The characterization of water treatment residuals containing arsenic was investigated in the first study. Arsenic desorption and leachability from the residuals were the focus of this study. Arsenic leaching from water treatment residuals was found to be underestimated by the toxicity characteristic leaching test (TCLP) due to the pH of the leachates being favorable for As(V) adsorption. Competitive desorption of arsenic with phosphate was significant because phosphate tends to compete with As(V) on the surface of the metal hydroxide for adsorption sites. However, arsenic desorption by the competition of sulfate and chloride was found to be negligible. The pH in the leachate was a critical variable in controlling arsenic stability in the residuals. The release of arsenic from the residuals was elevated at low and high pH due to the increase dissolution of the adsorbents such as Fe and Al hydroxides. In the second phase of the study, the stabilization techniques for arsenic contained residuals and were examined to develop methods to suitably stabilize arsenic to eliminate and/or minimize leaching. A decrease of arsenic leaching was achieved by the addition of lime to the residuals and believed to be due to the formation of less soluble and stable calcium-arsenic compounds. However, it is suggested that the ordinary Portland cement (OPC) should be added with the lime for the long term stabilization because lime can be slowly consumed when directly exposed to atmospheric CO2. The solidification and stabilization (S/S) technique with lime and OPC was shown to be successfully applied by the immobilization of a wide variety of arsenic tainted water treatment residuals.

Thesis (Ph. D.)--Lehigh University, 2004. / Includes vita. Includes bibliographical references (leaves 163-171).

In many clinical studies, continuous variables such as age, blood pressure and cholesterol are measured and analyzed. Often clinicians prefer to categorize these continuous variables into different groups, such as low and high risk groups. The goal of this work is to find the cutpoint of a continuous variable where the transition occurs from low to high risk group. Different methods have been published in literature to find such a cutpoint. We extended the methods of Contal and O’Quigley (1999) which was based on the log-rank test and the methods of Klein and Wu (2004) which was based on the Score test to find the cutpoint of a continuous covariate. Since the log-rank test is a nonparametric method and the Score test is a parametric method, we are interested to see if an extension of the parametric procedure performs better when the distribution of a population is known. We have developed a method that uses the parametric score residuals to find the cutpoint. The performance of the proposed method will be compared with the existing methods developed by Contal and O’Quigley and Klein and Wu by estimating the bias and mean square error of the estimated cutpoints for different scenarios in simulated data.

It is common practice to use Cox-Snell residuals to check for overall goodness of tin survival models. We evaluate the presumed relation of unit exponentially dis-tributed residuals for a good model t and evaluate under some violations of themodel. This is done graphically with the usual graphs of Cox-Snell residual andformally using Kolmogorov-Smirnov goodness of t test. It is observed that residu-als from a correctly tted model follow unit exponential distribution. However, theCox-Snell residuals do not seem to be sensitive to the violations of the model.

Thesis (M.S.)--University of Tennessee, Knoxville, 2001. / Title from title page screen. Document formatted into manuscript-like pagination: x, 128 leaves : ill. (some col.). Vita. Includes bibliographical references (leaves 114-122).

Thesis (Ph. D.)--Colorado State University, 2004. / Includes bibliographical references.

