O biodiesel tem sido amplamente utilizado como uma fonte de energia renovável, que contribui para a diminuição de demanda por diesel mineral. Portanto, existem várias propriedades que devem ser monitoradas, a fim de produzir e distribuir biodiesel com a qualidade exigida. Neste trabalho, as propriedades físicas do biodiesel, tais como massa específica, índice de refração e ponto de entupimento de filtro a frio foram medidas e associadas a espectrometria no infravermelho próximo (NIR) e espectrometria no infravermelho médio (Mid-IR) utilizando ferramentas quimiométricas. Os métodos de regressão por mínimos quadrados parciais (PLS), regressão de mínimos quadrados parciais por intervalos (iPLS), e regressão por máquinas de vetor de suporte (SVM) com seleção de variáveis por Algoritmo Genético (GA) foram utilizadas para modelar as propriedades mencionadas. As amostras de biodiesel foram sintetizadas a partir de diferentes fontes, tais como canola, girassol, milho e soja. Amostras adicionais de biodiesel foram adquiridas de um fornecedor da região sul do Brasil. Em primeiro lugar, o pré-processamento de correção de linha de base foi usado para normalizar os dados espectrais de NIR, seguidos de outros tipos de pré-processamentos que foram aplicados, tais como centralização dos dados na média, 1 derivada e variação de padrão normal. O melhor resultado para a previsão do ponto de entupimento de filtro a frio foi utilizando os espectros de Mid-IR e o método de regressão GA-SVM, com alto coeficiente de determinação da previsão, R2Pred=0,96 e baixo valor da Raiz Quadrada do Erro Médio Quadrático da previsão, RMSEP (C)= 0,6. Para o modelo de previsão da massa específica, o melhor resultado foi obtido utilizando os espectros de Mid-IR e regressão por PLS, com R2Pred=0,98 e RMSEP (g/cm3)= 0,0002. Quanto ao modelo de previsão para o índice de refração, o melhor resultado foi obtido utilizando os espectros de Mid-IR e regressão por PLS, com excelente R2Pred=0,98 e RMSEP= 0,0001. Para esses conjuntos de dados, o PLS e o SVM demonstraram sua robustez, apresentando-se como ferramentas úteis para a previsão das propriedades do biodiesel estudadas / Biodiesel has been widely used as a renewable energy source which contributes to the mineral diesel decrease demand. Therefore, there are several properties that must be monitored in order to produce and distribute biodiesel with the required quality. In this work, the biodiesel physical properties such as specific mass, refractive index and cold filter plugging point were measured and associated with near infrared spectroscopy (NIR) and mid-Infrared spectroscopy (mid-IR) spectra using chemometric tools. The Partial Least Squares Regression (PLS), Interval Partial Least Squares Regression (iPLS), and Support Vector Machines Regression (SVM) with variable selection by Genetic Algorithm (GA) methods were used to model the aforementioned properties. The biodiesel samples were synthesized from different sources such as canola, sunflower, corn, and soybean. Additional biodiesel samples were purchased from a Brazil South Region supplier. Firstly, the preprocessing baseline correction was used to normalize the NIR spectral data, following others preprocessing types were applied in such as the mean center, the first derivative and standard normal variate. The best result for predicting the cold filter plugging point was using Mid-IR spectra and GA-SVM regression method, with high coefficient determination of prediction, R2Pred = 0.94 and low value of the Root Mean Square Error of Prediction, RMSEP (C) = 0.7. For the specific mass prediction model, the best result was obtained using the Mid-IR spectrums and PLS regression, with the R2Pred = 0.98 and RMSEP (g/cm3) = 0.0002. As for a prediction model for the refractive index, the best result was obtained using the Mid-IR spectrums and PLS regression, with the R2Pred = 0.98 and RMSEP = 0.0001. For these datasets, the PLS and SVM models demonstrated theirs robustness, presenting themselves as useful tools for the biodiesel properties prediction studied

