Fourier Transform Infrared (FTIR) has been use to discriminate different pathogens by signals from cells infected with these versus normal cells as references. To do the statistical analysis, Partial Least Square Regression (PLSR) was utilized to distinguish any two kinds of virus‐infected cells and normal cells. Validation using Bootstrap method and Cross‐validations were employed to calculate the shrinkages of Area Under the ROC Curve (AUC) and specificities corresponding to 80%, 90%, and 95% sensitivities. The result shows that our procedure can significantly discriminate these pathogens when we compare infected cells with the normal cells. On the height of this success, PLSR was applied again to simultaneously compare two kinds of virus‐infected cells and the normal cells. The shrinkage of Volume Under the Surface (VUS) was calculated to do the evaluation of model diagnostic performance. The high value of VUS demonstrates that our method can effectively differentiate virus‐infected cells and normal cells.

京都大学 / 0048 / 新制・課程博士 / 博士(農学) / 甲第22489号 / 農博第2393号 / 新制||農||1076(附属図書館) / 学位論文||R2||N5269(農学部図書室) / 京都大学大学院農学研究科地域環境科学専攻 / (主査)教授 近藤 直, 准教授 小川 雄一, 教授 飯田 訓久 / 学位規則第4条第1項該当 / Doctor of Agricultural Science / Kyoto University / DGAM

A big challenge in managing large scale industry processes, like the ones in the paper and pulp industry, is to reduce the amount of downtime and reduce sources of product quality variability to a minimum, while staying cost effective. To accomplish this the key is to understand the complex nature of the processes variables, and to quantify the causal relationships between them and the product quality together with the amount of output. Paper and pulp industry processes consist mainly of chemical processes and the relatively low cost of sensors today enables collection of huge amounts of data, both variables and observations on frequent time intervals. These masses of data usually come with the intrinsic problem of multicollinearity which requires efficient multivari- ate statistical tools for the extraction of useful insights among the noise. One goal in this multivariate situation is to breakthrough the noise and find a relatively small subset of variables that are important, that is, variable selection. The purpose with this master thesis is to help SCA Obbola, a large paper manu- facturer that have had a variable production output, to come up with conclusions that can help them ensure a long term high production quantity and quality. We apply different variable selection approaches that have proven successful in the literature. The results that we get are of mixed success, but we manage to find both variables that SCA Obbola knows affect specific response variables, but also variables that they find interesting for further investigation. / En stor utmaning när det gäller att hantera storskaliga industriprocesser, som i pappers- och massaindustrin, är att minska tiden för driftstopp och reducera källor till varia- tioner i produktkvalitén till ett minimum, och samtidigt vara kostnadseffektiv. För att uppnå detta är det viktigt att förstå processvariablernas komplexa natur och att kvantifiera orsakssambanden mellan dem och produktkvaliteten tillsammans med pro- duktionsmängden. Pappers- och massasindustrin består huvudsakligen av kemiska pro- cesser och den relativt låga kostnaden för sensorer idag möjliggör insamling av stora mängder data, både variabler och observationer inom frekventa tidsintervall. Med des- sa datamängder får man ofta problem med multikollinearitet, vilket kräver effektiva multivariata statistiska verktyg för att extrahera användbara insikter bland bruset. Ett mål i denna multivariata situation är att bryta igenom bruset och hitta en relativt liten delmängd variabler som är viktiga, det vill säga variabel selektion. Syftet med denna masteruppsats är att hjälpa SCA Obbola, en stor pappersprodu- cent som har haft ett varierat produktionsutfall, att komma fram till slutsatser som kan hjälpa dem att säkerställa en långsiktig hög produktionskvantitet och kvalitet. Vi tillämpar olika metoder för variabel selektion, som har visat sig framgångsrika i lit- teraturen. Resultaten av arbetet är av blandad framgång, men vi lyckas hitta både variabler som SCA Obbola vet påverkar specifika responser, men även variabler som de tycker är intressanta för vidare utredning.

