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The hypothesis tested was that a site in Leflore County, Mississippi, located on the bluff above the Mississippi River flood plain (the Delta) would experience wind speeds adequate for power generation. Wind measurements were collected at a height of 55 m (above ground level) between October 2011 and October 2012. Winds at this height were predominately southeasterly with a mean wind speed less than 4 m/s. Winds did not accelerate above this bluff. Low surface friction of the Delta was not beneficial due to the predominant wind direction. To better understand Delta wind patterns, an S-mode varimax-rotated principal component analysis (RPCA) was performed on monthly 30 m North American Regional Reanalysis (NARR) wind data. Three areas for future wind resource assessment measurements were determined. Each pattern highlighted more energetic wind speeds areas, none of which included the measurement site. The RPCA method was successful in delineating homogeneous wind speed patterns.

1.Prostate Cancer (PC) 1.1.Epidemiology Prostate cancer (PC) is one of the major threats to men’s health worldwide (Siegel et al., 2016; Brawley, 2012; Jahn et al., 2015; Center et al., 2012). In the United States PC was estimated to make up roughly 20% of the new cancer cases in men in 2016. Deaths from PC are expected to account for 8% of cancer associated deaths (Siegel et al., 2016). Epidemiological data from China are still rare and incomplete but were recently supplemented by high-quality data provided by the National Central Cancer Registry of China (NCCR) (Chen et al., 2016). The incidence rate of prostate cancer in China increased from 1998 to 2008 by a factor of 3, from 35.2/100,000 to 110.0/100,000 and the average annual growth rate was as high as 12.07% reaching 60,300 cases in 2015 (Zhu et al., 2015; Coffey, 2001; Baade et al., 2013; Chen et al., 2016). While incidence rates in rural areas remained stable between 2006 and 2009, there was an increase in urban areas, especially documented in Hong Kong and Shanghai. The rapid rise of the incidence rate may be in part related to the aging of the population but there seems to be a strong link to Western-style diet (Lin et al., 2015). A comparison of the incidences of prostate cancer in 2015 showed that although the total number of patients in the United States has reached 3.66 times that of China, the estimated death tolls in the two countries are almost similar (Table 1) (Siegel et al., 2016; Ervik et al., 2016; Chen et al., 2016).Interestingly, the numbers in the European Union (EU, WHO region) are in between which might reflect more regional variations in living conditions and diet. However, further investigations are required to come to valid conclusions. Effectivity of PC treatment and cancer recurrence heavily depend on early detection and proper risk stratification (Moller et al., 2015; Schroder et al., 2012; Klotz et al., 2015; Moyer, 2012). In the US, the proportion of localized prostate cancer accounts for more than 80% of all cases, which is also one of the major reasons the mortality/morbidity rate in the US is much lower than that in Asian countries, and continues to decrease (Moller et al., 2015; Jemal et al., 2015; DeSantis et al., 2014). Therefore, early detection and diagnosis is the most effective way by which to improve the survival rate, and development of new biomarkers and/or reasonable combination of current diagnostic methods is a hot spot in the field of prostate cancer research (Felgueiras et al., 2014). Among countries that have implemented prostate cancer screening strategies, five-year survival rates have improved rapidly in Japan, with an average annual increase of about 11.7% and a 5-year survival rate of 93%, while in China, the annual increase was only 3.7% and the 5-year survival rate was 69.2%(Yao et al., 2021). In 2018, there were 1.3 million new cases of prostate cancer worldwide, and its morbidity and mortality ranked second and fifth among male malignancies, respectively.However, to date no serum or urine biomarker or biomarker panel meets the requirements for highly sensitive and specific detection of PC and differentiation between indolent and significant PC. We here explore the prospects of metabolomics to improve prostate cancer detection, patient stratification and treatment monitoring. 