La presencia de compuestos orgánicos cada vez más tóxicos en las aguas residuales, especialmente provenientes de la industria, ha desafiado los métodos convencionales de tratamiento de aguas residuales. Por esta razón existe una clara necesidad de buscar nuevas técnicas emergentes las cuales pueden tratar los contaminantes orgánicos muy concentrados en agua o no biodegradables. Como no es posible utilizar un único método universal para destruir todos los compuestos orgánicos, se ha probado Catalytic Wet Air Oxidation (CWAO), CWAO promovida por peróxido de hidrógeno, Wet Peroxide Oxidation and Oxidación de Fenton para eliminar compuestos aromáticos pertenecientes a diferentes grupos. Con este propósito un equipo de alta temperatura y alta presión ha sido diseñado y construido. Este equipo puede trabajar en un proceso tanto catalítico como no catalítico. El carbón activo, un material barato, ha sido utilizado como el catalizador heterogéneo (CWAO), mientras el sulfato de hierro ha sido empleado como un catalizador homogéneo (Oxidación de Fenton). Los compuestos estudiados fueron fenol, p-nitrofenol, anilina, nitrobenceno y sulfolano, porque son tóxicos y no biodegradable y al mismo tiempo son frecuentemente encontrados en los efluentes industriales. También se ha probado dos muestras de efluentes industriales reales provenientes de la producción de las resinas fenólicas. El peróxido de hidrógeno ha sido empleado como un oxidante, excepto en CWAO, donde se lo utilizó como un promotor, porque peróxido de hidrógeno es una excelente fuente de radicales hidroxilos muy oxidantes. En primer lugar, cada proceso ha sido probado con el fenol, como contaminante de referencia, para encontrar las variables de operación influyentes para la eficacia del proceso. El objetivo era no solo destruir el compuesto original, sino también convertirlo en dióxido de carbón y agua o al menos convertirlo en compuestos inocuos y fácilmente biodegradables. Posteriormente, el método ha sido también estudiado con otros compuestos. Se observó que es posible obtener la conversión completa para todos compuestos menos el nitrobenceno con el cual se obtiene la conversión máxima de 80% utilizando WPO. Sin embargo, para determinados compuestos se ha encontrado que algunos métodos presentaron desventajas, tales como problemas de corrosión en caso de sulfolano (WPO) o formación de un tapón en reactor en caso de CWAO con anilina sobre carbón activo. A pesar de esto, se puede proponer un método de tratamiento para cada compuesto. El peróxido de hidrógeno resultó ser un oxidante muy eficaz, así se encontró que el 100% de la cantidad estequiométrica de H2O2 era suficiente para mineralizar completamente todos los compuestos, excepto el nitrobenceno. El peróxido de hidrógeno también resultó ser un buen promotor de CWAO, aumentando considerablemente la eficacia del proceso. Cabe destacar que todos los métodos fueron estudiados siempre en el mismo equipo después de realizar pequeñas modificaciones. El método de la oxidación de Fenton en modo continuo, a 200ºC, empleando sulfato de hierro permite una eliminación similar (del 70%) de nitrobenceno al método WPO no catalítico a 550ºC (80%). Para los efluentes industriales reales las técnicas estudiadas han permitido obtener una conversión completa de fenol y la reducción de DQO por encima del 50%. Aunque esto no permite la completa mineralización, probablemente aumenta su biodegradabilidad. / The identification of more and more toxic organic compounds in wastewater, especially from industry, has challenged the conventional wastewater treatment methods. That is why there is a need to look for a new emerging technologies that can treat highly concentrated or non-biodegradable organic water pollutants. As it is impossible to use one universal method to destroy all the organic compounds, we have tested Catalytic Wet Air Oxidation (CWAO), hydrogen peroxide promoted CWAO, Wet Peroxide Oxidation and Fenton's Oxidation to remove aromatic organics belonging to different groups. For this purpose high temperature and high pressure continuous reactor system was designed and constructed. This equipment can be used either for catalytic or noncatalytic process. An activated carbon, that is low cost material, was used as a heterogeneous catalyst (CWAO), while iron sulphate was employed as a homogeneous catalyst (Fenton's Oxidation). Phenol, p-nitrophenol, aniline, nitrobenzene and sulfolane were studied, because these compounds are toxic, mostly non-biodegradable and at the same time, they are commonly found in industrial effluents. Also two samples of real industrial effluents coming from phenolic resins production were tested. Hydrogen peroxide was used as an oxidant, except in CWAO, where it was used as a promoter. This is because hydrogen peroxide is an excellent source of highly oxidative hydroxyl radicals. Firstly, each process was tested for phenol in order to find the influence of operational variables on the process efficiency. The aim was not only to destroy the original compound, but also to convert it to gas carbon dioxide and water, or at least in much more innocuous compounds easily biodegradable. Than the method performance with other compounds was examined. Finally, there can be achieved the complete conversion for every compound except nitrobenzene with highest conversion of about 80% during WPO experiments. However, for some compounds certain methods exhibited drawbacks such as corrosion problems with sulfolane, and plugging in the reactor during CWAO of aniline over activated carbon. In spite of this for every compound a removal technique among the methods studied can be proposed. Hydrogen peroxide resulted to be efficient oxidant, as 100% of stoichiometric quantity of H2O2 was sufficient to mineralise completely all the compounds, except nitrobenzene. Also, hydrogen peroxide is efficient as promoter of CWAO, enhancing greatly process efficacy. It is also interesting that all the methods could be performed in the same equipment after slight modification of the system. And Fenton's oxidation in continuous system in temperature about 200ºC permits similar removal of nitrobenzene (70%) using iron sulphate (II), that during noncatalytic WPO when employing 550ºC (80%). Also for real effluents it was observed that the oxidation techniques studied permitted to obtain complete phenol conversion and COD reduction over 50%. Even if it does not allow a complete mineralisation of organic compounds more refractory that phenol present in the wastewater it can probably increase the biodegradability.