Submitted by ANA KARLA PEREIRA RODRIGUES (anakarla_@hotmail.com) on 2017-08-09T15:33:48Z No. of bitstreams: 1 arquivototal.pdf: 4699110 bytes, checksum: ef3b7c0aa5c4758d2c77e65ad6a81ad3 (MD5) / Made available in DSpace on 2017-08-09T15:33:48Z (GMT). No. of bitstreams: 1 arquivototal.pdf: 4699110 bytes, checksum: ef3b7c0aa5c4758d2c77e65ad6a81ad3 (MD5) Previous issue date: 2016-06-20 / Conselho Nacional de Pesquisa e Desenvolvimento Científico e Tecnológico - CNPq / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / This work involves the development of two studies that are presented in chapters 2 and 3. At first, a new method to perform the calibration transfer was designed. This method was developed to make use of separate variables instead of using the full spectrum or spectral windows. To accomplish this task a univariate procedure is initially used to correct the spectra recorded in the secondary equipment, given a set of transfer samples. A robust regression technique is then used to obtain a model with small sensitivity with respect to the univariate correction. The proposed method is employed in two case studies involving near infrared spectrometric determination of specific mass, research octane number and naphtenes in gasoline, and moisture and oil in corn. In both cases, better calibration transfer results were obtained in comparison with piecewise direct standardization (PDS). In the second, a new strategy for cotton seed classification using near infrared (NIR) hyperspectral images (HSI) was developed. Initially the cotton seeds samples were recorded on a station HSI image-NIR and a conventional spectrometer NIR. Thereon, the images were segmented and the mean spectrum of each seed was extract. Classification models SPA-LDA e PLS-DA based on the mean spectral were developed for two data sets. The results for models SPA-LDA and PLSDA showed that the classification with HSI-NIR data set has been achieved with greater accuracy when compared to models for the NIR-conventional data set. / Este trabalho envolve o desenvolvimento de dois estudos, que são apresentados nos capítulos 2 e 3. No primeiro, um novo método para realizar a transferência de calibração foi concebido. Este método foi desenvolvido para fazer uso de variáveis isoladas em vez de usar todo o espectro ou janelas espectrais. Para realizar essa tarefa, um procedimento univariado é inicialmente usado para corrigir os espectros registrados no equipamento secundário, dado um conjunto de amostras de transferência. Uma técnica de regressão robusta é então usada para obter um modelo com pequena sensibilidade em relação aos resíduos da correção univariada. O novo método é então empregado em dois estudos de caso envolvendo análise espectrométrica NIR, em que foram determinados os parâmetros massa específica, RON (Research Octane Number) e teor de naftênicos em gasolina e os teores de água e óleo em amostras de milho. Os resultados do novo método foram melhores do que os obtidos usando o método PDS. No segundo, uma nova estratégia para classificação de sementes de algodão usando imagens hiperespectrais no NIR foi desenvolvido. Inicialmente as amostras de sementes de algodão foram registradas em uma estação de imagem HSI-NIR e em um equipamento NIR convencional. Após isso, as imagens foram segmentadas e os espectros médios de cada semente foram extraídos. Os modelos de classificação SPA-LDA e PLS-DA baseados nos espectros médios foram construídos para os dois conjuntos de dados. Os resultados SPA-LDA e PLS-DA para os modelos demonstraram que a classificação com os dados HSI-NIR foi alcançada com maior exatidão quando comparada aos modelos obtidos usando o NIR-convencional.