1.2. PC classification and grading The prostate gland is a walnut-sized gland located between the bladder neck and the external urethral sphincter. There are four main zones in the prostate gland: the peripheral zone (posteriorly), the fibromuscular zone (anteriorly), the central zone (centrally) and the transitional zone (surrounding the urethra). The anatomy of the prostate gland is shown in Fig. 1 (Adapted from: Bhavsar et al., 2014).Prostate cancer does not occur uniformly throughout the prostate. Although cancers of the prostate often are multifocal, from 80% to 85% arise from the peripheral zone, 10% to 15% arise from the transition zone, and 5% to 10% arise from the central zone (Buyyounouski et al., 2017). The biopsy Gleason grading system is the most important prognostic marker for prostate cancer. The higher the Gleason score, the higher the malignant degree of prostate cancer. The TNM staging system proposed by AJCC is a widely used independent index that can reflect the progression and prognosis of prostate cancer. Table 2 shows the definitions for clinical and pathological T, N, and M classifications (Buyyounouski et al., 2017). Radical prostatectomy (RP) has become the most effective method for the treatment of localized prostate cancer and some high-risk prostate cancer. RP is used when the cancer is believed to be confined to the prostate gland. During the procedure, the prostate gland and some tissue around the gland, including the seminal vesicles, are removed. Transurethral resection of the prostate, or TURP, which also involves removal of part of the prostate gland, is an approach performed through the penis with an endoscope (small, flexible tube with a light and a lens on the end). This procedure doesn't cure prostate cancer but can remove the obstruction while the doctors plan for definitive treatment. Laparoscopic surgery, done manually or by robot, is another method of removal of the prostate gland. Shortcomings in comprehensive medical check-ups in low- and middle-income countries lead to delayed detection of PC and are causative of high numbers of advanced PC cases at first diagnosis. The performance of available biomarkers is still insufficient and limited applicability, including logistical and financial burdens, impedes comprehensive implementation into health care systems. There is broad agreement on the need of new biomarkers to improve (i) early detection of PC, (ii) risk stratification, (iii) prognosis, and (iv) treatment monitoring. 2. PC Biomarkers Serum prostate specific antigen (PSA) level and digital rectal examination (DRE) constitute the major screening tests for prostate cancer (PC) diagnosis, while the transrectal ultrasound-guided prostate biopsy provides the final confirmation of cancer presence (Velonas et al., 2013). PSA level has been extensively used as a biomarker to detect PC. Nevertheless, due to prostate physiology, PSA testing results in a large frequency of false positives leading to numerous men each year undergoing unnecessary prostate biopsy procedures (Vickers et al., 2008; Link et al., 2004; McDunn et al., 2013; Roberts et al., 2011; Djavan et al., 2000). Hence, a non-invasive, cost-effective, efficient, and reasonably accurate test for early identification of PC is urgently needed. Compared with serum, urine is easier to obtain and handle, needs less sample preparation, and has higher amounts of metabolites and lower protein content (Rigau et al., 2013; Wilkosz et al., 2011; Zhang et al., 2013). Therefore, in attempt to solve this diagnostic dilemma, many previous studies have focused on urinary metabolomic profile, to identify the predictive biomarkers for PC (Chistiakov et al., 2018). Yang and colleagues conducted a study searching for urine metabolite biomarkers for the detection of PC. They found twenty differentially expressed urine metabolites in a cohort of 50 prostate cancer patients compared to non-cancerous individuals (Yang et al., 2021; Gordetsky et al., 2016; Nam et al., 2018; Di Meo et al., 2017). The combination of solely three metabolites, representing alterations in Glycine, Serine, and Threonine metabolism (KEGG database pathway), was able to identify PC patients with 77% accuracy at 80% sensitivity and 64% specificity. Furthermore, those metabolites could separate significant PC (Gleason score ≥ 7) from indolent PC (GS 6), which confirms urine metabolomics as a promising diagnostic tool in PC. However, to date, no single urine biomarker/biomarker panel meets the requirements for highly sensitive, and specific detection of PC. Therefore, the search for PC-specific biomarkers still is an active area of research. 3. PC prevalence is not equal in different populations There is a racial difference in incidence rate and interpatient heterogeneity of prostate cancer. By contrast, Asian men have lower disease prevalence compared with Asian-American or American PC cohorts. Despite lower PC incidence, the Asian populations have a higher prevalence of advanced disease, probably due to the lack of availability of more sensitive diagnostic tools (Ateeq et al., 2016). Therefore, it’s necessary to define the urine metabolome in an Asian population. 4. Aims of the study − Exploration of novel biomarkers for the detection of PC in an Asian cohort. − Are urinary metabolomics suitable to develop new PC biomarkers? − What are the advantages of urine biomarkers? − How to identify novel biomarkers in the urine and to investigate the possible functions and roles of potential biomarkers in PC?

