Development and Application of Improvements to the Tile-based Fisher Ratio Method and Fundamental Instrument Considerations for Non-targeted Analysis using Two-dimensional Gas Chromatography

Thesis (Ph.D.)--University of Washington, 2016-06

On the dimensionality of the Attachment Style Questionnaire in Italian clinical and nonclinical participants

This study examined the utility of the Attachment Style Questionnaire (ASQ) in an Italian sample of 487 consecutively admitted psychiatric participants and an independent sample of 605 nonclinical participants. Minimum average partial analysis of data from the psychiatric sample supported the hypothesized five-factor structure of the items; furthermore, multiple-group component analysis showed that this five-factor structure was not an artifact of differences in item distributions. The five-factor structure of the ASQ was largely replicated in the nonclinical sample. Furthermore, in both psychiatric and nonclinical samples, a two-factor higher order structure of the ASQ scales was observed. The higher order factors of Avoidance and Anxious Attachment showed meaningful relations with scales assessing parental bonding, but were not redundant with these scales. Multivariate normal mixture analysis supported the hypothesis that adult attachment patterns, as measured by the ASQ, are best considered as dimensional constructs.

A genetic two-factor model of the covariation among a subset of Multidimensional Aptitude Battery and Wechsler Adult Intelligence Scale - Revised subtests

The phenotypic and genetic factor structure of performance on five Multidimensional Aptitude Battery (MAB) subtests and one Wechsler Adult Intelligence Scale-Revised (WAIS-R) subtest was explored in 390 adolescent twin pairs (184 monozygotic [MZ]; 206 dizygotic (DZ)). The temporal stability of these measures was derived from a subsample of 49 twin pairs, with test-retest correlations ranging from .67 to .85. A phenotypic factor model, in which performance and verbal factors were correlated, provided a good fit to the data. Genetic modeling was based on the phenotypic factor structure, but also took into account the additive genetic (A), common environmental (C), and unique environmental (E) parameters derived from a fully saturated ACE model. The best fitting model was characterized by a genetic correlated two-factor structure with specific effects, a general common environmental factor, and overlapping unique environmental effects. Results are compared to multivariate genetic models reported in children and adults, with the most notable difference being the growing importance of common genes influencing diverse abilities in adolescence. (C) 2003 Elsevier Inc. All rights reserved.

Overlapping species boundaries and hybridization within the Monastraea "annularis" reef coral complex in the Pleistocene of the Bahama Islands

Recent molecular analyses indicate that many reef coral species belong to hybridizing species complexes or "syngameons." Such complexes consist of numerous genetically distinct-species or lineages, which periodically split and/or fuse as they extend through time. During splitting and fusion, morphologic intermediates form and species overlap. Here we focus on processes associated with lineage fusion, specifically introgressive hybridization, and the recognition of such hybridization in the fossil record. Our approach involves comparing patterns of ecologic and morphologic overlap in genetically characterized modern species with fossil representatives of the same or closely related species. We similarly consider the long-term consequences of past hybridization on the structure of modern-day species boundaries. Our study involves the species complex Montastraea annularis s.l. and is based in the Bahamas, where, unlike other Caribbean locations, two of the three members of the complex today are not genetically distinct. We measured and collected colonies along linear transects across Pleistocene reef terraces of last interglacial age (approximately 125 Ka) on the islands of San Salvador, Andros, and Great Inagua. We performed quantitative ecologic and morphologic analyses of the fossil data, and compared patterns of overlap among species with data from modern localities where species are and are not genetically distinct. Ecologic and morphologic analyses reveal "moderate" overlap (>10%, but statistically significant differences) and sometimes "high" overlap (no statistically significant differences) among Pleistocene growth forms (= "species"). Ecologic analyses show that three species (massive, column, organ-pipe) co-occurred. Although organ-pipes had higher abundances in patch reef environments, columnar and massive species exhibited broad, completely overlapping distributions and had abundances that were not related to reef environment. For morphometric analyses, we used multivariate discriminant analysis on landmark data and linear measurements. The results show that columnar species overlap "moderately" with organ-pipe and massive species. Comparisons with genetically characterized colonies from Panama show that the Pleistocene Bahamas species have intermediate morphologies, and that the observed "moderate" overlap differs from the morphologic separation among the three modern species. In contrast, massive and columnar species from the Pleistocene of the Dominican Republic comprise distinct morphologic clusters, similar to the modern species; organ-pipe species exhibit "low" overlap (