O biodiesel tem sido amplamente utilizado como uma fonte de energia renovável, que contribui para a diminuição de demanda por diesel mineral. Portanto, existem várias propriedades que devem ser monitoradas, a fim de produzir e distribuir biodiesel com a qualidade exigida. Neste trabalho, as propriedades físicas do biodiesel, tais como massa específica, índice de refração e ponto de entupimento de filtro a frio foram medidas e associadas a espectrometria no infravermelho próximo (NIR) e espectrometria no infravermelho médio (Mid-IR) utilizando ferramentas quimiométricas. Os métodos de regressão por mínimos quadrados parciais (PLS), regressão de mínimos quadrados parciais por intervalos (iPLS), e regressão por máquinas de vetor de suporte (SVM) com seleção de variáveis por Algoritmo Genético (GA) foram utilizadas para modelar as propriedades mencionadas. As amostras de biodiesel foram sintetizadas a partir de diferentes fontes, tais como canola, girassol, milho e soja. Amostras adicionais de biodiesel foram adquiridas de um fornecedor da região sul do Brasil. Em primeiro lugar, o pré-processamento de correção de linha de base foi usado para normalizar os dados espectrais de NIR, seguidos de outros tipos de pré-processamentos que foram aplicados, tais como centralização dos dados na média, 1 derivada e variação de padrão normal. O melhor resultado para a previsão do ponto de entupimento de filtro a frio foi utilizando os espectros de Mid-IR e o método de regressão GA-SVM, com alto coeficiente de determinação da previsão, R2Pred=0,96 e baixo valor da Raiz Quadrada do Erro Médio Quadrático da previsão, RMSEP (C)= 0,6. Para o modelo de previsão da massa específica, o melhor resultado foi obtido utilizando os espectros de Mid-IR e regressão por PLS, com R2Pred=0,98 e RMSEP (g/cm3)= 0,0002. Quanto ao modelo de previsão para o índice de refração, o melhor resultado foi obtido utilizando os espectros de Mid-IR e regressão por PLS, com excelente R2Pred=0,98 e RMSEP= 0,0001. Para esses conjuntos de dados, o PLS e o SVM demonstraram sua robustez, apresentando-se como ferramentas úteis para a previsão das propriedades do biodiesel estudadas / Biodiesel has been widely used as a renewable energy source which contributes to the mineral diesel decrease demand. Therefore, there are several properties that must be monitored in order to produce and distribute biodiesel with the required quality. In this work, the biodiesel physical properties such as specific mass, refractive index and cold filter plugging point were measured and associated with near infrared spectroscopy (NIR) and mid-Infrared spectroscopy (mid-IR) spectra using chemometric tools. The Partial Least Squares Regression (PLS), Interval Partial Least Squares Regression (iPLS), and Support Vector Machines Regression (SVM) with variable selection by Genetic Algorithm (GA) methods were used to model the aforementioned properties. The biodiesel samples were synthesized from different sources such as canola, sunflower, corn, and soybean. Additional biodiesel samples were purchased from a Brazil South Region supplier. Firstly, the preprocessing baseline correction was used to normalize the NIR spectral data, following others preprocessing types were applied in such as the mean center, the first derivative and standard normal variate. The best result for predicting the cold filter plugging point was using Mid-IR spectra and GA-SVM regression method, with high coefficient determination of prediction, R2Pred = 0.94 and low value of the Root Mean Square Error of Prediction, RMSEP (C) = 0.7. For the specific mass prediction model, the best result was obtained using the Mid-IR spectrums and PLS regression, with the R2Pred = 0.98 and RMSEP (g/cm3) = 0.0002. As for a prediction model for the refractive index, the best result was obtained using the Mid-IR spectrums and PLS regression, with the R2Pred = 0.98 and RMSEP = 0.0001. For these datasets, the PLS and SVM models demonstrated theirs robustness, presenting themselves as useful tools for the biodiesel properties prediction studied

A esterificação do sec-butanol com ácido acético, submetida à catálise homogênea, apresenta poucos resultados experimentais de cinética reacional e equilíbrio químico disponíveis na literatura. A presente dissertação visa determinar os parâmetros cinéticos e de equilíbrio químico desta reação de esterificação, empregando modelo cinético de 2ª ordem baseado em atividades. Os experimentos cinéticos foram realizados em reator batelada com auxílio da metodologia Karl Fischer para análise do teor de água e determinação do perfil de frações molares ao longo da reação. A principal dificuldade na modelagem desta esterificação consistiu em representar satisfatoriamente as não-idealidades da mistura em fase líquida, em espacial nas reações cuja fração molar inicial de ácido acético foi superior a 50%. Netas condições admitiu-se a ocorrência de dissociação do ácido acético levando ao surgimento de interações iônicas. O modelo empregado para obtenção das atividades, com base em frações molares, foi o NRTL. Este modelo representou bem as interações moleculares em condição de baixa acidez, mas apresentou desvios em condições de acidez e teores de água mais elevados. O estudo também visou o desenvolvimento de modelos de calibração para um método analítico on-line visando determinar o perfil de frações molares ao longo da reação. O método empregado foi a espectroscopia de infravermelho próximo (NIR), em vista à capacidade deste método analítico em determinar quantitativamente frações molares de água, além dos demais compostos envolvidos. Outro fator determinante ao emprego do NIR é a seu crescente uso no meio industrial, e o presente trabalho visou também contribuir para o uso futuro desta