The term "personality" nowadays occurs more often not only in psychological studies of humans but also in animal studies. Studying of personality help us to define the behavioural characteristics which can vary within the age, sexes, species or enviroments. Behavioral experiments are used to detect these behavioral patterns and they can divide the animals into the different groups. The subject of our research became three populations of house mouse (Mus musculus sensu lato) which we tested in a series of experiments involving free exploration, forced exploration, hole- board test, test of vertical activity and Elevated plus-maze. These experiments should reveal wheter the mice differ in their behaviour through the context of sex, comensalism or subspecies. We found (with in excepcion of one test) that intrapopulation variability differences are very small but interpopulation differences purely increase in the cas of comensalism and effects of subspecies. Keywords: Mus musculus, comensalism, open fieldtest, Elevated plus-maze, Principal Component Analysis (PCA)

L'objectif de cette thèse est le développement d'une méthodologie pour la détection de défauts appliquée aux équipements de production de semi-conducteurs. L'approche proposée repose sur l'Analyse en Composantes Principales (ACP) pour construire un modèle représentatif du fonctionnement nominal d'un équipement. Pour cela, notre méthodologie consiste à exploiter l'ensemble des mesures disponibles, collectées via les capteurs internes et externes au cours desopérations de fabrication pour chaque plaque manufacturée. Nous avons développé un module de pré-traitement permettant de transformer les mesures collectées en données interprétables par l'ACP, tout en filtrant l'information considérée comme non-désirable induite par la présence de valeurs aberrantes et perturbant la construction du modèle. Nous avons combiné des extensions de l'ACP linéaire et notamment l'ACP multiway, l'ACP filtrée ainsi que l'ACP récursive, de façon à adapter la modélisation aux caractéristiques des systèmes. L'utilisation d'un filtre par moyenne mobile exponentielle nous permet de considéré la dynamique du système au cours de la réalisation d'une opération. L'ACP récursive est employée pour adapter le modèle aux changements de comportement du système après certains événements (maintenance, redémarrage, etc.).Les différentes méthodes sont illustrées à l'aide de données réelles, collectées sur un équipement actuellement exploité par STMicroelectronics Rousset. Nous proposons également une application plus générale de la méthode pour différents types d'équipement et sur une période plus importante, de façon à montrer l'intérêt industriel et la performance de cette approche. / This thesis focus on developping a fault detection methodology for semiconductor manufacturing equipment. The proposed approach is based on Principal Components Analysis (PCA) to build a representative model of equipment in adequat operating conditions. Our method exploits collected measurements from equipement sensors, for each processed wafer. However, regarding the industrial context and processes, we have to consider additional problems: collected signals from sensors exhibit different length, or durations. This is a limitation considering PCA. We have also to consider synchronization and alignment problems; semiconductor manufacturing equipment are almost dynamic, with strong temporal correlations between sensor measurements all along processes. To solve the first point, we developped a data preprocessing module to transform raw data from sensors into a convenient dataset for PCA application. The interest is to identify outliers data and products, that can affect PCA modelling. This step is based on expert knowledge, statistical analysis, and Dynamic Time Warping, a well-known algorithm from signal processing. To solve the second point, we propose a combination multiway PCA with the use of an EWMA filter to consider process dynamic. A recursive approach is employed to adapt our PCA model to specific events that can occur on equipment, e.g. maintenance, restart, etc.All the steps of our methodology are illustrated with data from a chemical vapor deposition tool exploited in STMicroelectroics Rousset fab. Finally, the efficiency and industrial interest of the proposed methodologies are verified by considering multiple equipment types on longer operating periods.