Submitted by JOÃO PAIXÃO DOS SANTOS NETO (joaopaixaoneto@gmail.com) on 2018-11-12T17:32:27Z No. of bitstreams: 1 Tese Definita João.pdf: 2906923 bytes, checksum: 845ed5e6f32d28d2764507fa3867c277 (MD5) / Rejected by Neli Silvia Pereira null (nelisps@fcav.unesp.br), reason: Solicitamos que realize correções na submissão seguindo as orientações abaixo: 1- O agradecimento à CAPES deve ter a seguinte redação: O presente trabalho foi realizado com apoio da Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Código de Financiamento 001 2- Falta o abstract (resumo em inglês) no repositório. Agradecemos a compreensão. on 2018-11-13T13:21:55Z (GMT) / Submitted by João Paixão dos Santos Neto (joaopaixaoneto@gmail.com) on 2018-11-13T13:45:38Z No. of bitstreams: 1 Tese Definita João.pdf: 2907242 bytes, checksum: c61b7c2515e87708154877088732effc (MD5) / Approved for entry into archive by Neli Silvia Pereira null (nelisps@fcav.unesp.br) on 2018-11-14T16:00:50Z (GMT) No. of bitstreams: 2 Tese Definita João.pdf: 2907242 bytes, checksum: c61b7c2515e87708154877088732effc (MD5) santosneto_jp_dr_jabo.pdf: 2907242 bytes, checksum: c61b7c2515e87708154877088732effc (MD5) / Made available in DSpace on 2018-11-14T16:00:50Z (GMT). No. of bitstreams: 2 Tese Definita João.pdf: 2907242 bytes, checksum: c61b7c2515e87708154877088732effc (MD5) santosneto_jp_dr_jabo.pdf: 2907242 bytes, checksum: c61b7c2515e87708154877088732effc (MD5) Previous issue date: 2018-10-10 / Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) / O objetivo geral deste trabalho foi conservar a qualidade de mangas ‘Palmer’ exportadas para a Europa e por objetivos específicos: I. estabelecer o melhor estádio de maturação para o transporte marítimo refrigerado e sob condições de atmosfera controlada (CA) determinado usando técnicas não-destrutivas de espectroscopia de infravermelho próximo (NIRS); II. desenvolver modelos de calibração e predição de matéria-seca (MS) e sólidos solúveis (SSC); III. comparar se a abordagem proposta difere do manuseio tradicional de mangas em uma remessa de mangas por frete marítimo para a Europa. No trabalho sobre a determinação dos índices de maturidade de manga ‘Palmer’ utilizando espectrômetro portátil de infravermelho próximo (VIS-NIR) o melhor modelo de calibração para SSC foi obtido usando espectros pré-processados com variação normal padrão (SNV), primeira derivada de Savitizk-Golay e janela de 699-999 nm. Para os SSC, foi observado um RMSECV de 1,39 % com um R2CV de 0,87 e RPD de 2,77. Melhores resultados foram observados para o modelo de calibração de MS construído com espectros em bruto usando a janela de 699-981 nm (RMSECV de 8,81 g.kg-1, R2CV de 0,84 e RPD de 2,51) e os modelos de calibração para firmeza foram considerados ruins. No estudo sobre armazenamento refrigerado de mangas ‘Palmer’ classificadas com base no teor de MS usando espectrômetro portátil de infravermelho próximo (VIS-NIR) foi possível concluir que o modelo PLS desenvolvido com as mangas da safra 2015/2016 não foi adequado para predizer o teor de MS em frutos da safra 2016/2017 (R² não ajustado). Assim, os espectros VIS-NIR da safra 2016/2017 foram incorporados ao conjunto de dados e um novo modelo foi desenvolvido (RMSEcv de 10,5 g.kg-1, R²P de 0,75). Com o novo modelo, as mangas ‘Palmer’ foram classificadas em dois estádios de maturação (150 g.kg-1 e 110 g.kg-1), o que resultou em diferenças de qualidade principalmente em relação à MS e SSC. No experimento sobre a resposta pós-colheita de mangas selecionadas de forma não-destrutiva quanto ao teor de MS durante e após o armazenamento sob atmosfera controlada (AC) foi observado que o modelo de regressão de mínimos quadrados parciais (PLSR) desenvolvido com frutos das safras de 2015/2016 e 2016/2017 de Cândido Rodrigues - SP, foi capaz de prever adequadamente o teor de MS de mangas produzidas em Petrolina - PE, mas com erro médio quadrático de predição bastante alto (RMSEP = 20,2 g.kg-1) e baixo R2P (0,19). Os espectros Vis-NIR de mangas produzidas em Petrolina - PE foram incorporados ao conjunto de dados e um novo modelo foi desenvolvido (RMSEv = 13,8 g.kg-1 e R²V = 0,63). Com o novo modelo PLSR foi possível selecionar mangas produzidas em Petrolina - PE com 150 g.kg-1 de MS, confirmando a robustez do modelo. Não foram observadas diferenças significativas na qualidade entre os frutos classificados com base na MS (150 g.kg-1) em relação às selecionadas usando a aparência visual (manuseio tradicional) durante o armazenamento sob AC (5 kPa O2 e 5 kPa CO2) por 30 dias a 14,2±2,3 °C e 92,6±2,8 % UR. No entanto, as mangas classificadas com 150 g.kg-1 de MS apresentaram menor desvio padrão, indicando um lote de frutos mais homogêneo. De modo geral, foi possível conservar a qualidade de mangas ‘Palmer’ a serem exportadas para a Europa, principalmente por selecionar frutos no estádio de maturação mais apropriado (150 g.kg-1 MS), resultando em lotes de frutos mais homogêneos. / The main objective of this study was to preserve the quality of ‘Palmer’ mangoes exported for the supply chain in Europe, and the specific objectives were: I. establish the best maturity stage for sea freight transportation and under controlled atmosphere (CA) conditions, determined using non-destructive of techniques near infrared spectroscopy; II. develop calibration and prediction models for dry matter (DM) and soluble solids content (SSC), III. compare if the proposed approach differs from the traditional mango handling to sea freight to Europe. In the study about the determination of the ‘Palmer’ mangoes maturity stages using near portable infrared spectrometer (VIS-NIR), the best calibration model for SSC was obtained using NIR spectra pre-processed with standard normal variation (SNV), first derivative of Savitizk-Golay, and 699-999 nm window. For SSC, it was observed a RMSECV of 1.39 %, with a R2CV of 0.87, and a RPD of 2.77. Better results could be seen for the DM calibration model built with raw spectra using the 699-981 nm window (RMSECV of 8.81 g.kg-1, R2CV of 0.84 and RPD of 2.51), and poor calibration models were obtained for firmness. In the study about refrigerated storage of ‘Palmer’ mangos sorted based on their DM content using near portable infrared spectrometer (VIS-NIR), it could be seen that the PLS model developed during 2015/2016 mango season was not appropriate to predict the DM content of fruit from 2016/2017 season (R² not adjusted). Therefore, the VIS-NIR spectra from 2016/2017 season were incorporated into the dataset and a new model was developed (RMSEcv of 10.5 g.kg-1, R²P of 0.75). With the new model, ‘Palmer’ mangoes were sorted in two maturity stages (150 g.kg-1 and 110 g.kg-1), which resulted in quality differences, mainly in relation to DM and SSC. In the study about the postharvest responses of mangos non-destructively sorted based on DM content during and after the storage under controlled atmosphere (CA), it was observed that the partial least squares regression (PLSR) model developed with fruit from 2015/2016 and 2016/2017 from Candido Rodrigues - SP, was able to properly predict the DM content of mangoes produced in Petrolina - PE, but with a high root mean square error of prediction (RMSEP = 20.2 g kg-1) and low R2P (0.19). Therefore the VIS-NIR spectra from mangoes produced in Petrolina – PE were incorporated into the dataset and a new model was developed (RMSEv of 13.8 g kg-1 and R²V of 0.63). With the new PLSR model, it was possible to sort mangoes produced in Petrolina – PE with 150 g.kg-1 DM, confirming the robustness of the model. It was not observed significant quality differences between fruit sorted based on DM (150 g.kg-1) in relation to visual appearance sorted fruit (traditional handling) during CA storage (5 kPa O2 and 5 kPa CO2) for up to 30 days at 14.2±2.3 °C and 92.6±2.8 % RH. However, the mangoes sorted with 150 g.kg-1 DM showed lower standard deviation, indicating a more homogeneous fruit batch. All in all, it was possible to preserve the quality of ‘Palmer’ mango to be exported to Europe, mainly by sorting the fruit in the appropriate maturity stage (150 g.kg-1 DM) with a more homogeneous fruit batch. / 2015/25631-9

No description available.