técnica de monitoramento no processo industrial. Modelos de calibração multivariável com conjuntos de calibração interna por validação cruzada se mostraram adequados ao sistema estudado. Calibrações externas resultaram em modelos imprecisos, não sendo possível determinar claramente os fatores responsáveis pela imprecisão. / There is a lack of literature data on the reaction kinetics and equilibrium of the homogeneously catalyzed esterification of sec-butanol with acetic acid. This work aims at obtaining the kinetic parameters and chemical equilibrium parameters of this esterification reaction by using a second order kinetic model based on activities. The kinetic experiments were performed in a batch reactor and the Karl Fischer analytical method was used to determine the molar fraction of water along the reaction progress. The main challenge of modeling this reaction was to represent the highly non-ideal mixture in liquid phase, specially for reactions runs starting with acetic acid mole fraction higher than 50%. In these conditions, it was assumed the occurrence of acetic acid dissociation that leads to ionic interactions. The thermodynamic model used to calculate the activities was the NRTL. This model predicted well the molecular interactions on low acidity conditions but presented deviations when molar fractions of acid and water were higher. The present study also aims to develop calibration models for analytical on-line method to obtain molar fraction profiles along the reaction. Near infrared spectroscopy (NIR) was used due to the possibility of quantitatively analyze water mole fraction, besides the mole fractions of the other components. Another important reason to choose NIR was its crescent use in industry, and the present work intended to contribute towards the future use of this on line monitoring technique in industrial applications. Multivariate calibration models using internal set of calibration and cross-validation seems to be suitable for this system. External set of calibration leads to less accurate models, and the causes of this lack of accuracy were not clearly identified.

Neste trabalho estudou-se o processo de polimerização de estireno em miniemulsão, através do monitoramento in-line da conversão do monômero e do tamanho das partículas geradas durante o processo de polimerização, através das técnicas espectroscópicas de Infravermelho Próximo (Near Infra Red - NIR) e Raman. As medições off-line de conversão foram feitas através de gravimetria e do tamanho das partículas através de Espalhamento Dinâmico de Luz (Dynamic Light Scattering - DLS). Também foi objeto deste estudo a modelagem matemática do process de polimerização em miniemulsão, assim como sua simulação utilizando o programa Matlab. A metodologia adotada para a obtenção dos resultados envolveu o trabalho experimental de monitoramento da síntese de poliestireno em miniemulsão utilizando iniciador hidrossolúvel (persulfato de potássio), tensoativo (lauril sulfato de sódio) e co-estabilizantes (hexadecano e poliestireno) e equipamento rotor-estator, Ultra Turrax T25, para obtenção da miniemulsão. O modelo matemático envolveu a determinação de equações fenomenológicas representativas do sistema em questão, prevendo as possíveis variações na cinética e fenômenos físico-químicos, decorrentes de variações na formulação prevendo inclusive os mecanismos de nucleação existentes em função da concentração de tensoativo utilizado. Como resultado, este trabalho validou as metodologias avaliadas para monitoramento da conversão e diâmetro das partículas poliméricas e também, ao comparar as metodologias avaliadas, identificou a espectroscopia NIR como metodologia preferencial por não exigir preparação da amostra, fornecer respostas em tempo real, sem defasagem de tempo e também por permitir coletar espectros com pequenos intervalos de tempo, garante melhor precisão e evita a perda de informações do processo. / In this work, is the development of a detailed study of the miniemulsion polymerization process monitoring monomer conversion and particle size along process. Near Infrared Spectroscopy (Near Infra Red - NIR) and Raman Spectroscopy were used to conversion and diameter determination. Gravimetric analyses were used to conversion determination. Dynamic Light Scattering (Dynamic Light Scattering - DLS) to particle size determination. It was also object of this study the Mathematical Modeling of Miniemulsion Polymerization Reaction Kinetic, as well as it simulation using Matlab software. The methodology used to obtain the results involved experimental work to synthesize and monitor miniemulsion polystyrene using water-soluble initiator (potassium persulfate), stabilizer (sodium lauryl sulfate) and co-stabilizers (hexadecane and polystyrene) and rotor-stator equipment Ultra Turrax T25 for miniemulsion obtaining. The mathematical model involved the determination of representative phenomenological equations this system, anticipating the possible variations in kinetics and physical-chemical phenomena, resulting from formulation variations mainly by verifying the surfactant concentration [S] to determine the existing nucleation mechanism when compared with the same surfactant critical micelle concentration [CMC]. The provided mechanisms are: micellar nucleation to [S] [CMC], droplets nucleation and homogeneous nucleation to [S] < [CMC]. As a result, this study validated the proposed methods for monitoring conversion and polymer particles diameter and also compare the evaluated methodologies, identifying NIR spectroscopy as a differential method among others for not to require sample preparation, supply answers in real time, no time delay and also to perform in shorter intervals, preventing the loss of process information.