A acne é uma doença de pele com alta prevalência e seu tratamento é importante para evitar lesões cutâneas permanentes ou o agravamento de transtornos psicológicos provenientes do abalo à autoestima. Dessa forma, o desenvolvimento de formulações dermocosméticas eficazes que possam melhorar as condições desse tipo de pele é de grande valia. Dentre os ativos com potenciais benefícios para o controle de alguns dos principais fatores causadores da acne, estão a vitamina B3, um derivado de vitamina B6 e o PCA zinco. Assim o objetivo deste estudo foi o desenvolvimento de formulações dermocosméticas para a pele acnéica contendo vitamina B3, derivado lipossolúvel de vitamina B6 e PCA zinco bem como a avaliação da estabilidade e eficácia clínica dessas formulações. Para tal, foram desenvolvidas diferentes formulações, as quais, em um primeiro momento, foram avaliadas quanto à estabilidade frente à adição do ingrediente ativo Zinc PCA. Após esta etapa, os demais ingredientes ativos foram adicionados e as formulações foram submetidas a testes preliminares de estabilidade e ao estudo da estabilidade física por determinação do comportamento reológico. A formulação mais estável foi avaliada quanto à compatibilidade cutânea e também em relação à comedogenicidade do veículo. A formulação composta pelos ingredientes ativos foi avaliada, ainda, quanto as suas características sensoriais e eficácia clínica. Os estudos de eficácia foram realizados por meio de métodos objetivos e subjetivos, após seis semanas do uso da formulação. Os métodos objetivos consistiram no uso de metodologias in vivo, não invasivas (métodos biofísicos e de imagem), sendo avaliados parâmetros relacionados à hidratação, função barreira, conteúdo lipídico, pH cutâneo, contagem de porfirinas, de microcomedões e de lesões inflamatórias. Em relação aos métodos subjetivos, foi realizada a percepção da eficácia por meio de um questionário para a comparação da pele antes e após o tratamento. Os resultados mostraram que, de todas as formulações desenvolvidas, apenas uma mostrou-se estável frente aos testes de estabilidade realizados. A formulação (veículo e adicionada de ingredientes ativos) apresentou compatibilidade cutânea considerada como \"muito boa\", de acordo com o teste realizado, e o veículo sem potencial comedogênico. Na avaliação sensorial as frequências obtidas para os parâmetros considerados como ruins foram baixas, indicando que o sensorial da formulação mostrou-se adequado para as finalidades propostas. No estudo de eficácia clínica, a formulação não alterou a hidratação e a função barreira da pele e mostrou-se eficaz na redução da contagem de porfirinas e das lesões inflamatórias (p<0,05). A avaliação clínica por métodos subjetivos mostrou a eficácia da formulação quanto à melhora da acne inflamatória, oleosidade da pele, hidratação e maciez. Por fim, os resultados obtidos mostraram que a formulação desenvolvida é eficaz e compatível com a pele, bem como a importância da pesquisa e desenvolvimento para a obtenção de formulações estáveis, seguras, eficazes e com sensorial adequado. / Acne is a skin disease with high prevalence and its treatment is important to prevent permanent skin lesions or the aggravation of psychological disorders due to self-esteem shaken. This way, the development of effective dermocosmetic formulations, that can improve the conditions of this skin type, is very important. Vitamin B3, a vitamin B6 derivative and zinc PCA are among the active ingredients which present potential benefits in the controlling of some pathogenic factors of acne. Thus, the aim of this research was to develop cosmetic formulations for acneic skin containing vitamin B3, vitamin B6 lipophilic derivative and zinc PCA, as well as the evaluation of stability and clinical efficacy. For this purpose, were developed different formulations which, at first, were evaluated in terms of stability face to zinc PCA addition. After this, the others active ingredients were added and the formulations were submitted to preliminary tests of stability and physical stability studies by rheological behavior determination. The most stable formulation was subject to skin compatibility evaluation and vehicle comedogenicity. The formulation