Les spectres contiennent de l'information sur la composition d'échantillons. Cette information est extraite au moyen d'une première famille d'outils chimiométriques, les étalonnages. Une deu xième famille d'outils, les prétraitements, est destinée à enlever une information spectrale nuisible. Etalonnages et prétraitements sont construits à partir de deux types d'informations: (1) les informations expérimentales basées sur l'expérience; (2) les informations expertes basées sur la connaissance a priori. L'objectif de la thèse est d'étudier les complémentarités et synergies entre ces deux types d'informations. Après une étude bibliographique, un modèle général commun aux étalonnages et prétraitements est proposé. L'information utile ou nuisible contenue dans un spectre est obtenue par projection orthogonale de ce spectre (selon un métrique Sigma) sur une matrice P dont les colonnes constituent une base de l'espace vectoriel associé à l'information utile ou nuisible. Selon les cas, l'information utile est conservée alors que l'information nuisible est éliminée. Le modèle général est ensuite implémenté par deux nouvelles méthodes. L'IDC-Improved Direct Calibration est une méthode d'étalonnage direct utilisant conjointement des informations expérimentales et expertes. Ensuite VODKA-PLSR est une généralisation de la PLSR. Un vecteur r est mis en évidence, il permet d'inclure de l'information experte dans le modèle. En conclusion ce travail permet une vision plus synthétique des modèles existants, propose deux nouveaux modèles d'étalonnage et ouvre de nombreuses possibilités pour créer de nouveaux modèles d'étalonnage et de prétraitement. / Spectra contain informations about the composition of samples. This information is obtained using calibration. Harmful spectral information can be previoulsy withdrawn using pretraitments. Both calibration and pretraitment models are based on two types of informations: (1) experimental information based on measurements onto samples; (2) expert information based on a previous knowledge. The aim of this thesis is to study the links between those two types of information. After a biography review, a general model including both calibrations and pretraitments is proposed. The usefull or harmful spectral information is obtained after spectra have been orthogonaly projected (with a Sigma metrix ) onto a P matrix whose columns define a basis of the vectorial subspace described by the usefull or harmful information. Thus usefull information is kept whereas harmful information is withdrawn. Two new methods are proposed. First IDC-Improved Direct Calibra tion is a direct calibration method using both experimental and expert informations. Then VODKA-PLSR is a generalisation of PLSR. A vector r permits the use of expert information by the regression model. To conclude, this works allows a global view of existing tools, proposes two new models and offers new possibilities for building new models.

In der vorliegenden Arbeit werden die Möglichkeiten einer Nutzung thermal-infraroter Wellenlängen zur fernerkundlichen Erfassung/Quantifizierung von Bodenparametern vorgestellt. Die Studie basiert auf Bodenproben des Untersuchungsgebietes Mullewa, welches sich in einer semiariden Agrarregion im West-Australischen Weizengürtel befindet. Im Mittelpunkt der Arbeit steht die Bewertung des langwelligen Infrarots (LWIR), innerhalb des atmosphärischen Fensters zwischen 8 und 14 Mikrometer, bezüglich seines spektralen Potentials für die quantitative Ableitung des Ton- und Sandgehaltes sowie des Gehaltes an organischem Kohlenstoff (SOC). Zur Abschätzung der Effizienz wurden die Ergebnisse des LWIR einer Quantifizierung aus dem herkömmlich gebrauchten solar-reflektiven Wellenlängenbereichs zwischen 0,4 und 2,5 Mikrometer (VNIR-SWIR) gegenübergestellt. Mit verschiedenen Methoden der Laborspektroskopie wurden Bodenproben aus dem Untersuchungsgebiet im thermalen (Emissions-FTIR-Spektroskopie und direktional-hemisphärische Reflexions- (DHR) Spektroskopie)und im solar-reflektiven (Diffuse Reflexions-Spektroskopie) Wellenlängenbereich eingemessen und anschließend auf ihren Informationsgehalt hin untersucht. Die quantitative Modellierung der pedologischen Parameter aus den gemessenen spektralen Signaturen wurde mithilfe einer multivariaten Regressionsanalyse (Partial Least Squares Regression – PLSR) realisiert. Diese Grundlagenstudie konnte zeigen, dass die spektralen Voraussetzungen im