Sexual assault evidence composes a large portion of the evidence analyzed by forensic serologists. Key to the processing of sexual assault evidence is the screening of the evidence items for the presence of semen. Due to the intimate nature of a sexual assault, it is very possible that semen is mixed with other body fluids when it is deposited on an item of evidence. One of the body fluids that semen can easily come into contact with during a sexual assault is saliva. Saliva functions as the first step in the human body’s digestive system. Due to the digestive system’s purpose of breaking down nutrients, it stands to reason that saliva could play a role in breaking down seminal components. To detect semen, specific components of semen are tested for in forensic laboratories. These components are often acid phosphatase, prostate specific antigen, semenogelin, and spermatozoa. This experiment combined semen from one donor with saliva of seven other donors in a two part survey. In part one, semen was mixed with the saliva of Donors A, B, C, and D at three different ratios of 1:1, 1:2, and 1:10 semen-saliva. Twenty-microliter stains were pipetted onto one inch by one inch squares on twelve cotton swatches to test for acid phosphatase, prostate specific antigen, semenogelin, and spermatozoa. One set of six swatches was allowed to dry and the other set was kept damp. The stains were tested at six timepoints: day zero, day one, week one, week two, week three, and week four. Part two involved incubating the semen with saliva from Donors X, Y, and Z at body temperature for up to twenty-four hours. The same three ratios used in part one were repeated with the saliva from Donors X, Y, and Z in part two. A twenty microliter stain was pipetted onto a cotton swatch at each of the five timepoints from the start of the incubation period: zero minutes, one hour, five hours, eight hours, and twenty-four hours. Each stain was tested for acid phosphatase, prostate specific antigen, and semenogelin. The results of part one showed that semen samples that are mixed with saliva but allowed to dry are effectively unaffected by the presence of saliva. On the dry swatches, the stains tested positive for every component of semen at every timepoint for every donor except for Donor D’s 1:10 semen-saliva mixture stain, which tested negative for spermatozoa at week 1, but positive for spermatozoa in the subsequent timepoints. The results of the damp swatches suggests that damp environmental factors can prevent the detection of seminal components. By week two, the detection of spermatozoa had completely dropped out in the mixture stains and in the neat semen control stains. Detection of prostate specific antigen ceased in the control by week 3 and had also stopped in all 1:1 semen-saliva mixture stains by week 4. The detection of prostate specific antigen had stopped at week 3 for all donors in the 1:10 semen-saliva mixture stains. Semenogelin was still detectable in the control sample for the duration of the experiment, and it was detected for all donors at week 4 in the 1:1 and 1:2 semen-saliva mixture stains. Detection of semenogelin ceased in Donors B and D in the 1:10 semen-saliva mixture stains by week two. The results of part two suggested that the detection of acid phosphatase could be affected when semen and saliva have been incubating together at body temperature. Acid phosphatase was detected at all the timepoints in the neat semen control, but after eight hours, it was no longer detectable in all the mixture ratios of Donors X and Z. Acid phosphatase was no longer detectable in the 1:1 semen-saliva mixture stain of donor Y at eight hours and in the 1:2 semen-saliva mixture stain of Donor Y at twenty-four hours. Acid phosphatase did remain detectable in the 1:10 semen-saliva mixture stain of Donor Y through the twenty-four hour experimental period. Prostate specific antigen and semenogelin remained detectable in all the donors at all three ratios for the duration of the experiment.

The objective of this dissertation is to investigate all the necessary components in spectral mixture analysis (SMA) for hyperspectral imagery under an unsupervised circumstance. When SMA is linear, referred to as linear spectral mixture analysis (LSMA), these components include estimation of the number of endmembers, extraction of endmember signatures, and calculation of endmember abundances that can automatically satisfy the sum-to-one and non-negativity constraints. A simple approach for nonlinear spectral mixture analysis (NLSMA) is also investigated. After SMA is completed, a color display is generated to present endmember distribution in the image scene. It is expected that this research will result in an analytic system that can yield optimal or suboptimal SMA output without prior information. Specifically, the uniqueness in each component is described as follow. 1)A new signal subspace-based approach is developed to determine the number of endmembers with relatively robust performance and the least parameter requirement. 2)The best implementation strategy is determined for endmember extraction algorithms using simplex volume maximization and pixel spectral similarity; and algorithm with the special consideration for anomalous pixels is developed to improve the quality of extracted endmembers. 3)A new linear mixture model (LMM) is deployed where the number of endmembers and their types can be changed from pixel to pixel such that the resulting endmember abundances are sum-to-one and nonnegative as required; and fast algorithms are developed to search for a sub-optimal endmember set for each pixel. 4)A simple approach for NLSMA based on LMM is investigated and an automated approach is developed to determine either linear or nonlinear mixing is actually experienced. 5)A color display strategy is developed to present SMA results with high class/endmember separability.