with the active ingredients was also evaluated regarding their sensorial characteristics and clinical efficacy. Efficacy studies were performed by means of objective and subjective methods, after a sixweek- period of use of the formulation. The objective methods consisted in non-invasive in vivo methodologies (biophysical techniques and image analysis) where were evaluated hydration, barrier function, lipid content, skin pH and the counting of porphyrins, microcomedones and inflammatories lesions. In relation to subjective methods, was performed the efficacy perception using a questionnaire in order to compare the skin before and after the treatment. The results showed that among the formulations developed, only one kept stable after the stability tests. The formulations were considered as \"very good\" on skin compatibility test and showed no comedogenic potential. In sensorial evaluation, frequencies obtained for the parameters considered bad were low, which indicate the sensorial of the formulation was adequate for the purposes. In clinical efficacy study, the formulation under study did not alter the parameters related to hydration and skin barrier function and was effective in reducing the counting of porphyrins and inflammatories lesions (p<0,05). Clinical evaluation by subjective methods showed the formulation effectiveness regarding the improvement of inflammatory acne, skin oiliness, hydration and softness. Finally, the results obtained showed the formulation developed is effective and compatible with the skin and, besides the importance of research and development for obtaining stable, safe and effective formulations with suitable sensorial.

L’objectif de cette thèse était de valider l’ensemble des informations délivrées par les capteurs utiles à la commande d’une station de traitement des eaux usées. Pour cela, nous avons utilisé l’analyse en composantes principales (ACP) pour effectuer la détection et localisation de défauts de capteurs de la station de traitement des eaux usées. Afin de construire un modèle ACP, nous avons eu recours à une matrice de données constituée de l’ensemble des mesures disponibles (obtenues lors du fonctionnement normal de la station de traitement des eaux usées) dans l’installation. Cependant, afin d’appliquer l’ACP, nous avons rencontré plusieurs difficultés : 1. Présence dans les données de valeurs aberrantes (valeurs obtenues durant des périodes de démarrage, d’arrêt, de fonctionnement dégradé, erreurs de mesure, ...) perturbant la construction d’un modèle ACP. 2. Présence de défauts multiples, ce qui entraîne une explosion combinatoire des scénarii de défauts à considérer. Afin de résoudre le premier point, nous nous sommes intéressé aux variantes robustes de l’ACP. L’estimateur robuste MCD (Minimum Covariance Determinant), méthode de référence pour ses performances, nécessite un temps de calcul important, et une connaissance a priori de la quantité de valeurs aberrantes présente dans les données (inconnue). C’est la raison pour laquelle nous avons proposé une nouvelle méthode robuste, basée sur l’utilisation de MM-estimateur, nommée MMRPCA (MM-estimator Robust Principal Component Analysis). Concernant le point 2, une méthode d’analyse du modèle en terme de capacité de détection et de localisation a été appliquée afin de réduire le nombre de défauts à considérer. Les différentes méthodes développées ont été menées avec succès afin de valider les mesures issues des différents capteurs de la station d’épuration des eaux usées / This thesis deals with the validation of the information provided by the sensors to the control of a wastewater treatment plant. For this purpose, Principal Component Analysis (PCA) approach is used in order to accomplish sensor fault detection and isolation of the wastewater treatment plant. This approach is well adapted to cope with diagnosis of complex systems because no a priori theoretical model of the plant must be considered. A data matrix, obtained by taking into consideration the available measurements in normal behaviour of the wastewater treatment plant, is used in order to build a PCA model. However, two major problems must be taking into consideration when PCA is implemented: 1. Outliers appear naturally in the collection data (caused for example by faulty data, data obtained during shutdown or startup periods or data issued from different operating mode) and consequently the PCA model can seriously be affected. 