Thesis (Ph.D. ) -- McMaster University, 1998. / Includes bibliographical references (leaves 75-81). Also available via World Wide Web.

Orientador: José Eduardo de Oliveira / Banca: Flávio Santos de Gusmão Lima / Banca: Alessandra Borin / Resumo: Os óleos lubrificantes exercem papel fundamental no funcionamento dos motores automotivos, pois, além de reduzir o atrito entre as peças, ainda as protegem contra a corrosão. Entretanto, o desempenho do óleo lubrificante pode ser afetado por contaminantes. Embora existam várias normas e trabalhos relacionados a métodos para quantificação de contaminantes em óleo lubrificante, como por exemplo gasolina e óleo diesel, até o alcance de nossos conhecimentos, não há método descrito para quantificação de etanol em óleo lubrificante usado de motores ciclo Otto. Nesse sentido, o presente trabalho teve como objetivo o desenvolvimento e a validação de um método aplicável em rotina para quantificação de etanol em tal óleo lubrificante usado. Para tanto, foram avaliadas as técnicas combinadas: Headspace - Gas Chromatography - Flame Ionization Detector (HS-GC-FID) e Fourier Transform Infra Red Spectroscopy - Total Attenuated Reflectance - Partial Least Squares (FTIR-ATR-PLS), com e sem tratamento prévio das amostras, sendo que os melhores resultados foram obtidos pela técnica FTIR-ATR-PLS, com pré-tratamento por Extração Líquido/líquido (ELL), otimizada por planejamento fatorial. Na sequencia, foram avaliados dois cristais com diferentes ângulos de incidência para obtenção dos espectros por ATR, sendo que o cristal de ZnSe com θ = 45 º mostrou-se mais o mais adequado. Então, a partir dessas melhores condições experimentais, o método foi validado através das figuras de mérito, as quais apresentaram os seguintes resultados: LD (0,049 %), LQ (0,16 %), exatidão (RMSEP = 0,089 % (m/m) de etanol), repetibilidade (0,05 % (m/m) etanol), ajuste (R2 = 0,9997), seletividade média (0,047), sensibilidade (0,011), inverso da sensibilidade analítica (0,016 % (m/m)-1 de etanol), razão sinal ruído (máximo: 812,4 e mínimo: 200,9) e BIAS. Os resultados obtidos mostram... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: The lubricating oils have a crucial role in the operation of automotive engines, not only reduce friction between moving parts, but also protect against corrosion. However, the performance of lubricating oil may be affected by contaminants. Although there are many standards methods and studies related to methods for quantification of contaminants in lubricating oil such as gasoline and diesel oil, to the best our knowledge, there are no described methods for quantification of ethanol in Otto cycle engine used lubricating oil. In that sense, this work aimed the development and validation of an applicable in routine and method to quantify ethanol content in this used lubricating oil. For that were evaluated the combined techniques: Headspace/Gas Chromatography/Flame Ionization Detector (HS-GC-FID) and Fourier Transform Infrared Spectroscopy/Attenuated Total Reflectance/Partial Least Squares (PLS-ATR-FTIR) with and without pretreatment of the samples, and the best results were obtained to the FTIR-ATR-PLS with treatment by ELL (which was optimized by factorial design). Then, two crystals of ATR with differents incident angles were studied to obtain the spectra and the ZnSe crystal with θ = 45 ° was more appropriate for analysis. Then, from the best obtained conditions, the method was validated through the figures of merit, which presented the following results: LD (0.049 %), LQ (0.16 %), accuracy (RMSEP = 0.089 % (w/w) ethanol), repeatability (0,05 % (w/w) ethanol), fit (R2 = 0.9997), mean selectivity (0.047), sensitivity (0.011), inverse analytical sensitivity (0.016% (m / m)-1 of ethanol), signal-to-noise ratio (max: 812.4 and min: 200.9) and BIAS. The results show that the method developed and validated can be implemented, in routine, for quality control laboratories of lubricating oils / Mestre

