagem. Uma das abordagens consistiu na implementação de três transformações normalizadoras simples que dependem unicamente dos parâmetros das distribuições Poisson e binomial negativa: a transformação Rossi para dados com distribuição Poisson, a transformação Jorgensen para dados com distribuição binomial negativa e os sesíduos de Anscombe para modelos lineares generalizados. As duas últimas estatísticas já foram propostas como gráficos CUSUM: o Método Rogerson e Yamada (2004) é apresentado para dados com distribuição Poisson e neste trabalho foi proposto um novo parâmetro kt para dados binomial negativa; já o método proposto por Hohle (2007) é baseado na função de verossimilhança da distribuição binomial negativa. Utilizando limites de controle para obter um valor ARL0 = 500 sob normalidade, monitorou-se via simulação a série de interesse, implementando as transformações normalizadoras. Entretanto, utilizando-se esses limiares observa-se um maior número de alarmes falsos para as três estatísticas. Modificando o parâmetro k do gráfico CUSUM permitindo que variasse ao longo do tempo a série foi monitorada e foram obtidos valores ARL0 próximos a 500. Os gráficos CUSUM baseados no método Rogerson e Yamada e na estatística da razão de verossimilhanças para dados com distribuição binomial negativa mostraram, via simulação, bons resultados para detectar mudanças na média. As suposições de normalidade e independência das estatísticas normalizadoras, em geral omitidas em trabalhos publicados na literatura, foram avaliadas e comprova-se que as transformações não normalizam os dados, porém são independentes e estacionárias. Analisando os dados reais, as estatísticas apresentaram autocorrelação significativa no lag 7. Devido à persistência desta autocorrelação, foi proposta uma abordagem baseada no ajuste do modelo GARMA. / In public health several approaches have been proposed for the detection of outbreaks of infectious diseases where the characteristic being monitored is a time series of count data as the number of hospitalizations, where the population and the expected rate of admissions change over time. In this work we fitted generalized linear models (GLM) and implemented Shewhart and CUSUM control charts for monitoring the daily number of hospital admissions due to respiratory diseases for people aged 65 and older in the city of São Paulo. Through simulations, we evaluated the efficiency of implementing five different statistical for detecting changes in time series of count. One approach consisted of applying three transformations that only depend on the parameters of the negative binomial and Poisson distributions: The transformations of Rossi for data with Poisson distribution, the transformation proposed by Jorgensen for data with negative binomial distribution and residuals proposed by Anscombe for generalized linear models. The other statistics have been proposed as CUSUM charts: the method of Rogerson e Yamada (2004) was presented for data with Poisson distribution, in this work we proposed a new parameter kt for negative binomial distribution, the proposed method for Hohle (2007) uses the likelihood ratio statistic. Implementing limit control assuming normality for a value of ARL0 = 500 be monitored via simulation the serie of interest implementing the normalizing statistics. However, using these limits was observed a greater number of alarms for the three transformations. Modifying the parameter k of the CUSUM chart to this change over time the series was monitored and were obtained values of ARL0 close to 500. The CUSUM control charts for the methods of Rogerson and Yamada and Holhe for data with negative binomial distribution showed, by simulation, good results for detecting changes in the mean. For negative binomial distribution generalizing the method of Rogerson e Yamada (2004) and implemented the CUSUM charts using the likelihood ratio statistic. Both methods provided good results via simulation to detect small changes in average. The evaluation of assumptions of normality for the statistics proposed by Rossi, Jorgensen and Anscombe generally is omitted in published studies. In this work, we evaluated this assumptions indicating that the statistics are not normal using the real dataset but are independent and stationary. By analyzing real data, due to the persistence of correlation for the normalized statistics, an approach based on setting GARMA model was proposed. This method showed good results once the residuals of the fitted model were normal and independent. Due to the persistence of correlation for the normalized statistics, an approach based on setting GARMA model was proposed. This method showed good results once the residuals of the fitted model were normal and independent.