Novel markers for poor prognosis in head and neck cancer

Head and neck cancer (HNSCC) is one of the most distressing human cancers, causing pain and affecting the basic survival functions of breathing and swallowing. Mortality rates have not changed despite recent advances in radiotherapy and surgical treatment. We have compared the expression of over 13,000 unique genes in 7 cases of matched HNSCC and normal oral mucosa. Of the 1,260 genes that showed statistically significant differences in expression between normal and tumor tissue at the mRNA level, the three top ranking of the top 5% were selected for further analysis by immunohistochemistry on paraffin sections,. along with the tumor suppressor genes p16 and p53, in a total of 62 patients including 55 for whom >4-year clinical data was available. Using univariate and multivariate survival analysis, we identified SPARC/osteonectin as a powerful independent prognostic marker for short disease-free interval (DFI) (p < 0.002) and poor overall survival (OS) (p = 0.018) of HNSCC patients. In combination with other ECM proteins found in our analysis, PAI-1 and uPA, the association with DFI and OS became even more significant (p < 0.001). Our study represents the first instance of SPARC as an independent prognostic marker in HNSCC.

Approximate processing of massive continuous quantile queries over high-speed data streams

Quantile computation has many applications including data mining and financial data analysis. It has been shown that an is an element of-approximate summary can be maintained so that, given a quantile query d (phi, is an element of), the data item at rank [phi N] may be approximately obtained within the rank error precision is an element of N over all N data items in a data stream or in a sliding window. However, scalable online processing of massive continuous quantile queries with different phi and is an element of poses a new challenge because the summary is continuously updated with new arrivals of data items. In this paper, first we aim to dramatically reduce the number of distinct query results by grouping a set of different queries into a cluster so that they can be processed virtually as a single query while the precision requirements from users can be retained. Second, we aim to minimize the total query processing costs. Efficient algorithms are developed to minimize the total number of times for reprocessing clusters and to produce the minimum number of clusters, respectively. The techniques are extended to maintain near-optimal clustering when queries are registered and removed in an arbitrary fashion against whole data streams or sliding windows. In addition to theoretical analysis, our performance study indicates that the proposed techniques are indeed scalable with respect to the number of input queries as well as the number of items and the item arrival rate in a data stream.

Morbidity due to Schistosoma mansoni: an epidemiological assessment of distended abdomen syndrome in Ugandan school children with observations before and 1-year after anthelminthic chemotherapy

The objectives of this study were to determine the prevalence and distribution of distended abdomens among Ugandan school children across a range of eco-epidemiological settings and to investigate the relationship between distended abdomens and helminth infections, in particular Schistosoma mansoni, before and 1-year after anthelminthic treatment. A cross-sectional survey was conducted on 4354 school children across eight districts, with a longitudinal 1-year follow-up of 2644 children (60.7%). On both occasions, parasitological, biometrical and clinical data were collected for each child. Baseline prevalence of S. mansoni and hookworms was 44.3% and 51.8%, respectively. Distended abdomens, defined as an abdominal circumference ratio (ACR) >1.05, were observed in 2.5% of the sampled children, several of whom presented with particularly severe distensions necessitating hospital referral. ACR scores were highly overdispersed between districts and schools. Multivariate regression analysis revealed that S. mansoni infection accounted for only a small fraction of ACR variation, suggesting that either single point prevalence and intensity measures failed to reflect this more chronically evolved morbidity and/or that other interacting factors were involved, e.g. malnutrition and malaria. At 1-year follow-up, ACR scores showed an overall trend of regression towards the mean, potentially indicative of amelioration following chemotherapy, but geographic overdispersion still remained. © 2006 Royal Society of Tropical Medicine and Hygiene.