Discriminant analysis uses labelled observations to infer the labels of unlabelled observations in a population. Despite many advances in unsupervised and, to a lesser extent, semi-supervised learning over the past decade, discriminant analysis is often employed using approaches that date back to very well-known work of Fisher in the 1930s. One notable exception is mixture discriminant analysis, where the labels are estimated using parametric finite mixture models, commonly the Gaussian mixture model. The supposed advantage with mixture discriminant analysis is that multiple Gaussian components can be used for each class, hence providing a work around when a class is not Gaussian. This thesis makes several contributions to ``modern" discriminant analysis. Three robust discriminant analysis methods are introduced using mixtures of multivariate t-distributions, mixtures of multivariate power exponential distributions, and mixtures of contaminated Gaussian distributions, respectively. This provides an appealing framework for handling varying tail-weights and peakedness in the classes that may also contain mild outliers. To facilitate the modelling of asymmetric classes, we also explore robust discriminant analysis via finite mixtures of generalized hyperbolic distributions and mixtures of multivariate skew-t distributions. These approaches are tailored towards skewed classes but also have the added advantage of modelling symmetric classes where necessary. Finally, we introduce an approach that combines support vector machines with mixture discriminant analysis. This approach defines class boundaries in the labelled observations and, in some sense, improves mixture discriminant analysis performance. Crucially, in all of our mixture modelling work, we consider the case where the number of components per class is one. The utility of the approaches introduced is demonstrated on simulated and real data sets. / Thesis / Doctor of Philosophy (PhD)

Statistics, as a critical component in transportation research, has been widely used to analyze driver safety, travel time, traffic flow and numerous other problems. Many of these popular topics can be interpreted as to establish the statistical models for the latent structure of data. Over the past several years, the interest in latent class models has continuously increased due to their great potential in solving practical problems. In this dissertation, I developed several latent class models to quantitatively analyze the hidden structure of transportation data and addressed related application issues. The first model is focused on the uncertainty of travel time, which is critical for assessing the reliability of transportation systems. Travel time is random in nature, and contains substantial variability, especially under congested traffic conditions. A Bayesian mixture model, with the ability to incorporate the influence from covariates such as traffic volume, has been proposed. This model advances the previous multi-state travel time reliability model in which the relationship between response and predictors was lacking. The Bayesian mixture travel time model, however, lack the power to accurately predict the future travel time. The analysis indicates that the independence assumption, which is difficult to justify in real data, could be a potential issue. Therefore, I proposed a Hidden Markov model to accommodate dependency structure, and the modeling results were significantly improved. The second and third parts of the dissertation focus on the driver safety identification. Given the demographic information and crash history, the number of crashes, as a type of count data, is commonly modeled by Poisson regression. However, the over-dispersion issue within the data implies that a single Poisson distribution is insufficient to depict the substantial variability. Poisson mixture model is proposed and applied to identify risky and safe drivers. The lower bound of the estimated misclassification rate is evaluated using the concept of overlap probability. Several theoretical results have been discussed regarding the overlap probability. I also introduced quantile regression based on discrete data to specifically model the high-risk drivers. In summary, the major objective of my research is to develop latent class methods and explore the hidden structure within the transportation data, and the approaches I employed can also be implemented for similar research questions in other areas. / Ph. D.

