Travelling wave ion mobility spectrometry (TWIMS) in combination with ultra-high performance liquid chromatography (UHPLC) and mass spectrometry (MS) has been applied successfully for the untargeted, global metabolic profiling of biofluids such as mouse plasma and saliva. Methods based on UHPLC-MS alone and in combination with ion mobility spectrometry (UHPLC-IM-MS) have been developed and validated for the untargeted metabolite profiling of saliva, obtained non-invasively by passive drool. Three separate metabolic profiling studies have been carried out in conjunction with bioinformatics strategies to identify potential metabolomic biomarker ions that are associated with efficacy of rice bran in colorectal cancer, physiological stress and that have the potential for the diagnosis of asthma. The advantages offered by the utility of ion mobility in UHPLC-MS based metabolic profiling studies, including the increased analytical space, mass spectral clean-up of contaminants such as PEG post-UHPLC-IM-MS analysis, enhancement of the selectivity of targeted metabolites as well as the potential for the identification of metabolites by comparison of ion mobility drift times have been highlighted. Ten potential metabolic biomarker ions of asthma have been identified from the moderate asthmatics from untargeted metabolite profiling of saliva by UHPLC-MS. A predictive model based on partial least squares discriminant analysis (PLS-DA) has been constructed using these ten discriminant ions, which demonstrates good predictive capability for moderate asthmatics and controls. Potential metabolic biomarker ions of physiological stress have been identified through untargeted metabolite profiling analysis of saliva samples collected before and after exercise by UHPLC-IM-MS. Valerolactam has been identified as a potential biomarker of physiological stress from saliva by comparison of retention time, ion mobility drift time and MS/MS spectra with a standard of δ-valerolactam.

Scanning Laser Epitaxy (SLE) is a new laser-based layer-by-layer generative manufacturing technology being developed in the Direct Digital Manufacturing Laboratory at Georgia Tech. SLE allows creation of geometrically complex three-dimensional components with as-desired microstructure through controlled melting and solidification of stationary metal-alloy powder placed on top of like-chemistry substrates. The proposed research seeks to garner knowledge about the fundamental physics of SLE through simulation-based studies and apply this knowledge for hot section turbine component repair and ultimately extend the process capability to enable one-step manufacture of complex gas turbine components. Prior methods of repair specifically for hot-section Ni-base superalloys have shown limited success, failed to consistently maintain epitaxy in the repaired part and suffered from several mechanical and metallurgical defects. The use of a fine focused laser beam, close thermal control and overlapping raster scan pattern allows SLE to perform significantly better on a range of so-called “non-weldable” Ni-base superalloys. The process capability is expanded further through closed-loop feedback control of melt pool temperature using an infra-red thermal camera. The process produces dense, crack-free and epitaxial deposit for single-crystal (SX) (CMSX4), equiaxed (René-80, IN 100) and directionally solidified (DS) (René-142) Ni-based superalloys. However, to enable consistent and repeatable production of defect-free parts and future commercial implementation of the technology several concerns related to process capabilities and fundamental physics need to be addressed. To explore the process capability, the fabricated components are characterized in terms of several geometrical, mechanical and metallurgical parameters. An active-contour based image analysis technique has been developed to obtain several microstructural responses from the optical metallography of sample cross-sections and the process goes through continuous improvement through optimization of the process parameters through subsequent design of experiments. The simulation-based study is aimed at developing a multiphysics model that captures the fundamental physics of the fabrication process and allows the generation of constitutive equations for microstructural transitions and properties. For this purpose, a computational fluid dynamics (CFD) finite-volume solver is used to model the melting and solidification process. The development work also focuses on studying process response to different superalloy materials and implementing a multivariate statistical process control that allows efficient management and optimization of the design parameter space. In contrast to the prior work on single-bead laser scan, the model incorporates the raster scan pattern in SLE and the temperature dependent local property variations. The model is validated through thermal imaging data. The flow-thermal model is further tied to an empirical microstructural model through the active-contour based optical image analysis technique, which enables the identification of several microstructural transitions for laser beam describing a raster scan pattern. The CFD model can effectively be coupled with finite element solver to assess the stress and deformation and can be coupled with meso-scale models (Cellular Automata) to predict different microstructural evolutions. The research thus allows extending the SLE process to different superalloy materials, performs statistical monitoring of the process, and studies the fundamental physics of the process to enable formulation of constitutive relations for use in closed-loop feedback control; thus imparting ground breaking capability to SLE to fabricate superalloy components with as-desired microstructures.