In this thesis, two methods for assessing the functional form of covariates in the Cox proportional hazards model are evaluated. The methods include one graphical check based on martingale residuals and one graphical check, together with a Kolmogorov-type supremum test, based on cumulative sums of martingale residuals. The methods are evaluated in a simulation study under five different covariate misspecifications with varying sample sizes and censoring degrees. The results from both methods indicate that the type of covariate misspecification, sample size and censoring degree affect the ability to detect and identify the misspecification. The procedure based on smoothed scatterplots of martingale residuals reveals difficulties with assessing whether the behaviour of the smoothed curve in the plot is an indication of a misspecification or a phenomenon that can occur in a correctly specified model. The graphical check together with the test procedure based on cumulative sums of martingale residuals is shown to successfully detect and identify three out of five covariate misspecifications for large sample sizes. For small sample sizes, especially combined with a high censoring degree, the power of the supremum test is low for all covariate misspecifications.

No description available.

<p>Statistical models often rely on several assumptions including distributional assumptions on outcome variables and relational assumptions where we model the relationship between outcomes and independent variables. Further assumptions are also made depending on the complexity of the data and the model being used. Model diagnostics is, therefore, a crucial component of any model fitting problem. Residuals play important roles in model diagnostics. Residuals are not only used to check adequacy of model fit, but they also are excellent tools to validate model assumptions as well as identify outliers and influential observations. Residuals in univariate models are studied extensively and are routinely used for model diagnostics. In multivariate models residuals are not commonly used to assess model fit, although a few approaches have been proposed to check multivariate normality. However, in the analysis of longitudinal data, the resulting residuals are correlated and are not normally distributed. It is, therefore, not clear as to how ordinary residuals can be used for model diagnostics. Under sufficiently large sample size, a transformation of ordinary residuals are proposed to check the normality assumption. The transformation is based solely on removing correlation among the residuals. However, we show that these transformed residuals fail in the presence of model mis-specification. In this thesis, we investigate residuals in the analysis of longitudinal data. We consider ordinary residuals, Fitzmaurice’s transformed (uncorrelated) residuals as well as von Rosen’s decomposed residuals. Using simulation studies, we show how the residuals behave under multivariate normality and when this assumption is violated. We also investigate their properties under correct fitting as well as wrongly fitted models. Finally, we propose new residuals by transforming von Rosen’s decomposed residuals. We show that these residuals perform better than Fitzmourice’s transformed residuals in the presence of model mis-specification. We illustrate our approach using two real data sets.</p> / Master of Science (MSc)