Altered immune responses have been observed following occupational, inadvertent, or therapeutic exposure to xenobiotics. Many pesticides are known to cause immunotoxicity. Exposure to mixtures of pesticides, either concurrently or sequentially, may result in potentiating this effect partly because one can effect the metabolism of the other. The objective of this study was to determine the effect of the insecticides endosulfan, permethrin and their mixtures on C57/BL6 male mice thymocytes in vitro and to ascertain the mechanism by which these effects take place. Permethrin, a broad-spectrum synthetic pyrethroid, is a widely used insecticide in agriculture and public health. Endosulfan is a highly toxic chlorinated hydrocarbon insecticide used worldwide. We examined the immunotoxic potential of these pesticides using a flow cytometric technique in combination with 7-Amino Actinomycin D (7AAD) to distinguish live, early apoptotic, and late apoptotic/necrotic cells. DNA ladder assay, a hallmark of apoptosis, was also used to determine the occurrence of apoptosis. Both endosulfan and permethrin were found to cause significant apoptotic death of thymocytes in a dose- and time- dependent manner. Thus, permethrin at 50, 100 or 300 µM was found to cause 5.5, 11.5 and 26.1% increases in early apoptotic cell death relative to control, respectively. Endosulfan at 25, 50 or 250 µM was found to cause 11.9, 15.7 and 68.0% early apoptotic cell death, respectively. For the mixture study, concentrations of 100 µM permethrin and 50 µM endosulfan were selected and found to cause 27.1% apoptosis. Thus, these pesticides in mixture have an additive immunotoxic effect. Increases in late-apoptotic/necrotic cells were found at these concentrations for either pesticide when exposed for 12 hours. DNA ladder assay confirmed the presence of DNA fragments and therefore the presence of significant apoptotic cell death. Apoptosis is a morphologically distinct form of cell death that can be mediated by a variety of pathological and physiological stimuli. Because permethrin and endosulfan were found to induce apoptosis in C57/BL6 mice thymocytes in vitro, the objective of the second half of this study was to elucidate the potential mechanism by which these pesticides regulate apoptosis in immune cells. Caspases are a family of cystine-dependent, aspartate-directed proteases that have an integral role in apoptotic cell death. Caspases, which are normally inactive in healthy cells, are activated during apoptosis and form an irreversible cascade. There are two subsets of caspases, initiator caspases (i.e. caspase 8 and 9) and effector caspases (i.e. caspases 3 and 6). Caspase 3, a downstream effector of apoptosis, is activated by many different pathways and is an apoptotic marker in cells. Caspase 8 is the apical caspase in the extrinsic pathway. Caspase 9 is the apical caspase in the intrinsic pathway, therefore we investigated mechanisms of pesticide induced apoptosis involving the thymocyte caspase system. Thymocytes from C57/BL6 mice were incubated with varying concentrations of pesticides for varying amounts of time. Active caspase 3 was then measured using EnzCheck Caspase 3 Assay Kit. Relative fluorescence for permethrin exposed cells after 12 hours incubation in the presence of pesticides at 150, 100, and 50 µM and 40 minutes in the presence of AFC-substrate was found to be 387, 386, and 297, respectively. Relative fluorescence for endosulfan exposed cells at 150, 100 and 50 µM was 188, 177, and 294. Caspase 3 activity increased as permethrin concentrations increased and decreased as endosulfan concentrations were increased. Then the extrinsic and intrinsic pathways of apoptosis were further investigated. Active caspase 8 was measured using the ApoAlert Caspase Fluorescent Assay Kit. Relative fluorescence for permethrin exposed cells after 7 hours incubation in the presence of pesticides at 100, 150, and 200 µM was found to be 35.5, 10.5, and 0, respectively. Relative fluorescence for endosulfan exposed cells after 7 hours incubation at 25, 50, 100 and 150 µM was found to be 32.8, 63.8, 69.5, and 55.5, respectively. A mixture study was then performed using endosulfan (50, 100, 150 µM) combined with permethrin (100 µM). All combinations were found to have more than an additive effect, therefore the extrinsic pathway seems to be involved. Caspase 9 activity was measured using Caspase 9/Mch6 Fluorometric Protease Assay Kit. Relative fluorescence for endosulfan