Made available in DSpace on 2014-06-11T19:31:02Z (GMT). No. of bitstreams: 0 Previous issue date: 2011-12-20Bitstream added on 2014-06-13T20:21:42Z : No. of bitstreams: 1 cordeiro_mas_dr_jabo.pdf: 669942 bytes, checksum: 4e7ed86e9e941030576119cc7eb6df3e (MD5) / Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Sistemas conservacionistas favorecem as populações microbianas em função da conservação e do aumento da matéria orgânica no solo. As plantas desses sistemas favorecem o crescimento dos microrganismos principalmente pela influência das raízes, através do efeito rizosférico. O objetivo deste trabalho foi avaliar o efeito da rotação de culturas inverno (milho, girassol e guandu) e sequências de verão (soja/milho, milho/milho e soja/soja), em um sistema de semeadura direta, na atividade enzimática e atributos químicos em solo rizosférico e não rizosférico; na contagem dos fungos e bactérias do solo rizosférico e não rizosférico; e na habilidade metabólica dos fungos isolados do solo rizosférico atribuída à promoção de crescimento de plantas. O estudo foi realizado na safra de inverno de 2008 de uma área experimental com sistema de semeadura direta e rotação de culturas, da Faculdade de Ciências Agrárias e Veterinárias/FCAV/UNESP de Jaboticabal. O delineamento experimental foi em blocos casualizados no esquema de faixas e três repetições. As culturas de inverno: milho (Zea mays L.), girassol (Helianthus anuus L.) e guandu (Cajanus cajan (L.) Millsp), foram rotacionadas com sobre as sequências de verão: soja/soja (Glycine Max L.), milho/milho e soja/milho. Foram conduzidos dois experimentos, no Experimento 1, foram coletadas amostras de solo rizosférico (SR- solo aderido às raízes das plantas) e solo não rizosférico (SNR- solo da entrelinha de plantio) das culturas de inverno, totalizando assim 18 tratamentos (3 culturas de inverno x 3 sequências de verão x 2 posições de coleta no solo). Para o Experimento 2, foi utilizado o SR das culturas de inverno e as sequências de verão (3 x 3), totalizando 9 tratamentos... / Self-sustaining systems support microbial populations by conserving and increasing organic matter in the soil. Furthermore, plants help increase the microbial population, due to the influence of roots through the rhizosphere effect. This study evaluated the effect of winter crop rotation and summer sequences in no-tillage system on biochemical and chemical attributes; the count of total bacteria and total fungi in rhizospheric (RS) and non-rhizospheric soil (NRS); and metabolic ability of fungi isolated from the rhizospheric soil that were promoted by plant growth. This study was conducted in the winter crop of 2008 in an experimental area with no-tillage and crop rotation at the Collage of Agriculture and Veterinary Sciences / FCAV / UNESP Jaboticabal. The experimental design was randomized block scheme of plots and three repetitions. Winter crops: corn (Zea mays L.), sunflower (Helianthus anuus L.), and pigeonpea (Cajanus cajan (L.) Millsp) were rotated with summer sequences: soybean/soybean (Glycine max L.), corn/corn, and soybean/corn. Two experiments were conducted. In Experiment 1, samples were collected from rhizosphere soil (RS-soil adhering to plant roots) and non-rhizosphere soil (NRS- soil between rows of planting) of winter crops, totaling 18 treatments (3 winter crops x 3 summer sequences x 2 collect position of soil). For Experiment 2, the RS of winter crops were used and summer sequences (3 x 3), totaling nine treatments. Experiment 1: The activities of amylase, cellulase, protease, and urease in RS were 16, 85, 62, and 100% higher than in the NRS, respectively, while total organic carbon and protein were 21% higher in RS. Among the winter crops, corn stimulated higher activities of amylase, cellulase, protease, and urease in RS than other cultures. A similar effect was also observed... (Complete abstract click electronic access below)