2. Multiple sensor faults introduce unavoidably a combinatory explosion of the different fault scenarios to be considered. The first problem is solved by introducing a robustness degree in the PCA methodology. Among the existing robust methods proposed in the literature, the robust estimator MCD (Minimum Covariance Determinant) is the most popular. However, this method needs a large computing time on the one hand and a priori knowledge of the quantity of outliers present (generally unknown) in the data on the other hand. To avoid these difficulties, a new robust method is proposed in this thesis. Our method, namely MMRPCA (MM-estimator Robust Principal Component Analysis), is based on MM-estimators. The second mentioned problem is tackled by reducing the considered number of faults thanks to a new analysis method of the capacities of detection and isolation of the PCA model. The efficiency of the proposed methodologies is verified by considering the real wastewater treatment plant data

Made available in DSpace on 2014-12-17T15:42:13Z (GMT). No. of bitstreams: 1 LeomirASL_DISSERT.pdf: 2074968 bytes, checksum: 7f7bd033e89dd46efc6c92957584d5b9 (MD5) Previous issue date: 2013-07-23 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior / This paper investigates the potential of near infrared spectroscopy (NIR) for forensic analysis of human hair samples in order to differentiate smokers from nonsmokers, using chemometric modeling as an analytical tool. We obtained a total of 19 hair samples, 9 smokers and 10 nonsmokers varying gender, hair color, age and duration of smoking, all collected directly from the head of the same great Natal-RN. From the NIR spectra obtained without any pretreatment of the samples was performed an exploratory multivariate chemical data by applying spectral pretreatments followed by principal component analysis (PCA). After chemometric modeling of the data was achieved without any experimental data beyond the NIR spectra, differentiate smokers from nonsmokers, by demonstrating the significant influence of tabacco on the chemical composition of hair as well as the potential of the methodology in forensic identification / Nesse trabalho investiga-se a potencialidade da espectroscopia no infravermelho pr?ximo (NIR) para an?lise forense de cabelo humano, a fim de diferenciar amostras fumantes de n?o fumantes, utilizando-se a modelagem quimiom?trica como ferramenta anal?tica. Foram obtidos um total de 19 amostras de cabelo, sendo 9 de indiv?duos fumantes e 10 de n?o fumantes variando sexo, cor do cabelo, idade e tempo de consumo de tabaco, todos coletados diretamente da cabe?a dos mesmos na grande Natal-RN. A partir dos espectros NIR, obtidos sem nenhum tratamento pr?vio das amostras, foi realizado um estudo explorat?rio dos dados qu?micos multivariados aplicando-se pr?-tratamentos espectrais seguido da an?lise dos componentes principais (PCA). Ap?s modelagem quimiom?trica dos dados, conseguiu-se, sem qualquer outro dado experimental al?m dos espectros NIR, diferenciarem indiv?duos fumantes de n?o fumantes, demonstrando-se a influ?ncia significativa do tabaco na composi??o qu?mica do cabelo, bem como a potencialidade da metodologia na identifica??o forense

Diese Arbeit umfasst die Archivierung, Visualisierung anhand bioinformatischer Methoden und Interpretation eines vorhandenen Messdatensatz (Element [ICP-MS]-, Ionen [IC]- und Metabolitdaten [RP-HPLC und GC/TOF-MS]) der Pflanze Arabidopsis thaliana getrennt in Blätter und Wurzeln. Die Pflanzen wurden den sechs Mangelsituationen der Nährstoffe Eisen, Kalium, Magnesium, Stickstoff, Phosphor und Schwefel ausgesetzt und zu neun Messzeitpunkten [0.5-, 1-, 2-, 3-, 4-, 5-, 6-, 7-in Tagen und „resupply“ (vier Stunden nach dem vierten Tag)] analysiert. Es erfolgte die Integration der Messdaten in eine SQlite-Datenbank. Die Veranschaulichung erfolgte mit Hilfe der Programmiersprache R. Anhand einiger Pakete zur Erweiterung des Funktionsumfangs von R wurde erstens eine Schnittstelle zur SQLite- Datenbank