Orientadores: Marcia Miguel Castro Ferreira, Fabio Augusto / Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Quimica / Made available in DSpace on 2018-08-15T10:17:49Z (GMT). No. of bitstreams: 1 Ribeiro_JulianoSouza_D.pdf: 5735047 bytes, checksum: e7f146614953c780319857f147af11d5 (MD5) Previous issue date: 2009 / Resumo: Atualmente, o café é considerado a segunda bebida mais consumida em todo o mundo, sendo superado somente pela água. Esse consumo representa hoje, cerca de 60 bilhões de dólares anuais, contemplando desde a escolha do grão a ser plantado até o produto final comercializado. No mundo todo, especialistas e pesquisadores buscam meios para reconhecer, valorizar e promover padrões de qualidade para os melhores cafés. Porém, a qualidade da bebida tem se mostrado dependente de vários componentes simultaneamente, e sua avaliação é determinada pela prova ¿de xícara¿, realizada por profissionais experientes na arte de degustar café (provadores). Deste modo, este trabalho visou a construção de modelos quimiométricos de previsão de diversos atributos sensoriais do café arábica brasileiro, a partir da correlação entre o aroma e análises sensoriais. Para isso, a técnica analítica de microextração em fase sólida acoplada a cromatografia gasosa foi utilizada (SPME-GC). Um planejamento experimental realizado com as variáveis experimentais do sistema de SPME indicou as melhores condições para a extração simultânea da maioria dos picos cromatográficos. Com todo o sistema de extração otimizado, foram construídos modelos PLS de previsão para seis atributos sensoriais (acidez, amargor, aroma, bebida, corpo e qualidade global) descritos por provadores, a partir do perfil aromático de amostras de café torrado. Modelos com base em dados espectroscópicos (infravermelho próximo) também foram construídos. Os modelos de regressão PLS gerados a partir dos perfis cromatográficos dos voláteis de cafés arábica torrados e dos dados espectroscópicos previram adequadamente as notas dos seis atributos sensoriais estudados. Os erros de previsão desses modelos foram baixos e compatíveis com os erros médios das notas fornecidas pelos provadores / Abstract: Nowadays, coffee is considered the second most consumed beverage in the whole world, only being surpassed by water. This consumption represents about 60 billion dollars annually, from the choice of the seed to be planted until the final commercialized product. In the entire world, specialists and scientists search for ways to recognize, to promote and to valorize standards of quality for the best coffee beverages. However, the quality of the beverage depends on various compounds simultaneously, and its evaluation is determined by the cup profile carried out by experts in the art of sampling fresh coffee (cuppers). Thus, this work aimed at the construction of chemometric models for the prediction of diverse sensory attributes of Brazilian Arabica coffees from the correlation between their aromas and their sensory analyses. For this, the analytical technique used was solid phase microextraction followed by gas chromatography (SPME-GC). An experimental design carried out with the several variables of the SPME system indicated the best conditions for the simultaneous extraction of the majority of the chromatographic peaks. With the extraction system optimized, PLS prediction models for six sensory attributes (acidity, bitterness, flavour, cleanliness, body and overall quality) described by the cuppers were constructed from the flavour profile of roasted coffee samples. Spectroscopic models based on spectroscopic data (near infrared) were also constructed. The PLS regression models generated from the chromatographic profiles and of the spectroscopic data of roasted Arabica coffee adequately predicted notes of the six sensorial attributes studied. The prediction errors of these models were low and compatible with the average errors of notes supplied by the cuppers / Doutorado / Quimica Analitica / Doutor em Ciências

No description available.

Data processing tools are valuable to the analytical chemist as they can speed up the analysis, and sometimes solve problems that are not feasible to solve in a traditional manner. However, the complexity of many data processing tools can make their use daunting for the inexperienced user. This thesis includes two applications and two tools for data processing. The first application focuses on minimizing the manual input, reducing the time required for a simple task. The second application required more manual input, in the form of parameter selection, but process far more data.  The data processing tools both include features that simplify the manual work required. The first by including visual diagnostics tools that helps in setting the parameters. The second via internal validation that makes the tool’s process more robust and reliable, and thereby less sensitive to small changes in the parameters. No matter how good or precise a data processing tool is, if it is so cumbersome that it is not used by the analytical chemists that need it, it is useless. Therefore, the main focus of this thesis is to make data processing easier. / <p>At the time of the doctoral defense, the following paper was unpublished and had a status as follows: Paper 4: Submitted.</p>