Na área da saúde, várias abordagens nos últimos anos têm sido propostas baseadas nos gráficos de controle CUSUM para a detecção de epidemias infecciosas em que a caraterística a ser monitorada é uma série temporal de dados de contagem, como o número de internações. Neste trabalho foram implementados os modelos lineares generalizados (MLG) no monitoramento, por meio dos gráficos CUSUM e Shewhart, da série do número diário de internações por causas respiratórias para pessoas com 65 anos ou mais residentes no município de São Paulo. Por meio de simulações, avaliaram-se a eficiência de cinco estatísticas diferentes para detectar mudanças na média em séries de contagem. Uma das abordagens consistiu na implementação de três transformações normalizadoras simples que dependem unicamente dos parâmetros das distribuições Poisson e binomial negativa: a transformação Rossi para dados com distribuição Poisson, a transformação Jorgensen para dados com distribuição binomial negativa e os sesíduos de Anscombe para modelos lineares generalizados. As duas últimas estatísticas já foram propostas como gráficos CUSUM: o Método Rogerson e Yamada (2004) é apresentado para dados com distribuição Poisson e neste trabalho foi proposto um novo parâmetro kt para dados binomial negativa; já o método proposto por Hohle (2007) é baseado na função de verossimilhança da distribuição binomial negativa. Utilizando limites de controle para obter um valor ARL0 = 500 sob normalidade, monitorou-se via simulação a série de interesse, implementando as transformações normalizadoras. Entretanto, utilizando-se esses limiares observa-se um maior número de alarmes falsos para as três estatísticas. Modificando o parâmetro k do gráfico CUSUM permitindo que variasse ao longo do tempo a série foi monitorada e foram obtidos valores ARL0 próximos a 500. Os gráficos CUSUM baseados no método Rogerson e Yamada e na estatística da razão de verossimilhanças para dados com distribuição binomial negativa mostraram, via simulação, bons resultados para detectar mudanças na média. As suposições de normalidade e independência das estatísticas normalizadoras, em geral omitidas em trabalhos publicados na literatura, foram avaliadas e comprova-se que as transformações não normalizam os dados, porém são independentes e estacionárias. Analisando os dados reais, as estatísticas apresentaram autocorrelação significativa no lag 7. Devido à persistência desta autocorrelação, foi proposta uma abordagem baseada no ajuste do modelo GARMA. / In public health several approaches have been proposed for the detection of outbreaks of infectious diseases where the characteristic being monitored is a time series of count data as the number of hospitalizations, where the population and the expected rate of admissions change over time. In this work we fitted generalized linear models (GLM) and implemented Shewhart and CUSUM control charts for monitoring the daily number of hospital admissions due to respiratory diseases for people aged 65 and older in the city of São Paulo. Through simulations, we evaluated the efficiency of implementing five different statistical for detecting changes in time series of count. One approach consisted of applying three transformations that only depend on the parameters of the negative binomial and Poisson distributions: The transformations of Rossi for data with Poisson distribution, the transformation proposed by Jorgensen for data with negative binomial distribution and residuals proposed by Anscombe for generalized linear models. The other statistics have been proposed as CUSUM charts: the method of Rogerson e Yamada (2004) was presented for data with Poisson distribution, in this work we proposed a new parameter kt for negative binomial distribution, the proposed method for Hohle (2007) uses the likelihood ratio statistic. Implementing limit control assuming normality for a value of ARL0 = 500 be monitored via simulation the serie of interest implementing the normalizing statistics. However, using these limits was observed a greater number of alarms for the three transformations. Modifying the parameter k of the CUSUM chart to this change over time the series was monitored and were obtained values of ARL0 close to 500. The CUSUM control charts for the methods of Rogerson and Yamada and Holhe for data with negative binomial distribution showed, by simulation, good results for detecting changes in the mean. For negative binomial distribution generalizing the method of Rogerson e Yamada (2004) and implemented the CUSUM charts using the likelihood ratio statistic. Both methods provided good results via simulation to detect small changes in average. The evaluation of assumptions of normality for the statistics proposed by Rossi, Jorgensen and Anscombe generally is omitted in published studies. In this work, we evaluated this assumptions indicating that the statistics are not normal using the real dataset but are independent and stationary. By analyzing real data, due to the persistence of correlation for the normalized statistics, an approach based on setting GARMA model was proposed. This method showed good results once the residuals of the fitted model were normal and independent. Due to the persistence of correlation for the normalized statistics, an approach based on setting GARMA model was proposed. This method showed good results once the residuals of the fitted model were normal and independent.

Sustainable management of wildlife populations relies on accurate estimates of population size as harvest recommendations are dependent on estimates of sustainable surplus. Techniques for surveying wild turkey populations in Texas are constrained by land access issues, requiring that new methods be developed for population monitoring. I evaluated a combined approach using patch-occupancy modeling at broad spatial scales and intensive double observer roost surveys at local scales to estimate Rio Grande wild turkey (Meleagris gallapavo intermedia) distribution and abundance. I flew replicated aerial surveys during 2007 and 2008 to evaluate distribution of Rio Grande wild turkeys in the south Texas Coastal Sand Plains. I used a double observer approach to estimate local scale abundance. I used a single observer approach to estimate temporal variation in roost use. Detection probabilities from aerial surveys ranged between 0.24 (SE = 0.031) and 0.30 (SE = 0.083). Spatial parameters that influenced distribution of wild turkeys included size of suitable roosting habitat patches and distance to the nearest suitable roosting habitat. I conducted 100 inter-patch double observer roost counts, with counts ranging between 0 to 183 individuals. Average detection probabilities for observers were ~0.90. Roost level occupancy was ~0.84 with detection probabilities between 0.69 (SE = 0.107) and 0.79 (SE = 0.091). Based on my results, aerial surveys combined with local abundance estimation may be one viable alternative to monitor turkey populations over large spatial scales, by reducing overall survey effort without loss of estimated precision.