A Bayesian hierarchical model for categorical longitudinal data from a social survey of immigrants

The paper investigates a Bayesian hierarchical model for the analysis of categorical longitudinal data from a large social survey of immigrants to Australia. Data for each subject are observed on three separate occasions, or waves, of the survey. One of the features of the data set is that observations for some variables are missing for at least one wave. A model for the employment status of immigrants is developed by introducing, at the first stage of a hierarchical model, a multinomial model for the response and then subsequent terms are introduced to explain wave and subject effects. To estimate the model, we use the Gibbs sampler, which allows missing data for both the response and the explanatory variables to be imputed at each iteration of the algorithm, given some appropriate prior distributions. After accounting for significant covariate effects in the model, results show that the relative probability of remaining unemployed diminished with time following arrival in Australia.

A simple method to localise pleiotropic susceptibility loci using univariate linkage analyses of correlated traits

Univariate linkage analysis is used routinely to localise genes for human complex traits. Often, many traits are analysed but the significance of linkage for each trait is not corrected for multiple trait testing, which increases the experiment-wise type-I error rate. In addition, univariate analyses do not realise the full power provided by multivariate data sets. Multivariate linkage is the ideal solution but it is computationally intensive, so genome-wide analysis and evaluation of empirical significance are often prohibitive. We describe two simple methods that efficiently alleviate these caveats by combining P-values from multiple univariate linkage analyses. The first method estimates empirical pointwise and genome-wide significance between one trait and one marker when multiple traits have been tested. It is as robust as an appropriate Bonferroni adjustment, with the advantage that no assumptions are required about the number of independent tests performed. The second method estimates the significance of linkage between multiple traits and one marker and, therefore, it can be used to localise regions that harbour pleiotropic quantitative trait loci (QTL). We show that this method has greater power than individual univariate analyses to detect a pleiotropic QTL across different situations. In addition, when traits are moderately correlated and the QTL influences all traits, it can outperform formal multivariate VC analysis. This approach is computationally feasible for any number of traits and was not affected by the residual correlation between traits. We illustrate the utility of our approach with a genome scan of three asthma traits measured in families with a twin proband.

Constructing internationally comparable real income aggregates by combining sparse benchmark data with annual national accounts data: A state-space approach

The importance of availability of comparable real income aggregates and their components to applied economic research is highlighted by the popularity of the Penn World Tables. Any methodology designed to achieve such a task requires the combination of data from several sources. The first is purchasing power parities (PPP) data available from the International Comparisons Project roughly every five years since the 1970s. The second is national level data on a range of variables that explain the behaviour of the ratio of PPP to market exchange rates. The final source of data is the national accounts publications of different countries which include estimates of gross domestic product and various price deflators. In this paper we present a method to construct a consistent panel of comparable real incomes by specifying the problem in state-space form. We present our completed work as well as briefly indicate our work in progress.

BEM-ESTAR NO TRABALHO E PERCEPÇÃO DE SUCESSO NA CARREIRA COMO ANTECEDENTES DE INTENÇÃO DE ROTATIVIDADE.