Thesis (PhD)--Stellenbosch University, 2013. / ENGLISH ABSTRACT: Introduction: Wine production is a complex biotechnological process aiming at productively coordinating the interactions and outputs of several biological systems, including grapevine and many microorganisms such as wine yeast and wine bacteria. High-throughput data generating tools in the elds of genomics, transcriptomics, proteomics, metabolomics and microbiomics are being applied both locally and globally in order to better understand complex biological systems. As such, the datasets available for analysis and mining include de novo datasets created by collaborators as well as publicly available datasets which one can use to get further insight into the systems under study. In order to model the complexity inherent in and across these datasets it is necessary to develop methods and approaches based on network theory and multivariate data analysis as well as to explore the intersections between these two approaches to data modelling, mining and interpretation. Networks: The traditional reductionist paradigm of analysing single components of a biological system has not provided tools with which to adequately analyse data sets that are attempting to capture systems-level information. Network theory has recently emerged as a new discipline with which to model and analyse complex systems and has arisen from the study of real and often quite large networks derived empirically from the large volumes of data that have collected from communications, internet, nancial and biological systems. This is in stark contrast to previous theoretical approaches to understanding complex systems such as complexity theory, synergetics, chaos theory, self-organised criticality, and fractals which were all sweeping theoretical constructs based on small toy models which proved unable to address the complexity of real world systems. Multivariate Data Analysis: Principle components analysis (PCA) and Partial Least Squares (PLS) regression are commonly used to reduce the dimensionality of a matrix (and amongst matrices in the case of PLS) in which there are a considerable number of potentially related variables. PCA and PLS are variance focused approaches where components are ranked by the amount of variance they each explain. Components are, by de nition, orthogonal to one another and as such, uncorrelated. Aims: This thesis explores the development of Computational Biology tools that are essential to fully exploit the large data sets that are being generated by systems-based approaches in order to gain a better understanding of winerelated organisms such as grapevine (and tobacco as a laboratory-based plant model), plant pathogens, microbes and their interactions. The broad aim of this thesis is therefore to develop computational methods that can be used in an integrated systems-based approach to model and describe di erent aspects of the wine making process from a biological perspective. To achieve this aim, computational methods have been developed and applied in the areas of transcriptomics, phylogenomics, chemiomics and microbiomics. Summary: The primary approaches taken in this thesis have been the use of networks and multivariate data analysis methods to analyse highly dimensional data sets. Furthermore, several of the approaches have started to explore the intersection between networks and multivariate data analysis. This would seem to be a logical progression as both networks and multivariate data analysis are focused on matrix-based data modelling and therefore have many of their roots in linear algebra. / AFRIKAANSE OPSOMMING: Inleiding: Wynproduksie is 'n komplekse biotegnologiese proses wat mik op die produktiewe koördinering van verskeie interaksies en uitsette van verskeie biologiese sisteme. Hierdie sisteme sluit in die wingerd, wat van besondere belang is, asook die wyn gis en wyn bakterieë. Hoë-deurset data generasie word huidiglik beide globaal en plaaslik toegepas in die velde van genomika, transkriptomika, proteomika, metabolomika en mikrobiomika. As sulks is hierdie tipe datastelle beskikbaar vir ontleding, bemyning en verkening. Die datastelle kan de novo gegenereer word, met behulp van medewerkers, of dit kan vanuit die publieke databasisse gewerf word waar sulke datastelle dikwels beskikbaar gemaak word sodat verdere insig verkry kan word met betrekking tot die sisteem onder studie. Die hoë-deurset datastelle onder bespreking bevat 'n hoë mate van inherente kompleksiteit, beide ten opsigte van ditself asook tussen verskeie datastelle. Om ten einde hierdie datastelle en hul inherente kompleksiteit te modelleer is dit nodig om metodes en benaderings te ontwikkel wat gesetel is in netwerk teorie en meerveranderlike statistiek. Verdermeer is dit ook nodig om die kruisings tussen netwerk teorie en meerveranderlike statistiek te verken om sodoende die modellering, bemyning, verkening en interpretasie van data te verbeter. Netwerke: Die tradisionele reduksionistiese paradigma, waarby enkele komponente van 'n biologiese sisteem geontleed word, het tot dusver nie voldoende metodes en gereedskap gelewer waarmee datastelle, wat streef om sisteemvlak informasie te bekom, geontleed kan word nie. Netwerk teorie het na vore gekom as 'n nuwe dissipline wat toegepas kan word vir die model-skepping en ontleding van komplekse sisteme. Dit stem uit die studie van egte, dikwels groot netwerke wat empiries afgelei word uit die groot volumes data wat tans na vore kom vanuit kommunikasie-, internet-, nansiële- en biologiese sisteme. Dit is in skrille kontras met vorige teoretiese benaderings wat gestreef het om komplekse