hergestellt, was ein Abfragen an diese ermöglichte und zweitens verhalfen sie zu der Erstellung einer Reihe zusätzlicher Darstellungsformen (Heatmap, Wireframe, PCA). Selbstgeschriebene Skripte erlaubten den Datenzugriff und die grafische Ausgabe als z. B. Heatmaps. In der Entstehung dieser Arbeit sind weiterhin zwei weitere Visualisierungsformen von PCA-Daten entwickelt worden: Das Abstandsdiagramm und die animierte PCA. Beides sind hilfreiche Werkzeuge zur Interpretation von PCA-Plots eines zeitlichen Verlaufes. Anhand der Darstellungen der Element- und Ionendaten ließen sich die Nährstoffmangelsituationen durch Abnahme der entsprechenden Totalelemente und Ionen nachweisen. Weiterhin sind starke Ähnlichkeiten der durch RP-HPLC bestimmten Metaboliten unter Eisen-, Kalium und Magnesiummangel erkannt worden. Allerdings gibt es nur eine geringe Anzahl an Interkationen der Metabolitgehalte, da der Großteil der Metabolitlevel im Vergleich zur Kontrolle unverändert blieb. Der Literaturvergleich mit zwei Publikationen, die den Phosphat- und Schwefelmangel in Arabidopsis thaliana untersuchten, zeigte ein durchwachsenes Ergebnis. Einerseits gab es eine gleiche Tendenz der verglichenen Aminosäuren zu verzeichen, aber andererseits wiesen die Visualisierungen auch Gegensätzlichkeiten auf. Der Vergleich der mit RP-HPLC und GC/TOF-MS gemessenen Metaboliten erbrachte ein sehr kontroverses Ergebnis. Zum einen wurden Übereinstimmungen der gleichen Metaboliten durch gemeinsame Cluster in den Heatmaps beobachtet, zum anderen auch Widersprüche, exemplarisch in den Abstandsdiagrammen der Blätterdaten jedes Verfahrens, in welchen unterschiedliche Abstandshöhepunkte erkennbar sind. / This manuscript deals with archiving, visualization with bioinformatic methods and the interpretation of an existing measuring dataset (element [ICP-MS]-, ions [IC]- and metabolit data [RP-HPLC and GC/TOF-MS]) of the plant Arabidopsis thaliana – for either its leaves and roots. These plants have been subjected to six situations of deficiency according to the nutrients iron, potassium, magnesium, nitrate, phosphor, and sulfur. They have been analyzed for nine time-points of measurement [0.5-, 1-, 2-, 3-, 4-, 5-, 6-, 7- in days and “resupply” (four hours after the fourth day). While the measuring data has been integrated in a SQLite-database, its illustration has been carried out with the help of the programming language R. In order to extend the functional range of R, first, an interface to the SQLite-database has been established, which offered the query to this and, secondly, it helped to create a row of additional display formats (heatmaps, wireframe, PCA). Self-written scripts allowed the access to the data and the graphical output, for example as heatmaps. Additionally two more visualization formats for the PCA-data have been designed in the development of this manuscript: the distance-diagram and the animated PCA. Both are useful tools to interpret PCA-plots during a specific course of time. Based on the illustration of element and ion data the situations of deficiency for several nutrients could be detected by the decrease of the corresponding total-elements and ions. Furthermore, obvious similarities between the metabolits, which were measured through RP-HPLC, have been examined under iron-, potassium- and magnesium-deficit. There are certainly only a low number of interactions regarding to the content of metabolits because most of the metabolit level did not change in comparison to the control. The comparative study of specialist literature – in this case of two particular publications –, which analyzed the deficit of phosphate and sulfate in Arabidopsis thaliana, presented an intermingled result. On the one hand a similar tendency of the compared amino acid could be observed, but on the other hand the visualizations showed opposites, too. The comparison of the metabolits measured by RP-HPLC and GC/TOF-MS effected a very controversial result. Although there are analogies between the same metabolits through common clusters in the heatmaps, contradictory elements can also be found – for example in the distance-diagram of the data of the leaves for each procedure in which different distance-peaks are recognizable.

