Each year, County Extension Agents dedicate many hours toward educational programs to serve clientele. One of the largest programs in 4-H is the youth livestock project. Livestock projects take a significant amount of time and there is a variety of programs offered to youth exhibitors. One of these educational programs offered though Texas Cooperative Extension is Quality Counts. Quality Counts focuses on teaching character education and quality assurance to youth livestock exhibitors. The purpose of this study was to determine the total number of youth livestock projects entered in Texas during 2006 and identify any apparent educational trends. The second objective of this study was to determine how Quality Counts is perceived by County Extension Agents. To complete this study, a web based survey was sent administered to every County Extension office in Texas. 250 of 254 counties responded to the survey (98.43% response rate). From data collected, it was revealed that there were a total of 89,839 total livestock projects entered in 2006 at the county level (76,225 market and 13, 614 breeding). This data was compared to a previous study completed in 2001 by Boleman, Howard, Smith, and Couch. This data compared market livestock entry numbers. Based upon the comparison, market livestock projects have increased by 7.06% since 2000. Beef cattle and goats have increased, while sheep and swine have slightly decreased. Roughly a third of Texas counties will be utilizing the Quality Counts curriculum during the year 2007. Qualitative analysis reveals that Quality Counts is seen as educationally useful and easy to implement into traditional livestock educational programming, and is most often used as part of ongoing project clinics. Most importantly, program participants are increasing their knowledge of livestock projects, character, and ethics. Respondents are also beginning to see program participants’ behaviors change because of participating in Quality Counts.

Thesis (doctoral)--Ludwig-Maximilians-Universität in München, 1925. / "Teil I der eingereichten Arbeit." Vita. Includes bibliographical references (p. v-x).

The key results of this thesis are (1) an extension of N-mixture models to incorporate the additional layer of obfuscation brought by observing counts from a related auxiliary population (rather than the target population), (2) an extension of N-mixture models to allow for grouped counts, the purpose being two-fold: to extend the applicability of N-mixtures to larger population sizes, and to allow for the use of coarse counts in fitting N-mixture models, (3) a new R package allowing the easy application of the new N-mixture models, (4) a new R package allowing for optimization of multi-parameter functions using arbitrary precision arithmetic, which was a necessary tool for optimization of the likelihood in large population abundance N-mixture models, as well as (5) simulation studies validating the new grouped count models and comparing them to the classic N-mixtures models. / Graduate

No description available.

Inaug.-Diss.- Halle. / Vita.

Graduation date: 2000

In order to study jets and outflows from Young Stellar Objects (YSOs), I performed an unbiased search on a continuous 33 square degree sized region in Serpens and Aquila using data taken from the UWISH2 survey, which uses the 1-0 S(I) emission line ofH2 as a tracer. I identified 130 molecular hydrogen outflows from YSOs from which 120 (92 %) objects are new discoveries. Distances were measured by foreground star counts with an accuracy of25 %. Outflows were found in groups of 3 - 5 members with a size of about 5 pc. Groups were separated by about half a degree on the sky. About half of the objects were assigned with potential source candidates. Brighter MHOs had a higher probability to have a source candidate assigned to them. I find an over abundance of outflows with position angles between 1300 and 1500 which is almost perpendicular to the Galactic Plane. The fraction of parsec scale outflows is about 25 % which is more than twice compared to the one found in Orion A by Stanke et al. (2002) and Davis et al. (2009). The outflows are not able to provide a sufficient fraction of energy and momentum to support the turbulence levels in their surrounding molecular clouds. The typical dynamical jet age was of the order of 104 yrs, while groups of emission knots are ejected every 103 yrs. This indicates that low level accretion rate fluctuations and not Fu-Ori type events are responsible for the episodic ej ection of material. The luminosity distribution of the outflows shows a power law behaviour with N ex: LH;·9. The Milky Way star formation rate was estimated to more than 1.6 ± 0.4M0 yr-1 The Spectral Index Classification distribution plot of YSOs indicated that the number of outflows increases in line with a values and has a similar distribution to the one from Davis et al. (2009) from Orion A.

No description available.

Maintaining water quality in distribution systems has become a prominent issue in the study of water networks. This thesis concentrates on disinfectant and particle counts as two important indicators of water quality. The models discussed in this work are based on data collected by the author. The experimental set-up and procedure are described and observations of particle counts, particle counter size distributions, monochloramine as disinfectant, temperature, heterotrophic plate counts and epifluorescence microscopy counts are reported. A model of the response of particle counts to an increase in flow is developed. This model is obtained from specification derived from the data and assumptions, and is validated by its interpretability and its fit to data. A local shear-off density and an initial biofilm shedding profile were introduced and thus a linear model for this part of the water quality dynamics could be obtained. A procedure for the identification of the parameters of the local shear-off function and for the determination of the biofilm shedding profile is presented. This profile can be used to provide information about the status of the distribution system in terms of shear-off from the biofilm on the pipe walls. Monochloramine decay dynamics are investigated. The chlorine meter data is preprocessed with the help of titration data to correct meter drift. The data is then used in calibrating two different possible chlorine models: a model with a single decay coefficient and a model with bulk decay coefficient and wall demand (as used in Epanet). Important difficulties in identifying these parameters that come about because of the structure of the models are highlighted. Identified decay coefficients are compared and tested for flow, inlet chlorine and temperature dependence. The merits and limits of the approach to modelling taken in this work and a possible generalisation are discussed. The water industry perspective and an outlook are provided.

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.