sisteme te verstaan met konsepte soos kompleksiteits teorie, synergetics , chaos teorie, self-georganiseerde kritikaliteit en fraktale. Al die bogeneomde is breë teoretiese konstrukte, gebasseer op relatief kleinskaal modelle, wat nie instaat was om oplossings vir die kompleksiteit van egte-wêreld sisteme te bied nie. Meerveranderlike Data-analise: Hoofkomponente-ontleding (PCA) en Partial Least Squares (PLS) regressie word dikwels gebruik om die dimensionaliteit van 'n matriks (en tussen matrikse in die geval van PLS) te verminder. Hierdie matrikse bevat dikwels 'n aansienlike groot hoeveelheid moontlikverwante veranderlikes. PCA en PLS is variansie gedrewe metodes en behels dat komponente gerang word deur die hoeveelheid variansie wat elke component verduidelik. Komponente is by de nisie ortogonaal ten opsigte van mekaar en as sulks ongekorreleerd. Doelwitte: Hierdie tesis verken die ontwikkeling van verskeie Computational Biology metodes wat noodsaaklik is om ten volle die groot skaal datastelle te benut wat tans deur sisteem-gebasseerde benaderings gegenereer word. Die doel is om beter begrip en kennis van wyn verwante organismes te kry, hierdie organismes sluit in die wingerd (met tabak as laboratorium-gebasseerde plant model), plant patogene en microbes sowel as hulle interaksies. Die breë mikpunt van hierdie tesis is dus om gerekenaardiseerde metodes te ontwikkel wat gebruik kan word in 'n geintergreerde sisteem-gebaseerde benadering tot die modellering en beskrywing van verskillende aspekte van die wynmaak proses vanuit 'n biologiese standpunt. Om die mikpunt te bereik is gerekenaardiseerde metodes ontwikkel en toegepas in die velde van transkriptomika, logenomika, chemiomika en mikrobiomika. Opsomming: Die primêre benadering geneem in hierdie tesis is die gebruik van netwerke en meerveranderlike data-ontleding metodes om hoë-dimensie datastelle te ontleed. Verdermeer, verskeie van die metodes begin om die gemeenskaplike grond tussen netwerke en meerveranderlike data-ontleding te verken. Dit blyk om 'n logiese progressie te wees, aangesien beide netwerke en meerveranderlike data-ontleding gefokus is op matriks-gebaseerde data modellering en dus gewortel is in liniêre algebra.

Challenges encountered in pathogen identification and detection include the genetic heterogeneity of strains within species of some foodborne pathogens, isolation of injured cells, mixed strains or mixed species contamination of foods, and differentiation between viable and dead cells. The first objective of this research was to evaluate an isolation medium that was based on time-delayed release (5 to 6 h) of selective agents in tablet format to a modified Listeria recovery enrichment broth (mLRB) medium for enhanced and rapid recovery of injured Listeria. The second objective involved the use of Fourier transform infrared (FT-IR) spectroscopy and chemometric analysis for the differentiation of: Listeria monocytogenes epidemic clones (ECs); viable versus heat-killed populations; different mixed strains and mixed species of Listeria; and different injury treatments and repair in Listeria populations. Nitrite- or acid-injured Listeria at approximately 10 CFU/ml were recovered in mLRB medium, and cell populations enumerated at various times (12 to 48 h) of incubation at 37oC. Analysis of variance revealed that acid-injured Listeria populations in mLRBS6 (mLRB plus the selective agents at 6 h) were significantly higher (P < 0.05) than those in mLRBS0 (mLRB plus the selective agents at 0 h) at 24 h; however, the differences in populations on these two media were not significant for nitrite-injured Listeria. Cell populations of four strains of Listeria recovered in mLRBTD (mLRB plus the time-delayed release tablets of the selective agents) were significantly higher than when those strains were enriched in the U.S. Food and Drug Administration (FDA), International Organization for Standardization (ISO), and U.S. Department of Agriculture (USDA) broths at 24 h. Comparison between artificially contaminated milk and meat samples with a four-strain cocktail of Listeria resulted in cell populations that were significantly higher (P < 0.05) on mLRBTD for contaminated meat than on mLRBTD for contaminated milk at 24 h. FT-IR spectroscopy in the mid-infrared region (4000 to 600 cm-1) and chemometrics was successfully applied to discriminate L. monocytogenes strains belonging to the same EC (ECII or ECIV) (100% accurate spectral classification), intact and heat-killed populations of each EC strain (100% accurate spectral classification), and spectral wavenumbers 1650 to 1390 cm-1 were used to differentiate heat-killed from intact populations. FT-IR spectroscopy and chemometrics in the wavelength region 1800 to 900 cm-1 could successfully discriminate different mixed strains of L. monocytogenes (98.15% accurate spectral classification) and different mixed species of L. monocytogenes and L. innocua (92.06% accurate spectral classification) from individual strains; Wavelength range 1800 to 900 cm-1 was successfully used to discriminate between intact, acid-injured, and heat-injured Listeria, with repaired cells from acid and heat treatments clustering closer to intact cells (93.33% of spectra accurately classified). Delayed-addition of selective agents to broth medium improves recovery of injured Listeria by allowing repair time, could minimize contamination through manual addition of selective agents, and saves analyst time; FT-IR spectroscopy is a highly discriminatory and reproducible technique that can be used for the differentiation of strains and various physiological states of Listeria.