exposed cells after 7 hours incubation at 25, 50, 100 and 150 µM was found to be 43, 73, 78.9, and 5.12, respectively. Relative Fluorescence for permethrin exposed cells at 100, 150 and 200 µM was found to be 34.5, 39, and 55.5, respectively. A mixture study was then performed using endosulfan (25, 50 µM) combined with permethrin (100 µM). Both combinations were found to have less than an additive effect. These results suggest that apoptosis caused by both endosulfan and permethrin exert their effects via the caspase pathway. The results also show that mixtures of pesticides have a less than additive effect on caspase 9 activation and more than an additive effect on caspase 8 activation, therefore the extrinsic pathway is predominantly involved in thymocyte apoptosis caused by mixtures of permethrin and endosulfan. / Master of Science

OCLUST is a clustering algorithm that trims outliers in Gaussian mixture models. While mixtures of multivariate Gaussian distributions are a useful way to model heterogeneity in data, it is not always an appropriate assumption that the data arise from a finite mixture of Gaussian distributions. This thesis extends the OCLUST algorithm to three types of data which depart from the multivariate Gaussian distribution. The first extension, called funOCLUST, is developed for data which exist in functional form. Next, MVN-OCLUST applies outlier trimming to matrix-variate normal data. Finally, the skewOCLUST algorithm is formulated for skewed data by applying a transformation to normality. However, this final extension occurs after a brief detour in Chapter 5 to establish a foundation for the final chapter. / Thesis / Doctor of Philosophy (PhD)

Finite mixture modelling is a powerful and well-developed paradigm, having proven useful in unsupervised learning and, to a lesser extent supervised learning (mixture discriminant analysis), especially in the case(s) of data with local variation and/or latent variables. It is the aim of this thesis to improve upon mixture discriminant analysis by introducing two types of random forest analogues which are called Mix- Forests. The first MixForest is based on Gaussian mixture models from the famous family of Gaussian parsimonious clustering models and will be useful in classify- ing lower dimensional data. The second MixForest extends the technique to higher dimensional data via the use of mixtures of factor analyzers from the well-known family of parsimonious Gaussian mixture models. MixForests will be utilized in the analysis of real data to demonstrate potential increases in classification accuracy as well as inferential procedures such as generalization error estimation and variable importance measures. / Thesis / Doctor of Philosophy (PhD)

CoordenaÃÃo de AperfeiÃoamento de Pessoal de NÃvel Superior / A pavimentaÃÃo utiliza grandes volumes de recursos naturais requerendo aÃÃes que mitiguem os consequentes danos ambientais. Observando-se uma obra rodoviÃria, pode-se destacar aspectos que afetam o meio ambiente, como: desmatamento, extrativismo mineral para a produÃÃo de agregados e extraÃÃo e refino de petrÃleo para utilizaÃÃo em camadas asfÃlticas. Esta atividade faz uso ainda de processos que geram grandes volumes de passivos ambientais, tais como: fresagem e demoliÃÃes. O material fresado pode ser reciclado e reaproveitado, por exemplo, na produÃÃo de Misturas AsfÃlticas Recicladas a Quente (MARQs). As altas temperaturas que as misturas asfÃlticas exigem para tornarem-se trabalhÃveis submetem o ambiente a sua volta, especialmente os operÃrios que trabalham na produÃÃo do revestimento asfÃltico na usina, à condiÃÃes insalubres. Tendo em vista que o Cimento AsfÃltico de PetrÃleo (CAP), quando submetido a altas temperaturas, libera fumos que sÃo sabidamente nocivos. Para mitigar estes malefÃcios, pode-se utilizar as Misturas AsfÃlticas Mornas (MAMs).Essas misturas requerem temperaturas mais baixas do que as temperaturas normalmente empregadas na produÃÃo de Concretos AsfÃlticos (CAs).