A new era of chemical analysis is upon us. In the past, a small number of samples were selected from a population for use as a statistical representation of the entire population. More recently, advancements in data collection rate, computer memory, and processing speed have allowed entire populations to be sampled and analyzed. The result is massive amounts of data that convey relatively little information, even though they may contain a lot of information. These large quantities of data have already begun to cause bottlenecks in areas such as genetics, drug development, and chemical imaging. The problem is straightforward: condense a large quantity of data into only the useful portions without ignoring or discarding anything important. Performing the condensation in the hardware of the instrument, before the data ever reach a computer is even better. The research proposed tests the hypothesis that clusters of data may be rapidly identified by linear fitting of quantile-quantile plots produced from each principal component of principal component analysis. Integrated Sensing and Processing (ISP) is tested as a means of generating clusters of principal component scores from samples in a hyperspectral near-field scanning optical microscope. Distances from the centers of these multidimensional cluster centers to all other points in hyperspace can be calculated. The result is a novel digital staining technique for identifying anomalies in hyperspectral microscopic and nanoscopic imaging of human atherosclerotic tissue. This general method can be applied to other analytical problems as well.

No description available.

One of the many recorded adaptive responses in respiratory chain complex I deficient cells is the over-expression of the small metal binding proteins, metallothioneins (MTs). The antioxidant properties of MTs putatively protect the deficient cells against oxidative damage, thus limiting further damage and impairment of enzymes involved in energy production. Moreover, the role of metallothioneins in supplying metal cofactors to enzymes and transcription factors in order to promote energy metabolism was previously proposed, which could accompany their role as antioxidants. This view is supported by the observations that MT knockout mice tend to become moderately obese, implying a lower energy metabolic rate. Hence, the involvement of metallothioneins in mitochondrial function and disease cannot be ignored. However, this association is still very vague due to the diversity of their functions and the complexity of the mitochondrion. The use of systems biology technology and more specifically metabolomics technology was thus employed to clarify this association by investigating the metabolic differences between wild type and MT knockout mice in unchallenged conditions as well as when mitochondrial function (energy metabolism) was challenged with exercise and/or a high-fat diet. The metabolic differences between these mice were also studied when complex I of the respiratory chain was inhibited with rotenone. The metabolome content of different tissues and bio-fluids were examined in an untargeted fashion using three standardized analytical platforms and the data mined using modern metabolomics and related statistical methods. Clear metabolic differences were found between the wild type and MT knockout mice during unchallenged conditions. These metabolic differences were persisted and were often amplified when mitochondrial metabolism was specifically challenged through exercise, high-fat intake or complex I inhibition. The data pointed to an overall reduced metabolic rate in the MT knockout mice and possible insulin resistance after the interventions which imply (and confirm) the involvement of MTs in promoting energy metabolism in the wild type mice. / Thesis (Ph.D. (Biochemistry))--North-West University, Potchefstroom Campus, 2012