A Study Of Texas Youth Livestock Exhibitors Knowledge Within The Constructs Of The Quality Counts Assessment. (August 2013) J. D. Ragland, B.S., M. S. Chairman of Advisory Committee: Dr. Steve Fraze. The purpose of this study was to examine the effectiveness of the current Quality Counts program and assessment. This on-line training and assessment is a required program of completion for all youth exhibiting livestock at all major livestock shows in Texas. The studies additional purposes was to evaluate assessment results of participants within their respected age groups and club affiliation, and to identify their relationships of the four program objectives as well as the three research objectives outlined for this study to determine where curriculum improvements maybe needed. It was concluded that the Quality Counts program needs revision to be a more effective tool for youth exhibiting livestock.

This research develops and applies a methodology to calculate vehicle activity inputs for modelling of emissions from on-road vehicles using traffic count data. The thesis: (1) provides an understanding of emissions modelling in Canada and the U.S. and discusses the traffic activity data inputs required by vehicle emissions modelling software; (2) develops a methodology to collect and prepare vehicle activity data for an urban centre and applies this methodology by estimating vehicle activity for Winnipeg and Saskatoon; and (3) estimates vehicle emissions and then compares the sensitivity of estimating emissions using locally developed vehicle activity to estimating emissions using default vehicle activity. The methodology this research develops and applies to Winnipeg and Saskatoon is applicable to any jurisdiction in need of developing their own vehicle activity inputs for emissions modelling. The emissions estimates calculated using these different inputs emphasizes the importance of obtaining jurisdiction-specific input values for emissions modelling.

A study was undertaken to evaluate and compare the effectiveness of three anthelmintics, ivermectin, fenbendazole, and a combination of ivermectin and pyrantel pamoate, on fecal egg count reductions of cyathostomes and Parascaris equorum in 30 foals at the Texas A&M Horse Center. The foals were reared under standard horse center practices and were naturally infected with both cyathostomes and Parascaris. The foals were randomized into three treatment groups with individuals being rerandomized after each eight week observation period. The treatments of ivermectin and fenbendazole were given at the manufacturer's recommended doses and the pyrantel treatment was given at two times the manufacturer's recommended dose. All doses were based on weights taken prior to treatment. Fecal egg counts were performed at the time of treatment and at two week intervals after treatment for a total of eight weeks. Each foal received a total of three treatments during the course of the study along with the most effective treatment at the conclusion of the study. Fecal egg counts were performed by a modified McMaster's test with a sensitivity of 25 eggs per gram of feces and by the modified Wisconsin double centrifugal floatation with a sensitivity of 0.2 eggs per gram of feces. Fecal egg reduction percentages were calculated for each two week interval. Analysis of the results showed that ivermectin, either used alone or with pyrantel was a more effective anthelmintic for cyathostome (small strongyle) control than fenbendazole. Fenbendazole and pyrantel showed a higher initial reduction in Parascasris eggs when compared to the ivermectin only treated group, but ivermectin showed improved egg reduction over time. At the conclusion of this study, a primary treatment of ivermectin at the manufacturer's recommended dose and treatment of pyrantel at two times the manufacturer's recommended dose was recommended to control cyathostome egg production and severely reduce the initial number of Parascaris adults in the foals at this facility. Subsequent monthly does of ivermectin at the manufacturer's recommended dose was also recommended to continue to control both parasites. Follow up fecal examinations were also recommended to test the continued effectiveness of the recommended treatment protocol.

This research develops and applies a methodology to calculate vehicle activity inputs for modelling of emissions from on-road vehicles using traffic count data. The thesis: (1) provides an understanding of emissions modelling in Canada and the U.S. and discusses the traffic activity data inputs required by vehicle emissions modelling software; (2) develops a methodology to collect and prepare vehicle activity data for an urban centre and applies this methodology by estimating vehicle activity for Winnipeg and Saskatoon; and (3) estimates vehicle emissions and then compares the sensitivity of estimating emissions using locally developed vehicle activity to estimating emissions using default vehicle activity. The methodology this research develops and applies to Winnipeg and Saskatoon is applicable to any jurisdiction in need of developing their own vehicle activity inputs for emissions modelling. The emissions estimates calculated using these different inputs emphasizes the importance of obtaining jurisdiction-specific input values for emissions modelling.

