<p>This thesis describes the use of nuclear magnetic resonance (NMR) spectrometry as an analytical tool. The theory of NMR spectroscopy in general and quantitative NMR spectrometry (qNMR) in particular is described and the instrumental properties and parameter setups for qNMR measurements are discussed. Examples of qNMR are presented by impurity determination of pharmaceutical compounds and analysis of urine samples from rats fed with either water or a drug (metabolic profiling). The instrumental parameter setup of qNMR and traditional data pre-treatments are examined. Spectral smoothing by convolution with a triangular function, which is an unusual application in this context, was shown to be successful regarding the sensitivity and robustness of the method in paper II. In addition, papers III and IV comprise the field of peak alignment, especially designed for ¹H-NMR spectra of urine samples. This is an important preprocessing tool when multivariate analysis is to be applied. A novel peak alignment method was developed and compared to the traditional bucketing approach and a conceptually different alignment method.</p><p>Univariate, multivariate, linear and nonlinear data analyses were applied to qNMR data. In papers I–II, calibration models were created to examine the potential of qNMR for these applications. The data analysis in papers III–VI was mainly explorative. The potential of data fusion and data correlation was examined in order to increase the possibilities of analysing the highly complex samples from metabolic profiling (papers V–VI). Data from LC/MS analysis of the same samples were used with the ¹H-NMR data in different ways. Correlation analyses between the¹H-NMR data and the drug metabolites identified from the LC/MS data were also performed. In this process, data fusion proved to be a valuable tool.</p>

This thesis describes the use of nuclear magnetic resonance (NMR) spectrometry as an analytical tool. The theory of NMR spectroscopy in general and quantitative NMR spectrometry (qNMR) in particular is described and the instrumental properties and parameter setups for qNMR measurements are discussed. Examples of qNMR are presented by impurity determination of pharmaceutical compounds and analysis of urine samples from rats fed with either water or a drug (metabolic profiling). The instrumental parameter setup of qNMR and traditional data pre-treatments are examined. Spectral smoothing by convolution with a triangular function, which is an unusual application in this context, was shown to be successful regarding the sensitivity and robustness of the method in paper II. In addition, papers III and IV comprise the field of peak alignment, especially designed for 1H-NMR spectra of urine samples. This is an important preprocessing tool when multivariate analysis is to be applied. A novel peak alignment method was developed and compared to the traditional bucketing approach and a conceptually different alignment method. Univariate, multivariate, linear and nonlinear data analyses were applied to qNMR data. In papers I–II, calibration models were created to examine the potential of qNMR for these applications. The data analysis in papers III–VI was mainly explorative. The potential of data fusion and data correlation was examined in order to increase the possibilities of analysing the highly complex samples from metabolic profiling (papers V–VI). Data from LC/MS analysis of the same samples were used with the 1H-NMR data in different ways. Correlation analyses between the 1H-NMR data and the drug metabolites identified from the LC/MS data were also performed. In this process, data fusion proved to be a valuable tool.

134 f. / Submitted by Ana Hilda Fonseca (anahilda@ufba.br) on 2013-09-19T14:49:05Z No. of bitstreams: 1 Tese_Vanjoaldo Lopes.pdf: 3691974 bytes, checksum: 4acbb7d5e3b7ac76fe0b2ff6e4a01cc2 (MD5) / Approved for entry into archive by Ana Hilda Fonseca(anahilda@ufba.br) on 2013-09-19T15:13:57Z (GMT) No. of bitstreams: 1 Tese_Vanjoaldo Lopes.pdf: 3691974 bytes, checksum: 4acbb7d5e3b7ac76fe0b2ff6e4a01cc2 (MD5) / Made available in DSpace on 2013-09-19T15:13:57Z (GMT). No. of bitstreams: 1 Tese_Vanjoaldo Lopes.pdf: 3691974 bytes, checksum: 4acbb7d5e3b7ac76fe0b2ff6e4a01cc2 (MD5) Previous issue date: 2012 / CAPES, FAPESB, CNPQ / Buscando minimizar a dependência dos combustíveis fosseis, fontes energéticas alternativas e renováveis estão em franco desenvolvimento, ganhando cada vez mais espaço na matriz energética mundial e levando à diminuição dos impactos ambientais. Neste contexto, muitas pesquisas são realizadas, buscando o aumento da produção de biodiesel e a garantia da sua qualidade. Em um país como Brasil, que possui vasto território, onde muitas oleaginosas e gorduras animais podem ser usadas para produzir biodiesel, investigar a origem do biodiesel é uma necessidade, uma vez que a qualidade do biodiesel está relacionada às matérias-primas que o produziu. Neste trabalho, determinou-se a composição de amostras de biodiesel em relação aos tipos de matéria-prima através da cromatografia a gás associada à calibração multivariada. Para tal, foram desenvolvidas três modelagens por PLS, a partir de cromatogramas de amostras de biodiesel obtidos empregando a norma EN 14103, onde foi possível identificar, com segurança estatística, a composição das matérias-primas de amostras de B100. As duas primeiras modelagens foram realizadas com as áreas dos picos cromatográficos e com as áreas normalizadas, respectivamente; nestas duas modelagens, os picos foram integrados manualmente. Na terceira modelagem, os cromatogramas foram previamente alinhados usando o algoritmo COW, e todo o cromatograma foi explorado pelo PLS. Os procedimentos foram aplicados a misturas de biodiesel quaternárias (soja, sebo bovino, girassol e dendê), sendo alcançados parâmetros similares para as duas primeiras modelagens na determinação da composição do biodiesel quanto as suas matérias-primas. Na modelagem das áreas não normalizadas, nos conjuntos de calibração encontraram-se valores de RMSEC < 4,40%; RMSECV < 5,36%; R2 (calibração) > 0,973 e R2 (Validação Cruzada) > 0,962; o conjunto de previsão apresentou correlação > 0,992 e RMSEP < 3,57%. Para a modelagem das áreas normalizadas, encontraram-se valores: RMSEC < 4,70%; RMSECV < 5,34%; R2 (calibração) > 0,985; R2 (Validação Cruzada) > 0,963; correlação > 0,989 e RMSEP < 3,43%. A terceira modelagem, com os cromatogramas totais alinhados, encontraram-se valores: RMSEC < 5,35%; RMSECV < 9,14%; R2 (calibração) > 0,955 e R2 (Validação Cruzada) > 0,875; Correlação > 0,966 e RMSEP < 7,19%. As duas primeiras modelagens estabeleceram parâmetros análogos, exatos e seguros para avaliar o teor de cada tipo de biodiesel na composição da mistura B100. A terceira modelagem apresentou parâmetros inferiores aos das duas primeiras modelagens; este fato pode ser explicado porque, nesta modelagem, a altura (sinal) foi a variável avaliada, e por sua vez a altura é um dado cromatográfico de menor confiabilidade que a área dos picos. / Salvador