O objetivo geral deste estudo foi analisar, interpretar e discutir as relações entre as percepções de sucesso na carreira, bem-estar no trabalho e a intenção de rotatividade em trabalhadores da Região Sudeste do Brasil. Participaram desta pesquisa 500 trabalhadores que atuam no estado de São Paulo em organizações não governamentais, públicas e privadas. Como instrumento para coleta de dados foi utilizado um questionário de autopreenchimento composto de cinco escalas que mediram as variáveis da pesquisa. A presente pesquisa se propôs a apresentar, interpretar e discutir as relações entre as variáveis, como também, testar as hipóteses referentes ao modelo conceitual proposto, por meio de uma pesquisa de natureza transversal com abordagem quantitativa, cujos dados coletados foram analisados por aplicação de técnicas estatísticas paramétricas (cálculos de estatísticas descritivas: médias, desvio padrão, teste t e correlações; cálculos de estatísticas multivariadas: análise de regressão linear múltipla stepwise e teste da normalidade das variáveis, por meio do teste de Kolmogorov-Smirnov). O tratamento e análise dos dados foram realizados pelo software estatístico Statistical Package for the Social Science SPSS, versão 18.0 para Windows. Os resultados obtidos demonstraram que as dimensões de bem-estar no trabalho exercem forte e significativo impacto sobre a intenção de rotatividade dos profissionais, enquanto que a percepção de sucesso na carreira contribuiu com valores baixos neste impacto, devido ao formato do modelo hipotético. A pesquisa possibilitou concluir que quanto mais a empresa se preocupa em proporcionar um ambiente de trabalho que seja animador, interessante e que cause entusiasmo, menos os profissionais pensarão em deixá-la.

O IMPACTO DA ESPIRITUALIDADE NO TRABALHO E DE PERCEPÇÃO DE SAÚDE ORGANIZACIONAL SOBRE COMPORTAMENTOS DE CIDADANIA ORGANIZACIONAL

Cada vez mais o fator humano está em evidência no mercado competitivo e globalizado. Por isso, constantemente, as empresas se preocupam com a qualidade do trabalho, para que seus colaboradores sintam prazer em sua realização, não sendo tão agredidos pelas pressões do dia a dia. Nesse contexto, esta dissertação teve como objetivo geral analisar as relações entre espiritualidade no trabalho, percepção de saúde organizacional e comportamentos de cidadania organizacional entre professores universitários. Participaram deste estudo 82 trabalhadores de ambos os sexos, com idade entre 28 e 63 anos, os quais atuam no Estado de São Paulo em Instituições de Ensino Superior públicas e privadas. Como instrumento para coleta de dados foi utilizado um questionário de autopreenchimento composto de três escalas que mediram as variáveis da pesquisa. Assim, o estudo se propôs a apresentar, interpretar e discutir as relações entre as variáveis, como também, testar hipóteses referentes ao modelo conceitual proposto, por meio de uma pesquisa com abordagem quantitativa, cujos dados coletados foram analisados por aplicação de técnicas estatísticas paramétricas (cálculo de estatísticas descritivas: médias, desvios padrão, índice de precisão de medidas, teste t e correlações; cálculos de estatísticas multivariadas: regressão linear múltipla padrão. A análise dos dados foi realizada pelo software estatístico Statistical Package for the Social Science SPSS, versão 19.0 para Windows. Os resultados obtidos demonstraram que dentre as três dimensões de comportamentos de cidadania organizacional, apenas duas divulgação da imagem da organização e cooperação com os colegas receberam impacto positivo de percepção de saúde organizacional e espiritualidade no trabalho. Para estas duas classes de ações de cidadania organizacional ficou mais evidenciado o poder de impacto no trabalho. O estudo possibilitou concluir que ações de sugestões criativas realizadas pelos empregados, não sofre influências do quanto eles acreditam que a empresa tem uma saúde satisfatória e do quanto eles vivenciam, ou não, a espiritualidade no ambiente organizacional.

Rule induction for data exploration

This paper describes how the statistical technique of cluster analysis and the machine learning technique of rule induction can be combined to explore a database. The ways in which such an approach alleviates the problems associated with other techniques for data analysis are discussed. We report the results of experiments carried out on a database from the medical diagnosis domain. Finally we describe the future developments which we plan to carry out to build on our current work.

Probabilistic principal component analysis

Principal component analysis (PCA) is a ubiquitous technique for data analysis and processing, but one which is not based upon a probability model. In this paper we demonstrate how the principal axes of a set of observed data vectors may be determined through maximum-likelihood estimation of parameters in a latent variable model closely related to factor analysis. We consider the properties of the associated likelihood function, giving an EM algorithm for estimating the principal subspace iteratively, and discuss the advantages conveyed by the definition of a probability density function for PCA.