Experimental results indicated that dolomite dissolution rates increased in all the acid solutions as the disk rotational speeds increased at 150, 200, and 250˚F. The dissolution of dolomite in 0.886 M GLDA was found to be surface-reaction limited at lower temperatures and mass-transfer limited at highest temperature. GLDA with the lowest reaction rates and relative diffusion coefficient demonstrated retardation before spending with deeper penetration capability for productivity and injectivity improvement. The purpose of this study was to analyze the Texas Quality Counts Verification Exam for junior and senior aged 4-H and FFA members. The Texas Quality Counts program was developed due to a need for teaching livestock ethics and care to the youth of Texas and it strives to teach youth how to produce a safe and wholesome livestock product for the consumer. An analysis of youth scores between 2011 and 2012 was done to determine how well youth were scoring on the Texas Quality Counts Verification Exam. Out of the 91,733 attempts, 18,204 were taken by juniors and 73,572 were taken by seniors. Junior level attempts show a fairly even spread among self-identified membership in 4-H and FFA, while senior level attempts saw a much greater spread in membership, with 73% of attempts taken by youth who identified themselves as a member in FFA. Overall, 78% of junior level youth were able to pass the exam on their first attempt, and showed a range of mean attempts between 1.13 and 1.47 based on age. Senior level youth, on the other hand, had only 47% pass on their first attempt and had a range of mean attempts between 2.21 and 2.54 based on age. The means of scores on the exam were calculated for juniors and seniors, with 0.85 and 0.71 respectively. To determine if there were any differences in scores between self-identified membership in 4-H, FFA, or both 4-H and FFA, a oneway ANOVA for junior and senior members was conducted. Both junior and senior age groups showed a significant difference between the three membership categories (p=0.001).

Background: Bloodstream infection (BSI) caused by Klebsiella pneumoniae (KP), is a leading cause of hospitalassociated childhood mortality. There are limited data on how poor outcomes of KPBSI can be predicted in poorly resourced areas. This study aimed to assess if the profile of differential counts from full blood counts (FBC) taken at two time points in children <13 years with KPBSI could be used to predict the risk of death. Methods We conducted a retrospective study of a cohort of children admitted to hospital between 2006-2011 with KPBSI. FBC collected within 48 hours (T1) of blood culture and 5-14 days later (T2), were reviewed. Differential counts were classified as abnormal if they were higher or lower than laboratory ranges for normal results. The risk of death was assessed for each category of differential counts. Risk ratios adjusted (aRR) for potential confounders were used to estimate the effect of cell counts on risk of death using multivariable analysis. Data were stratified by HIV status. Results: Of 296 children included, median age 5 (IQR:2-13) months, 82 were HIV -infected. Ninety-five (32%) of the children with KPBSI died. Mortality in HIV-infected and uninfected children was 39/82 (48%) and 56/214 (26%), respectively (p <0.001). Independent associations with mortality were observed with leucopenia, neutropenia and thrombocytopenia. Risk of mortality in children with thrombocytopenia at T1 and T2 was aRR 2.5 (95% CI: 1.34-4.64) and 3.18 (95% CI: 1.31-7.73) respectively in the HIV-uninfected group, whereas the risk for mortality in the HIV-infected group with thrombocytopaenia at T1 and T2 was aRR 1.99 (95% CI: 0.94-4.19) and 2.01 (95% CI: 0.65-5.99) respectively. Neutropenia in the HIV-uninfected group at T1 and T2, showed aRR 2.17 (95% CI: 1.22- 3.88) and 3.70 (95% CI 1.30-10.51) respectively, while in the HIV-infected group, they were aRR 1.18 (95% CI 0.69-2.03) and 2.05 (0.87-4.85) at similar time points. Risk of mortality related to leucopenia at T2 was associated with mortality in HIV-uninfected and HIV-infected patients was aRR 3.22 (95%CI 1.22-8.51) and 2.34 (1.09-5.04) respectively. Persistently high band cell percentage at T2 in HIVinfected children indicated a risk of mortality of aRR 2.91 (95% CI 1.20-7.06). Conclusion Abnormal neutrophil counts and thrombocytopenia are independently associated with significant mortality in children with KPBSI. In resource-limited countries haematological markers have the potential to predict KPBSI mortality.