This study utilizes major-, trace- and rare earth elements, as well as radiogenic isotopes (Rb-Sr, Sm-Nd, Pb), in bulk sediment, extracted glass shards, and discrete ash layers, at Ocean Drilling Program Site 1149 (Izu-Bonin Arc), Deep Sea Drilling Project Site 52 (Mariana Arc), and Integrated Ocean Drilling Program Sites C0011 and C0012 (Nankai Trough) in order to characterize and quantify the abundance of dispersed ash, rather than discrete ash layers, in sediments from the Northwest Pacific Ocean. Combination of the geochemical methods with multivariate statistical techniques, such as Q-mode Factor Analysis and multiple linear regressions, allows for differentiation of unique chemistries of the dispersed ash, and the terrigenous components. Therefore, we can document sources that change through time and space. At Site 1149 the bulk sediment is a mixture of two dust and two dispersed ash sources. The two dust sources show contrasting accumulation patterns changing over at a tectonically and climactically active time in Earth's past (~22 Ma) and yield a more complete history of Asian aridity than has been previously considered. We interpret the source of the ashes as basalt from the Izu-Bonin Front Arc (IBFA) and rhyolite from the Honshu Arc (HR). Comparison of the dispersed ash component to the discrete ash layers suggests that eruption frequency, rather than eruption size, drives the dispersed ash record. In contrast, at Site 52 Chinese Loess, IBFA, dispersed boninite from the Izu-Bonin arc, and a dispersed felsic ash of unknown origin are the sources. Interestingly, there are no boninite layers, yet boninite is dispersed within the sediment. Changes in the volcanic and eolian inputs through time indicate strong arc- and climate-related controls. The bulk sediment at Site C0011 is characterized by eolian dust, HR, and a dacite of unknown origin. Site C0012 is comprised of eolian dust, a dacite of unknown origin, as well as dacite and andesite from the Izu-Bonin Arc. Analysis of the total ash record at these two sites provides insight into subduction zone mass balance and water budgets as well as information about the changes in physical properties that result from the alteration of volcanic ash.