Dans cette thèse nous proposons de mettre en œuvre des méthodes des mathématiques appliquées et du traitement du signal pour l’étude à partir de spectres infrarouges (IR) de l’évolution des litières végétales au cours du processus de biodégradation. Nous présentons tout d’abord une nouvelle méthode de classification floue fondée sur une optimisation de type non supervisée, basée sur le facteur de covariance qui permet de classer des données IR de forme sphérique ou non sphérique afin d’identifier les méthodes de prétraitement et de choix de gammes spectrales les mieux adaptées. Nous développons des outils mathématiques et des algorithmes innovants permettant de combiner des informations spectrales moyen IR (MIR) et proche IR (MIR) afin d’identifier des marqueurs spectroscopiques discriminants de résidus lignocellulosiques en fonction de leur niveau de dégradation. Pour cela, nous proposons une méthode d'optimisation stochastique basée sur un algorithme génétique avec paramètres adaptés. Nous montrons que l’analyse conjoints des spectres MIR et NIR fusionnés par le produit extérieur permet de mieux discriminer la biomasse lignocellulosique au cours du processus de dégradation qu’un traitement séparé. Nous proposons ensuite une nouvelle approche d’optimisation non linéaire basée sur la sélection d’un vecteur qui met en évidence les poids des bandes spectrales. Enfin, nous développons une méthode de modélisation mathématique basée sur l’extension de l’algorithme AG-PLS en combinant les informations spectrales MIR et NIR par le produit extérieur (OP-AG-PLS). Cette méthode permet d’améliorer les performances de prédiction de l’état de dégradation de la biomasse. / In this thesis we propose to implement methods of applied mathematics and signal processing for the study of the evolution of plant biomass during the biodegradation process. The degradation of plant biomass is identified by FTIR spectroscopy, particularly in the MIR and NIR ranges. We proposed a new unsupervised classification method of Fuzzy C-Means based on the covariance factor to classify the IR data with spherical and not spherical form to identify the pre-treatment methods and the choice of spectral ranges that are the best adapted for our study. We have developed mathematical tools and innovative algorithms to combine these spectral information and identifying infrared spectroscopic markers that are discriminative in the lignocellulosic residues according to their level of degradation. For this, we have proposed a stochastic optimization method based on a genetic algorithm by choosing the appropriate parameters. We have shown that the joint analysis of the MIR and NIR spectra by the outer product (OP) provides better results than the separate analysis for the discrimination of the lignocellulosic biomass during the degradation process. Then, we proposed a new nonlinear optimization approach based on the built of vector which highlights the weight of spectral bands. Finally, we have developed a mathematical modelisation based on the extension of the GA-PLS algorithm combining the MIR and NIR spectral information by outer product (OP-GA-PLS) which significantly improves the prediction performance of the state of degradation of biomass.