<p>This thesis is based on five papers addressing variance reduction in different ways. The papers have in common that they all present new numerical methods.</p><p>Paper I investigates quantitative structure-retention relationships from an image processing perspective, using an artificial neural network to preprocess three-dimensional structural descriptions of the studied steroid molecules.</p><p>Paper II presents a new method for computing free energies. Free energy is the quantity that determines chemical equilibria and partition coefficients. The proposed method may be used for estimating, e.g., chromatographic retention without performing experiments.</p><p>Two papers (III and IV) deal with correcting deviations from bilinearity by so-called peak alignment. Bilinearity is a theoretical assumption about the distribution of instrumental data that is often violated by measured data. Deviations from bilinearity lead to increased variance, both in the data and in inferences from the data, unless invariance to the deviations is built into the model, e.g., by the use of the method proposed in paper III and extended in paper IV.</p><p>Paper V addresses a generic problem in classification; namely, how to measure the goodness of different data representations, so that the best classifier may be constructed. </p><p>Variance reduction is one of the pillars on which analytical chemistry rests. This thesis considers two aspects on variance reduction: before and after experiments are performed. Before experimenting, theoretical predictions of experimental outcomes may be used to direct which experiments to perform, and how to perform them (papers I and II). After experiments are performed, the variance of inferences from the measured data are affected by the method of data analysis (papers III-V).</p>

This thesis is based on five papers addressing variance reduction in different ways. The papers have in common that they all present new numerical methods. Paper I investigates quantitative structure-retention relationships from an image processing perspective, using an artificial neural network to preprocess three-dimensional structural descriptions of the studied steroid molecules. Paper II presents a new method for computing free energies. Free energy is the quantity that determines chemical equilibria and partition coefficients. The proposed method may be used for estimating, e.g., chromatographic retention without performing experiments. Two papers (III and IV) deal with correcting deviations from bilinearity by so-called peak alignment. Bilinearity is a theoretical assumption about the distribution of instrumental data that is often violated by measured data. Deviations from bilinearity lead to increased variance, both in the data and in inferences from the data, unless invariance to the deviations is built into the model, e.g., by the use of the method proposed in paper III and extended in paper IV. Paper V addresses a generic problem in classification; namely, how to measure the goodness of different data representations, so that the best classifier may be constructed. Variance reduction is one of the pillars on which analytical chemistry rests. This thesis considers two aspects on variance reduction: before and after experiments are performed. Before experimenting, theoretical predictions of experimental outcomes may be used to direct which experiments to perform, and how to perform them (papers I and II). After experiments are performed, the variance of inferences from the measured data are affected by the method of data analysis (papers III-V).

This thesis investigates the intonation of Argentine Spanish in Queens, NYC, with the goal of verifying if the unique prosody of producing early peak alignments in the F0 of Argentine Spanish, specifically of Porteños (those from Buenos Aires), is maintained among the intense contact influences with other varieties of Spanish in the area. Previous studies have reported this early peak alignment phenomenon in the Spanish spoken in Buenos Aires, and this paper strives to see if this still occurs among Argentine Spanish speakers in New York City. The Buenos Aires speakers were compared with other native Argentine Spanish speakers in New York City who originated from provinces other than Buenos Aires (primarily from Mendoza) to verify if the dialectal varieties of Argentine Spanish had remained the same under the intense language contact situation of living in Queens. The data in the current study are from interviews recorded during the summer of 2014 in the Queens, NYC neighborhood of Elmhurst. Acoustic information obtained includes total syllable duration, F0 measurements, and F0 patterns. Additional linguistic variables included vowel type and vowel syllable position within a word. Extralinguistic variables included speaker sex, age, origin in Argentina, educational level, number of years in NYC, and number of years in Argentina. Results indicate that early peak alignment does indeed occur among Argentine speakers in Queens, NYC; however, it is interesting to note that it not only occurs in the informants from Buenos Aires as predicted, but in the informants from outside Buenos Aires as well. This suggests that the Outside Buenos Aires speakers are undergoing prosodic dialectal leveling with their pitch accent patterns and an increase in stressed syllable duration as occur naturally among the Buenos Aires speakers.