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No. of bitstreams: 2 Dissertação - Flávia Carneiro Gonçalves - 2015.pdf: 3718226 bytes, checksum: 3024f921d7aec7030599eee358d0593f (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) Previous issue date: 2015-07-30 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / This study objectives to evaluate the effect of an inappropriate night cooling condition, it is practiced by some shops with processed mozzarella cheese and conventional mozzarella chemical profiles, using nuclear magnetic resonance technique (NMR). The simulation of inappropriate cooling was performed using a Styrofoam box with ice, not covered, and leaving the system to reach thermal equilibrium with the ambient temperature during the night. To make studies with processed mozzarella cheese was acquired two packages of the same batch, at local shops. Subjecting the spectral data, coming from the analysis made with HR-MAS, in the chemometric treatment was observed a tendency of discrimination in the samples exposed to different cooling conditions, and signals concerning lactose and some of fatty acids had greater influence in the observed separation. For the mozzarella cheese, in addition to NMR studies, it was also performed physical and chemical characteristics studies. For these studies, it has been acquired twenty-two trays containing sliced cheese, in the local market, which were divided into two sets with eleven trays each. Samples were analyzed in nature, using HR-MAS probe, and the crude extract using TBI probe. The identification of metabolites was done from the HSQC experiments, J-resolved and NMR ¹H, the last one being also used in the relative quantification of twelve metabolites. For the mozzarella cheese maintained under improper cooling conditions, there was a reduction in the galactose content and an increasing of amino acids and organic acids contents. The physicochemical analysis of pH, saturated fat and protein showed no significant differences that could be correlated with the different conditions of sample cooling. Finally, it has been concluded that NMR technique and chemometric tools are promising in identify the cheese samples submitted to different cooling conditions that has been studied, which could not be done using the physical and chemical parameters commonly used in cheese quality analysis. / Neste estudo vislumbrou-se avaliar a o efeito da condição de refrigeração noturna inadequada, praticada por alguns estabelecimentos comerciais, no perfil químico dos queijos tipo processados sabor mozarela e tipo mozarela convencional, fazendo uso da técnica de Ressonância Magnética Nuclear (RMN). A simulação da refrigeração inadequada foi realizada utilizando-se uma caixa de isopor contendo gelo, sem tampa, deixando o sistema atingir o equilíbrio térmico com o ambiente no decorrer da noite. Para os estudos com o queijo tipo mozarela processado adquiriu-se dois pacotes, pertencentes a um mesmo lote, no comércio local. Submetendo-se os dados espectrais, advindos das análises fazendo uso da sonda HR-MAS, ao tratamento quimiométrico, observa-se uma tendência de discriminação das amostras submetidas a diferentes condições de refrigeração, sendo que os sinais referentes a lactose e de alguns ácidos graxos tiveram maior influencia na separação observada. Já para o queijo tipo mozarela convencional, além dos estudos de RMN, realizou-se também estudos de características físico-químicas. Para isso, foram adquiridas no comércio local vinte e duas bandejas contendo queijo fatiado, as quais foram divididas em dois conjuntos com onze bandejas cada. Foram realizadas análises da amostra in natura, fazendo uso da sonda HR-MAS, e do extrato bruto, fazendo uso da sonda TBI. A identificação de metabólitos foi feita a partir dos experimentos HSQC, J-resolved e RMN de ¹H, sendo este último utilizado também na quantificação relativa de doze metabólitos. Para o queijo tipo mozarela mantido sob condições inadequadas de refrigeração observou-se uma redução no teor de galactose e aumento no teor de aminoácidos e ácidos orgânicos. As análises físicoquímicas de pH, gordura total e proteína total não mostraram diferenças significativas que pudessem ser correlacionadas com as diferentes condições de refrigeração das amostras. Nesse sentido, conclui-se que a técnica de RMN e ferramentas quimiométricas mostraram-se promissoras na identificação das amostras de queijo submetidas às diferentes condições de refrigeração estudadas, o que não pôde ser feito utilizando-se os parâmetros físico-químicos rotineiramente empregados em análises da qualidade de queijos.