O vinho tinto é rico em compostos fenólicos com atividade antioxidante, capazes de inativar espécies reativas de oxigênio, minimizando danos celulares oriundos do estresse oxidativo, proporcionando uma redução de risco para doenças crônicas não transmissíveis. Assim, os objetivos desta pesquisa foram identificar associações entre a atividade antioxidante in vitro e fatores relacionados ao tipo de uva, região de produção, perfil sensorial, safra, valor comercial e concentração de compostos fenólicos de vinhos tintos produzidos no Brasil, Chile e Argentina. Inicialmente, os vinhos brasileiros (n=29) foram avaliados em relação à atividade antioxidante (ORAC e DPPH), cor instrumental e compostos fenólicos majoritários, no intuito de verificar qual classe de fenólicos estaria associada com a atividade antioxidante. Verificou-se que tanto os compostos fenólicos totais como os flavonóides totais, com destaque aos flavonóides não-antociânicos, se associaram significativamente (p<0,05) com a atividade antioxidante. Em um segundo passo, as características sensoriais, a cor, o valor comercial e a atividade antioxidante das 80 amostras de vinhos Sul-Americanos, distribuídas em Merlot (n=9), Pinot Noir (n=17), Malbec (n=11), Syrah (n=12), Cabernet Sauvignon (n=24), e vinhos de uvas americanas (Vitis labrusca) (n=7) foram avaliados usando estatística multivariada, objetivando-se verificar se a qualidade sensorial das amostras estaria associada com o valor comercial, cor, e à atividade antioxidante. De uma forma geral, os vinhos chilenos e argentinos apresentaram maior atividade antioxidante, valor comercial, intensidade de odor, qualidade sensorial, índice de acidez e taninos, ao passo que os vinhos brasileiros obtiveram os menores valores para os atributos sensoriais. Os vinhos de uvas americanas apresentaram menores valores para todas as variáveis. As varietais Syrah, Malbec e Cabernet Sauvignon apresentaram maior capacidade antioxidante e melhores características sensoriais, sendo que esse resultado foi independente da safra e de procedência. Como última etapa, as amostras de vinhos produzidas com uva V. vinifera (n=73) foram classificadas, usando análise hierárquica de agrupamentos, de acordo com o valor comercial, qualidade sensorial e capacidade antioxidante medida por ORAC e DPPH, e os grupos foram caracterizados em relação à sua composição fenólica. Os resultados indicaram que a atividade antioxidante se correlacionou positivamente com o conteúdo de fenólicos totais, flavonóides totais, ácido gálico, quercetina, catequina, ácido ferúlico, miricetina, caempferol, e rutina, sendo que apenas os conteúdos de miricetina, ácido gálico e quercetina foram diferentes (p<0,05) entre os grupos. Nenhum composto fenólico avaliado nesse estudo associou-se com a as diferenças sensoriais dos grupos de vinho. / Red wine is rich in phenolic compounds with antioxidant activity, being able to buffer reactive oxygen species, thus decreasing the risk of non-transmissible chronic diseases. In this regard, the objectives of this research aimed at identifying associations between the in vitro antioxidant activity and factors related to grape varietal, region of production, sensory profile, vintage, color, commercial value, and concentration of phenolic compounds of red wines produced in Brazil, Chile, and Argentina. Initially, the Brazilian red wines (n = 29) were assessed in relation to antioxidant activity, instrumental color, and major phenolic compounds with the objective to verify which phenolic class was associated with the antioxidant activity. Both the total phenolic compounds and total flavonoids, with special attention to non-anthocyanin flavonoids, were significantly associated with the antioxidant activity. In a second step, the sensory characteristics, color, commercial value, and antioxidant activity of the 80 red wine samples, which were distributed in Merlot (n=9), Pinot Noir (n=17), Malbec (n=11), Syrah (n=12), Cabernet Sauvignon (n=24), and table wines (Vitis labrusca) (n=7) were evaluated using multivariate statistical techniques, with the aim to verify how the overall perception of quality of wines was related to commercial value, color and antioxidant activity. In a general way, te Chilean and Argentinean red wines displayed a higher antioxidant activity, commercial value, intensity of odors, sensory perception of quality, acidity level, and tannin level, whereas the Brazilian samples obtained the lowest values for the sensory attributes. The table wines presented the lowest values for all response variables. Syrah, Malbec and Cabernet Sauvignon varietals presented the highest antioxidant activity and most favorable sensory features, and this result was independent of wine\'s vintage and origin. As a last step, the wines produced with V. vinifera grapes (n=73) were classified, using hierarchical cluster analysis, in relation to commercial value, sensory quality and antioxidant activity measured by ORAC and DPPH assays, and the groups were characterised in relation to the phenolic composition.The results showed that the antioxidant capacity correlated to the total contents of phenolic compounds, flavonoids, gallic acid, quercetin, catechin, ferulic acid, myricetin, kaempferol, and rutin, where only the contents of quercetin, gallic acid, and myricetin were different (p < 0.05) whithin clusters. None of the phenolic compounds analysed in this research was associated with sensory differences within clusters.