LWIR für ein mögliches Monitoring der Bodenparameter mit thermalen Fernerkundungsdaten gegeben sind. Die Arbeit demonstriert darüber hinaus, dass für die Erfassung/Quantifizierung der Textur-Parameter (Sand- und Tongehalt) der relevante spektrale Informationsgehalt im LWIR deutlich höher ist als im VNIR-SWIR. / This study embraces the feasibility of using the thermal infrared wavelength region for future remote sensing applications to detect/quantify soil parameters. The research is based on soil samples from the semiarid agricultural area of Mullewa, located within the wheat belt of Western Australia. The main focus of this study is to assess the potential of the longwave infrared (LWIR), within the atmospheric window between 8 and 14 micrometer, to predict the content of sand, clay and organic carbon (SOC) in soils. The results are compared with predictions made with the traditionally used solar-reflective wavelength region (visible, VIS: 0.4 - 0.7 micrometer; near infrared, NIR: 0.7 - 1.1 micrometer; shortwave infrared, SWIR: 1.1 - 2.5 micrometer). Using laboratory spectroscopy, the Mullewa soil samples were measured, both in the thermal infrared (emission FTIR spectroscopy and directional hemispherical reflection (DHR) spectroscopy) and in the solar-reflective (diffuse reflection spectroscopy) wavelength region. This data was analyzed to determine the relevant content of information for the soil parameters. Multivariate regression analyses (partial least squares regression - PLSR) were used to quantitatively model the soil parameters from the spectral signatures. This basic research demonstrated that the spectral requirements in the LWIR are met for monitoring these soil parameters with thermal remote sensing instruments. Furthermore the study found that the relevant spectral information for the detection/quantification of the sand- and the clay content (textural parameters) is explicitly higher in the LWIR than in the VNIR-SWIR.

Made available in DSpace on 2017-07-24T19:38:02Z (GMT). No. of bitstreams: 1 Giselle Nathaly Calaca.pdf: 1144795 bytes, checksum: 67dd1a377ef4bf40b69d80c46ee27a58 (MD5) Previous issue date: 2010-02-26 / Fundação Araucária de Apoio ao Desenvolvimento Científico e Tecnológico do Paraná / Kojic Acid (KA) and Hydroquinone (HQ) are depigmenting agents used as skinwhitening cosmetics to treat dyschromias. The need for low cost analytical methodologies that enable quality control of this association is evident. Due to the characteristics such as high sensitivity, low cost and operational simplicity, this work aims to use spectrophotometry in the visible region and multivariate calibration tools, mainly Partial Least Squares Regression (PLSR) for quantitative etermination of KA and HQ. The method is based on the complexation of kojic acid with Fe3+ ion (λ = 494nm), while hydroquinone reduces Fe3+ ions to Fe2+, which complex with 1,10-phenanthroline (λ = 510nm). The quantitative determination of KA and HQ by conventional methods was performed by analytical curve, spectrophotometric additivity principle and first-derivative pectrophotometry, and the average errors were: 20,65% (HQ) and 469,91% (AK), 41,44% (HQ) and 47,11% (AK), 57,59% (HQ) and 156,72% (AK), respectively. The results of conventional methods were compared to PLSR, and the multivariate models with better predictive capacity used: spectral range from 350 to 800 nm, mean center data, 03 and 02 latent variables for kojic acid and hydroquinone, respectively. The mean relative errors obtained from these models were: 4,20% for AK and 6,05% for HQ, indicating that PLSR method showed better results for the quantification of analytes, when compared to conventional methods. The multivariate methodology developed was validated according to ANVISA criteria and then used for quantification of analytes in real samples, obtained from manipulation pharmacies of the region. / O Ácido Kójico (AK) e a Hidroquinona (HQ) são agentes despigmentantes freqüentemente comercializados em associações dermocosméticas de manipulação magistral, utilizadas no tratamento de discromias. A necessidade de metodologias analíticas de baixo custo que viabilizem o controle de qualidade dessa associação é evidente. Em função de características como alta sensibilidade, baixo custo e simplicidade operacional, o presente trabalho tem por objetivo a utilização da espectrofotometria na região do visível associada a métodos de calibração