[ES] La presente tesis doctoral titulada "Nuevas sondas, portadores y pro-fármacos dirigidos a células senescentes in vivo" se centra en el diseño, preparación, caracterización y evaluación de sondas basadas en fluoróforos funcionalizados o en nanopartículas, así como en el desarrollo de profármacos, aplicadas al campo de la senescencia celular. En el primer capítulo se introducen, a nivel general, los diferentes conceptos relacionados con el reconocimiento molecular y la detección de biomarcadores. Seguidamente se introducen conceptos básicos de senescencia celular y envejecimiento, así como el papel que juegan las células senescentes a nivel fisiológico, en enfermedades asociadas al envejecimiento celular y en el cáncer. Por último, se aborda también la creciente necesidad de desarrollar nuevas herramientas de diagnóstico y terapias centradas en la detección y tratamiento de dichas enfermedades. En el segundo capítulo se exponen los objetivos generales de la presente tesis doctoral, así como los objetivos concretos que son abordados en los diferentes capítulos experimentales. En el tercer capítulo se describe una nueva sonda molecular para la detección de senescencia in vivo. En concreto, se describe el diseño de una sonda de dos fotones basada en un fluoróforo de naftalimida conectada, mediante un éster metílico de L-histidina, con una galactosa acetilada que esta unida a uno de los átomos de nitrógeno aromático de la L-histidina a través de un enlace N-glicosídico hidrolizable (AHGa). La sonda inicial presenta una baja emsión pero en células senescentes se transforma en un fluoróforo con alto rendimiento cuantico que permite visualizar estas células debido a la hidrólisis del enlace N-glicosidico por la enzima ¿-galactosidasa sobreexpresada en este tipo de células. La sonda es capaz de detectar in vitro células de melanoma humano SK-Mel-103 tratadas con quimioterapia inductora de senescencia frente a células control. Adicionalmente, se validó la detección in vivo de senescencia en ratones con xenoinjertos tumorales tratados con quimioterapia inductora de senescencia. Basándonos en los resultados obtenidos en el capítulo tres, en el capítulo cuatro se describe un sistema similar cuyas características confieren al fluoróforo una mayor longitud de onda de excitación (HeckGal). La nueva sonda es capaz de detectar células senescentes debido a la sobreexpresión de la enzima ¿-galactosidasa asociada a senescencia en gran variedad de líneas celulares con diversos métodos de inducción de senescencia. Esta sonda se validó también in vivo en un modelo ortotópico de cáncer de mama de ratón tratado con quimioterapia inductora de senescencia, y en un modelo de ratón de fibrosis renal. Seguidamente, el capítulo cinco, se centra en un nuevo concepto de sondas moleculares no invasivas, que proporcionan una señal fácilmente legible a través de simples medidas de fluorescencia de la orina. Esta idea se llevó a cabo mediante la funcionalización de una sonda con grupos que le confieren características diuréticas (rápida eliminación renal) y el concepto se aplicó al diseño de una sonda para a la detección en orina de la carga senescente en diversos modelos. La sonda (Cy7Gal) está basada en la cianina-7 que es hidrolizada por la enzima ¿-galactosidasa en un fluoróforo altamente emisivo Cy7. Cy7Gal y Cy7 contienen restos de ácido sulfónico que aumentan su solubilidad en agua y desencadenan su rápida excreción por el sistema urinario. El grado de senescencia se cuantificó por medición directa de fluorescencia en orina en tres modelos de senescencia en ratones: (i) un modelo ortotópico de cáncer de mama en ratones BALB/cByJ con senescencia inducida por quimioterapia; (ii) ratones BALB / cByJ envejecidos de forma natural; y (iii) ratones con senescencia acelerada (SAMP8, del inglés Senescence Accelerated Mouse-Prone 8). Además, las imágenes IVIS ex vivo permite / [CA] La tesi doctoral titulada "Noves sondes, portadors i profàrmacs dirigits a cèl·lules senescents in vivo" se centra en el desenvolupament i avaluació de sondes basades en fluoròfors funcionalitzats o en nanopartícules, així com en el desenvolupament de profàrmacs, aplicades a el camp de la senescència cel·lular. Primer s'introdueixen els diferents conceptes relacionats amb el sensing i amb la sescencia