Orientador: Carlos Roberto Padovani / Resumo: O futebol de 5 é uma modalidade de desporto adaptada exclusivamente para atletas cegos. A seleção brasileira de futebol de 5 consagrou-se multicampeã nos mais importantes campeonatos mundias e nas Paralimpíadas, sendo considerada a melhor seleção do mundo nessa modalidade e tendo em sua escalação atletas eleitos os melhores do mundo. Nesse contexto, o objetivo desta pesquisa consiste em construir o perfil de atletas de futebol de 5 segundo as características biomotoras avaliadas no protocolo de testes físicos aplicados à seleção brasileira de futebol de 5 quanto à posição e à titularidade, utilizando-se das técnicas multivariadas de dados: Análise de Agrupamento, Análise de Correlação Canônica, Análise de Componentes Principais e Análise Fatorial. Os resultados das análises de caráter exploratório indicam que não há um perfil definido como o padrão dos atletas da seleção brasileira de futebol de 5 no que se refere à posição e à titularidade em quadra, sendo possível, nesses aspectos, observar associações entre algumas características biomotoras dos atletas. / Abstract: 5-a-side football is a sport adapted exclusively for blind athletes. The Brazilian national 5-a-side football team has won several of the most important world championships and Paralympic medals. Thus, it is considered the best 5-a-side football team in the world and it has in its roster athletes named the best in the world. In this context, this research aims to determine the profile of 5-a-side football players according to the biomotor characteristics evaluated with the protocol of physical tests applied to the Brazilian 5-a-side football team regarding position on the field and status as a starter or substitute player, using multivariate data analysis techniques. The results of the exploratory analyses indicate that there is no profile defined as the standard for the Brazilian national 5-a-side football team with regard to position on the field and status as a starter or substitute player. In these aspects, it is possible to observe associations between some biomotor characteristics of the athletes. / Doutor

This thesis presents the results of compositional and statistical analyses of Iron Age ironworking residues from sites in Scotland, England, Wales and France. As no framework for ferrous archaeometallurgy previously existed in the main research area of Scotland, a catalog of sites was compiled to determine where targeted scientific analyses could be of most use in creating a regional metallurgical profile. Fieldwork carried out at the site of Meunet Planches in France provided the non- British research component, as extant analyses matching this study’s temporal criteria were not available. A total of 80 new SEM-EDS samples were generated (58 from Scotland and 22 from France), and used together with existing site- and regional-level compositional studies to explore chemical behavior following the procedures laid out by Charlton (2007) and others. These included a range of multivariate statistical techniques such as Hierarchical Clustering Analysis (HCA), Principal Component Analysis (PCA), and Discriminant Analysis (DA). These approaches were considered within the wider discussion of smelting “systems” as defined by Dillmann and L’Heritier (2007), in an effort to visualize the relationship between compositional groups and parent geographic regions. Results indicate overall chemical homogeneity within and between the study regions, suggesting that the systems producing the slag were broadly similar in terms of their operation and reduction “efficiency”. This trend remains stable even when accounting for resource-based influence; implying that appreciable similarities existed between system operations (and therefore potentially human decisions) regardless of the size, age, or complexity of manufacturing industries. Deviation from this main compositional group, exhibited by only a handful of sites, seems to be similarly unrelated to temporal or geographic factors. Rather, it appears to follow the diffusion of slag between the two slag Optima identified by Rehren et al (2007), and on several of the outlier sites relates to the production of hypereutectoid steel.