multivariada, principalmente Regressão de Mínimos Quadrados Parciais (PLSR) para determinação de AK e HQ. A metodologia proposta consiste na complexação de ácido kójico com o íon Fe3+ (λ = 494 nm), enquanto a hidroquinona reduz os íons Fe3+ a Fe2+, que por sua vez complexam com 1,10-fenantrolina (λ = 510 nm). A determinação quantitativa de AK e HQ pelos métodos convencionais de análise foi realizada via curva analítica, princípio da aditividade espectrofotométrica e primeira derivada, cujos erros relativos médios foram: 20,65% (HQ) e 469,91% (AK), 41,44% (HQ) e 47,11% (AK), 57,59% (HQ) e 156,72% (AK), respectivamente. Os resultados dos métodos convencionais foram comparados ao PLSR, sendo que os modelos de melhor capacidade preditiva empregaram: faixa espectral de 350 a 800 nm, dados centrados na média, 03 e 02 variáveis latentes para ácido kójico e hidroquinona, respectivamente. Os erros relativos médios obtidos a partir desses modelos foram: 4,20% para AK e 6,05% para HQ, evidenciando que o método PLSR apresentou melhores resultados para a quantificação dos analitos, quando comparado aos métodos convencionais. A metodologia multivariada desenvolvida foi validada segundo critérios da ANVISA e posteriormente utilizada para previsão dos analitos em amostras reais obtidas em farmácias de manipulação da região.

Ce travail tend à l'amélioration de la détection et de la quantification des minéraux argileux, et plus particulièrement des minéraux argileux " gonflants ", dans la partie superficielle des sols. Cette étude est menée à l'échelle locale et à l'échelle globale pour accompagner la démarche des régions pour la prévention du risque de retrait-gonflement des argiles. La première partie présente les principes généraux de la spectrométrie infrarouge et la base de données utilisés dans la thèse. Nous confrontons ensuite deux approches classiquement utilisées dans les sciences du sol : Les méthodes statistiques (PLSR et ACP) et l'étude des figures d'absorption caractéristiques des minéraux argileux. Elles montrent principalement la quantification de la kaolinite dans un mélange multiphasé et dans un sol. Les limites de ces méthodes pour la quantification de la smectite amènent au développement d'une nouvelle méthode basée sur la transformée en ondelettes continue et la corrélation croisée en ondelette. Cette méthode apparaît être la plus prometteuse pour la quantification fine de la teneur en smectite des sols, à l'échelle locale comme à l'échelle globale, dans les études de prévention des risques de retrait et de gonflement des sols.

<p>This thesis is a part of a project where a new method, the base descriptor approach, is studied. The purpose of this method is to reduce drift and extract vital information from electronic tongue measurements. Reference solutions, called descriptors, are measured and the measurements are used to find base descriptors. A base descriptor is, in this thesis, a regression vector for prediction of the property that the descriptor represent. The property is in this case the concentration of a chemical substance in the descriptor solution. Measurements from test samples, in this case fruit juices, are projected onto the base descriptors to extract vital and drift-stable information from the test samples. </p><p>The base descriptors are used to determine the concentrations of the descriptors'chemical substances in the juices and thereby also to classify the different juices. It is assumed that the measurements of samples of juices and descriptors drift the same way. This assumption has to be true in order for the base descriptor approach to work. The base descriptors are calculated by multivariate regression methods like partial least squares regression (PLSR) and principal component regression (PCR). </p><p>Only two of the descriptors tested in this thesis worked as basis for base descriptors. The base descriptors'predictions of the concentrations of chemical substances in the juices are hard to evaluate since the true concentrations are unknown. Comparing the projections of juice measurements onto the base descriptors with a classification model on the juice measurements performed by principal component analysis (PCA), there is no significant difference in drift of the juice measurements in the results of the two methods. The base descriptors, however, separates the juices for classification somewhat better than the classification of juices performed by PCA.</p>