A demanda comercial de produtos derivados da cana-de-açúcar é a grande motivadora do aprimoramento genético com a finalidade de proporcionar a planta aumento no acúmulo de sucrose e/ou de resistência a ataques de herbívoros. Assim sendo, este trabalho abrange o estudo metabolomico de duas variedades transgênicas da cana-de-açúcar (Bowman-Birk-SBBI e Kunitz- SKTI) e seus respectivos controles através de duas metodologias distintas: a análise quimiométrica do perfil cromatográfico dos polifenóis existentes nas variedades transgênicas e o estudo metabolomico por ressonância magnética nuclear a fim de identificar possíveis diferenças entre as plantas transgênicas em relação aos seus respectivos controles. Nas amostras de folhas foram encontradas nove regiões cromatográficas representativas para a discriminação das variedades SBBI e SKTI. Análises de HPLC-MS/MS foram empregadas para a identificação parcial dos biomarcadores selecionados pelo método OPS, dentre eles: ácido cafeoílaquínico, ácido feruloílaquínico, shaftosídeo ou isoshafitosídeo, além de quatro substâncias parcialmente identificadas: um derivado de apigenina, um glicosídeo da tricina--O-(metoxicinamato), um derivado de flavonóide metoxilado e um derivado de catequina. Através do estudo metabolomico obteve-se uma visão geral sobre os metabólitos produzidos pelas variedades transgênicas e controles e através das análises dos espectros de RMN 1H, J-resolved, COSY 1H-1H, HMBC 13C-1H foi possível identificar a presença de ácidos orgânicos, amino-ácidos, açúcares, flavonóides e fenilpropanóides. Adicionalmente, a análise quimiométrica dos espectros de RMN 1H mostrou não haver diferença significativa entre folhas SBBI e controles e SKTI e controles. Como conclusão pôde-se sugerir que a inserção dos genes inibidores de protease na cana-de-açúcar não afeta as rotas biosintéticas da planta, mas apenas confere maior resistência contra a broca da cana-de-açúcar (Diatrea saccharilis). Entretanto diferenças significativas entre as variedades transgênicas foram encontradas: a variedade SBBI apresenta teor de açucares e fenilpropanóides mais elevados que a variedade SKTI. Conclui-se também que as alterações metabólicas encontradas neste trabalho não são provenientes dos genes inseridos na planta, mas por outro tipo de efeito sofrido nos controles das duas variedades, como por exemplo, variação somaclonal que antecedem a modificação genética. / Comercial demanding of industrial products from sugarcane plants are reponsable for researchs on genetic improvements with the aim to increase sucrose plant acumulation and/or provide resistence against herbivors. Thus, the present work covers metabolomic study of two transgenics varieties of sugarcane (Bowman-Birk-SBBI e Kunitz- SKTI) and their respectives wild (control) plants through two distinct methodologies: chemometrics analysis of polyphenols chromatography profile found into the transgenics varieties and the metabolomic study by nuclear magnetic resonance for identification of possible metabolic alterations comparing transgenics plants and their respective controls. Nine discriminants chromatography regions were detected on SBBI and SKTI leaves samples. HPLC-MS/MS analyses were performed for biomarkers identification selected by OPS method, among then: caffeoylquinic acid, feruloyl quinic acid, shaftoside or isoshaftoside, apigenin derivatives, tricin-O-(methoxycinamate)-glicosilated, methoxylated flavone and catechine derivative. A general vision about metabolites produced for transgenics and control plants could be achived through metabolomic study. Identification of organic acids, amino acids, sugars, phenylpropanoids and flavonoids were possible through 1H NMR, J-resolved, COSY 1H-1H, HMBC 13C-1H. Moreover, chemometrics analysis of the 1H NMR spectra had shown no significant differences between SBBI with wild plant and SKTI with control plants. These results suggest that the biosyntheses pathways are not affected by protease inhibitors genes introduced on sugarcane, but these genes just provides resistence against Diatrea saccharilis. However, metabolic alterations were found between the transgenic plants (SBBI and SKTI). Specially, the variety SBBI presents high levels of sugars and phenylpropanoids compared with SKTI variety. In conclusion, the metabolic variation found in the present are not due to genes introduction, but are originated by other type of effect on wild plants, such as, somaclonal variation before genetical modification.

Near infrared (NIR) spectroscopy is being developed on living tissue models for noninvasively measuring in vivo glucose concentrations in individuals with diabetes. Multivariate calibration models have been built and the selectivity of each multivariate signature has been evaluated by several means. The primary objective of the research detailed in this dissertation is to practically apply noninvasive NIR glucose measurements on animal models for both short-term and long-term studies and preview future human subject evaluations. In the animal study, living tissue spectra were collected through a modified optical interface with hyper- and hypo-glycemia control. Selective measurements of glucose molecules are illustrated by the partial lease squares (PLS) algorithm, net analyte signal (NAS) vector, and hybrid linear analysis (HLA). Each model demonstrates the ability to predict prospective glucose concentrations in the short term. A restraint platform was developed for the long-term study on conscious animals. Conscious animal spectra were collected on multiple days. The anesthetized animal experiment follows on the final day. Principal component analysis (PCA) of spectra collected on different days demonstrates no significant difference between conscious animal spectra and anesthetized animal spectra. Moreover, an NAS vector analysis from conscious animal spectra has the ability predict glucose concentrations which follow the blood glucose transient during the anesthetized animal experiment. This procedure has great potential to be applied in future NIR glucose monitoring device. Before the application of this noninvasive NIR technology on people with diabetes, the impact of skin difference must be determined. In this human subject study, human skin color and baseline spectra were collected and analyzed to determine differences among individuals and within groups of people. To compare in vivo NIR spectra with different skin characteristics, PCA was performed to obtain principal component (PC) scores. Poor correlation between PC scores and skin characteristics concludes that noninvasive near-infrared technology is insensitive to different types of skin. In addition, glucose prediction was performed by a NAS analysis. The prediction results demonstrate that it is feasible to build a NAS glucose model for noninvasive NIR glucose predictions in human subjects.