O vinho tinto é rico em compostos fenólicos com atividade antioxidante, capazes de inativar espécies reativas de oxigênio, minimizando danos celulares oriundos do estresse oxidativo, proporcionando uma redução de risco para doenças crônicas não transmissíveis. Assim, os objetivos desta pesquisa foram identificar associações entre a atividade antioxidante in vitro e fatores relacionados ao tipo de uva, região de produção, perfil sensorial, safra, valor comercial e concentração de compostos fenólicos de vinhos tintos produzidos no Brasil, Chile e Argentina. Inicialmente, os vinhos brasileiros (n=29) foram avaliados em relação à atividade antioxidante (ORAC e DPPH), cor instrumental e compostos fenólicos majoritários, no intuito de verificar qual classe de fenólicos estaria associada com a atividade antioxidante. Verificou-se que tanto os compostos fenólicos totais como os flavonóides totais, com destaque aos flavonóides não-antociânicos, se associaram significativamente (p<0,05) com a atividade antioxidante. Em um segundo passo, as características sensoriais, a cor, o valor comercial e a atividade antioxidante das 80 amostras de vinhos Sul-Americanos, distribuídas em Merlot (n=9), Pinot Noir (n=17), Malbec (n=11), Syrah (n=12), Cabernet Sauvignon (n=24), e vinhos de uvas americanas (Vitis labrusca) (n=7) foram avaliados usando estatística multivariada, objetivando-se verificar se a qualidade sensorial das amostras estaria associada com o valor comercial, cor, e à atividade antioxidante. De uma forma geral, os vinhos chilenos e argentinos apresentaram maior atividade antioxidante, valor comercial, intensidade de odor, qualidade sensorial, índice de acidez e taninos, ao passo que os vinhos brasileiros obtiveram os menores valores para os atributos sensoriais. Os vinhos de uvas americanas apresentaram menores valores para todas as variáveis. As varietais Syrah, Malbec e Cabernet Sauvignon apresentaram maior capacidade antioxidante e melhores características sensoriais, sendo que esse resultado foi independente da safra e de procedência. Como última etapa, as amostras de vinhos produzidas com uva V. vinifera (n=73) foram classificadas, usando análise hierárquica de agrupamentos, de acordo com o valor comercial, qualidade sensorial e capacidade antioxidante medida por ORAC e DPPH, e os grupos foram caracterizados em relação à sua composição fenólica. Os resultados indicaram que a atividade antioxidante se correlacionou positivamente com o conteúdo de fenólicos totais, flavonóides totais, ácido gálico, quercetina, catequina, ácido ferúlico, miricetina, caempferol, e rutina, sendo que apenas os conteúdos de miricetina, ácido gálico e quercetina foram diferentes (p<0,05) entre os grupos. Nenhum composto fenólico avaliado nesse estudo associou-se com a as diferenças sensoriais dos grupos de vinho. / Red wine is rich in phenolic compounds with antioxidant activity, being able to buffer reactive oxygen species, thus decreasing the risk of non-transmissible chronic diseases. In this regard, the objectives of this research aimed at identifying associations between the in vitro antioxidant activity and factors related to grape varietal, region of production, sensory profile, vintage, color, commercial value, and concentration of phenolic compounds of red wines produced in Brazil, Chile, and Argentina. Initially, the Brazilian red wines (n = 29) were assessed in relation to antioxidant activity, instrumental color, and major phenolic compounds with the objective to verify which phenolic class was associated with the antioxidant activity. Both the total phenolic compounds and total flavonoids, with special attention to non-anthocyanin flavonoids, were significantly associated with the antioxidant activity. In a second step, the sensory characteristics, color, commercial value, and antioxidant activity of the 80 red wine samples, which were distributed in Merlot (n=9), Pinot Noir (n=17), Malbec (n=11), Syrah (n=12), Cabernet Sauvignon (n=24), and table wines (Vitis labrusca) (n=7) were evaluated using multivariate statistical techniques, with the aim to verify how the overall perception of quality of wines was related to commercial value, color and antioxidant activity. In a general way, te Chilean and Argentinean red wines displayed a higher antioxidant activity, commercial value, intensity of odors, sensory perception of quality, acidity level, and tannin level, whereas the Brazilian samples obtained the lowest values for the sensory attributes. The table wines presented the lowest values for all response variables. Syrah, Malbec and Cabernet Sauvignon varietals presented the highest antioxidant activity and most favorable sensory features, and this result was independent of wine\'s vintage and origin. As a last step, the wines produced with V. vinifera grapes (n=73) were classified, using hierarchical cluster analysis, in relation to commercial value, sensory quality and antioxidant activity measured by ORAC and DPPH assays, and the groups were characterised in relation to the phenolic composition.The results showed that the antioxidant capacity correlated to the total contents of phenolic compounds, flavonoids, gallic acid, quercetin, catechin, ferulic acid, myricetin, kaempferol, and rutin, where only the contents of quercetin, gallic acid, and myricetin were different (p < 0.05) whithin clusters. None of the phenolic compounds analysed in this research was associated with sensory differences within clusters.