à possÃvel, ainda,combinar as duas tÃcnicas (MARQs e MAMs) utilizando as Misturas AsfÃlticas Recicladas Mornas (MARM).O presente trabalho tem como objetivo principal avaliar MARMs no que diz respeito a trabalhabilidade, a compactabilidade e ao comportamento mecÃnico das mesmas. Para isso, foram dosadas e caracterizadas em laboratÃrio 14 misturas do tipo CA, quais sejam: (i) duas misturas de referÃncia (uma dosada atravÃs da metodologia de dosagem Marshall e outra atravÃs da metodologia Superpave), (ii) trÃs MAMs (dosadas atravÃs da metodologia de dosagem Marshall) com, respectivamente, 20, 30 e 40ÂC de diminuiÃÃo das temperaturas utilizadas em todas as etapas do processo de dosagem, (iii) trÃs MAMs (dosadas atravÃs da metodologia de dosagem Superpave) com as mesmas diminuiÃÃes nas temperaturas jà mencionadas, (iv) trÃs MARQs (dosadas atravÃs da metodologia de dosagem Superpave) com 15, 35 e 50% de fresado em suas composiÃÃes e (v) trÃs MARMs com os mesmos percentuais de fresado utilizados nas MARQs e com a diminiÃÃo de temperatura de 40ÂC em todas as fases do processo. AlÃm das 14 misturas aqui descritas que foram avaliadas na fase de laboratÃrio do presente trabalho, foram dosadas outras quatro misturas em laboratÃrio para serem testadas em campo com a construÃÃo de trechos experimentais.Analisando-se os resultados encontrados percebe-se que as MARMs tem um potencial promissor, tendo em vista que as mesmas apresentaram parÃmetros volumÃtricos encontrados durante o processo de dosagem e comportamento mecÃnico similares se comparados aqueles obtidos para as misturas asfÃlticas convencionais. Tais parÃmetros foram alcanÃados sem a necessidade de mudanÃas nos equipamentos utilizados para a produÃÃo dessas misturas. Foi possÃvel atingir patamares de economia no consumo de CAP virgem de atà 45% e de agregados convencionais virgens de atà 50%, alÃm de uma possÃvel diminuiÃÃo do consumo energÃtico durante o processo de produÃÃo dessas misturas asfÃlticas devido a reduÃÃo das temperaturas em atà 40ÂC. / The paving process uses large amounts of natural resources thus requiring actions to mitigate the resulting environmental damage. Observing a road section, you can highlight activities that affect the environment, such as deforestation, mineral extraction for the production of aggregates and petroleum extraction and refining for use in asphalt layers. This activity also uses processes that generate large volumes of environmental liabilities, such as milling and demolition material. The reclaimed asphalt pavement (RAP) can be recycled and reused, for example in the production of RAP hot mixtures asphalts (HMA). The high temperatures that need to be used to produce acceptable workability of the asphalt mixtures can affect the environment and the workers on the construction site. The asphalt binder when subjected to high temperatures releases fumes known to be health hazardous. To mitigate these hazards, one can use the warm mixtures asphalt (WMA). This technology uses lower temperatures than the ones normally applied for HMA, thereby aforementioned emissions can be mitigated. It is also possible that the asphalt mixtures can be implemented with lower energy consumption. One can still use RAP WMA making use of both solutions already mentioned, RAP HMA and WMA. This work aims to use both techniques together and evaluate RAP WMA with respect to its workability, compactability and mechanical behavior. In order to achieve this objective it will be characterized in the laboratory HMAs with different RAP percentages and WMA additive. Such mixtures are also subsequently tested in the field using experimental sections. Analyzing the results it is noticed that the RAP WMAs has a promising potential since they presented the same volumetric parameters and mechanical behavior when compared to those obtained for the conventional asphalt mixtures. These parameters have been achieved without the need for changes in the equipment used for the production of these mixtures. It was possible to attain savings in binder consumption of up to 45% and conventional aggregates of up to 50%.A reduction in energy consumption is also achieved during the production of asphalt mixtures due to reductions in temperature to 40ÂC.

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This paper considers a free energy functional and corresponding free boundary problem for multilayered structures which arise from a mixture of a block copolymer and a weak solvent. The free boundary problem is formally derived from the limit of large solvent/polymer segregation and intermediate segregation between monomer species. A change of variables based on Legendre transforms of the effective bulk energy is used to explicitly construct a family of equilibrium solutions. The second variation of the effective free energy of these solutions is shown to be positive. This result is used to show more generally that equilibria are local minimizers of the free energy.