The separation of natural and anthropogenically caused climatic changes is an important task of contemporary climate research. For this purpose, a detailed knowledge of the natural variability of the climate during warm stages is a necessary prerequisite. Beside model simulations and historical documents, this knowledge is mostly derived from analyses of so-called climatic proxy data like tree rings or sediment as well as ice cores. In order to be able to appropriately interpret such sources of palaeoclimatic information, suitable approaches of statistical modelling as well as methods of time series analysis are necessary, which are applicable to short, noisy, and non-stationary uni- and multivariate data sets. Correlations between different climatic proxy data within one or more climatological archives contain significant information about the climatic change on longer time scales. Based on an appropriate statistical decomposition of such multivariate time series, one may estimate dimensions in terms of the number of significant, linear independent components of the considered data set. In the presented work, a corresponding approach is introduced, critically discussed, and extended with respect to the analysis of palaeoclimatic time series. Temporal variations of the resulting measures allow to derive information about climatic changes. For an example of trace element abundances and grain-size distributions obtained near the Cape Roberts (Eastern Antarctica), it is shown that the variability of the dimensions of the investigated data sets clearly correlates with the Oligocene/Miocene transition about 24 million years before present as well as regional deglaciation events. Grain-size distributions in sediments give information about the predominance of different transportation as well as deposition mechanisms. Finite mixture models may be used to approximate the corresponding distribution functions appropriately. In order to give a complete description of the statistical uncertainty of the parameter estimates in such models, the concept of asymptotic uncertainty distributions is introduced. The relationship with the mutual component overlap as well as with the information missing due to grouping and truncation of the measured data is discussed for a particular geological example. An analysis of a sequence of grain-size distributions obtained in Lake Baikal reveals that there are certain problems accompanying the application of finite mixture models, which cause an extended climatological interpretation of the results to fail. As an appropriate alternative, a linear principal component analysis is used to decompose the data set into suitable fractions whose temporal variability correlates well with the variations of the average solar insolation on millenial to multi-millenial time scales. The abundance of coarse-grained material is obviously related to the annual snow cover, whereas a significant fraction of fine-grained sediments is likely transported from the Taklamakan desert via dust storms in the spring season. / Die Separation natürlicher und anthropogen verursachter Klimaänderungen ist eine bedeutende Aufgabe der heutigen Klimaforschung. Hierzu ist eine detaillierte Kenntnis der natürlichen Klimavariabilität während Warmzeiten unerlässlich. Neben Modellsimulationen und historischen Aufzeichnungen spielt hierfür die Analyse von sogenannten Klima-Stellvertreterdaten eine besondere Rolle, die anhand von Archiven wie Baumringen oder Sediment- und Eisbohrkernen erhoben werden. Um solche Quellen paläoklimatischer Informationen vernünftig interpretieren zu können, werden geeignete statistische Modellierungsansätze sowie Methoden der Zeitreihenanalyse benötigt, die insbesondere auf kurze, verrauschte und instationäre uni- und multivariate Datensätze anwendbar sind. Korrelationen zwischen verschiedenen Stellvertreterdaten eines oder mehrerer klimatologischer Archive enthalten wesentliche Informationen über den Klimawandel auf großen Zeitskalen. Auf der Basis einer geeigneten Zerlegung solcher multivariater Zeitreihen lassen sich Dimensionen schätzen als die Zahl der signifikanten, linear unabhängigen Komponenten des Datensatzes. Ein entsprechender Ansatz wird in der vorliegenden Arbeit vorgestellt, kritisch diskutiert und im Hinblick auf die Analyse von paläoklimatischen Zeitreihen weiterentwickelt. Zeitliche Variationen der entsprechenden Maße erlauben Rückschlüsse auf klimatische Veränderungen. Am Beispiel von Elementhäufigkeiten und Korngrößenverteilungen des Cape-Roberts-Gebietes in der Ostantarktis wird gezeigt, dass die Variabilität der Dimension der untersuchten Datensätze klar mit dem Übergang vom Oligozän zum Miozän vor etwa 24 Millionen Jahren sowie regionalen Abschmelzereignissen korreliert. Korngrößenverteilungen in Sedimenten erlauben Rückschlüsse auf die Dominanz verschiedenen Transport- und Ablagerungsmechanismen. Mit Hilfe von Finite-Mixture-Modellen lassen sich gemessene Verteilungsfunktionen geeignet approximieren. Um die statistische Unsicherheit der Parameterschätzung in solchen Modellen umfassend zu beschreiben, wird das Konzept der asymptotischen Unsicherheitsverteilungen eingeführt. Der Zusammenhang mit dem Überlapp der einzelnen Komponenten und aufgrund des Abschneidens und Binnens der gemessenen Daten verloren gehenden Informationen wird anhand eines geologischen Beispiels diskutiert. Die Analyse einer Sequenz von Korngrößenverteilungen aus dem Baikalsee zeigt, dass bei der Anwendung von Finite-Mixture-Modellen bestimmte Probleme auftreten, die eine umfassende klimatische Interpretation der Ergebnisse verhindern. Stattdessen wird eine lineare Hauptkomponentenanalyse verwendet, um den Datensatz in geeignete Fraktionen zu zerlegen, deren zeitliche Variabilität stark mit den Schwankungen der mittleren Sonneneinstrahlung auf der Zeitskala von Jahrtausenden bis Jahrzehntausenden korreliert. Die Häufigkeit von grobkörnigem Material hängt offenbar mit der jährlichen Schneebedeckung zusammen, während feinkörniges Material möglicherweise zu einem bestimmten Anteil durch Frühjahrsstürme aus der Taklamakan-Wüste herantransportiert wird.