cel·lular, abordant la necessitat de noves eines diagnòstiques i terapèutiques d'aquestes malalties. En els capítols 3:04 es descriuen una nova sonda molecular dos fotons per a la detecció de senescència in vivo en ratolins amb xenoempelts tumorals tractats amb quimioteràpia inductora de senescència, una altra sonda per a la detecció in vivo en un model ortotòpic de càncer de mama de ratolí tractat amb quimioteràpia inductora de senescència, i en un model de ratolí de fibrosi renal. El capítol 5, se centra en un nou concepte de sondes moleculars no invasives, que proporcionen un senyal fàcilment llegible a través de simples mesures de fluorescència de l'orina. Finalment, pel que fa a detecció de senescència cel·lular es refereix, es presenta en el capítol sis la detecció in vivo de senescència cel·lular mitjançant l'alliberament controlat de Nile Blue en nanopartícules de sílice mesoporoses funcionalitzades amb un galactohexasacárido. Un cop assolits els objectius planificats pel que fa a la diagnosi, en el capítol set es va abordar la millora d'un dels senolíticos més potents i àmpliament conegut en el camp de la senescència cel·lular que existeix a dia d'avui al mercat: el Navitoclax. / [EN] The doctoral thesis entitled "New probes, carriers and pro-drugs directed to senescent cells in vivo" focuses on the development and evaluation of probes based on functionalized fluorophores or nanoparticles, as well as on the development of prodrugs, applied to the field of cellular senescence. First, the different concepts related to sensing and cell sescence are introduced, addressing the need for new diagnostic and therapeutic tools for these diseases. Chapters three and four describe a new two-photon molecular probe for in vivo senescence detection in mice with tumor xenografts treated with senescence-inducing chemotherapy, another probe for in vivo detection in an orthotopic mouse breast cancer model. treated with senescence-inducing chemotherapy, and in a mouse model of renal fibrosis. Chapter five focuses on a new concept of non-invasive molecular probes, which provide an easily readable signal through simple measurements of urine fluorescence. Finally, regarding the detection of cellular senescence, chapter six presents the in vivo detection of cellular senescence through the controlled release of Nile Blue in mesoporous silica nanoparticles functionalized with a galactohexasaccharide. Once the planned objectives with regard to diagnosis had been achieved, chapter seven addressed the improvement of one of the most powerful and widely known senolytics in the field of cellular senescence that exists on the market today: Navitoclax. / The authors thank the financial support from the Spanish Government (projects MAT2015-64139-C4-1-R and AGL2015-70235-C2-2-R) and the Generalitat Valenciana (project PROMETEOII/2014/047). R.M laboratory members thank the financial support from the Spanish Government (project RTI2018-100910-B-C41) and the Generalitat Valenciana (project PROMETEO 2018/024). B.L-T. is grateful to the Spanish Ministry of Economy for their PhD grants (FPU15/02707). Work in the laboratory of MS was funded by the IRB and by grants from the Spanish Ministry of Economy co-funded by the European Regional Development Fund (ERDF) (SAF2013-48256-R), the European Research Council (ERC-2014-AdG/669622), and the “laCaixa” Foundation. D.M.-E. laboratory is supported by the Cancer Research UK (CRUK) Cambridge Centre Early Detection Programme, by a CRUK Early Detection OHSU Project Award (C62187/A26989), by a Medical Research Council (MRC) New Investigators Research Grant (NIRG, MR/R000530/1). Work in the laboratory of I.F. is supported by grants from the Spanish Government (SAF2017-86690-R), Instituto de Salud Carlos III (CIBERNED and RETIC Tercel), and Generalitat Valenciana (Prometeo 2017/030). / Lozano Torres, B. (2021). Novel probes, carriers and prodrugs to target senescent cells in vivo [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/172175 / TESIS

Ziel dieser Arbeit war es, die mechanistischen Abläufe bei der Papierleimung mit ASA besser zu verstehen und weiter aufzuklären, um vor allem Wechselwirkungen mit Füllstoffen und anderen chemischen Additiven zu minimieren. Dazu sollten analytische Verfahrensmethoden entwickelt werden, welche die bilanztechnische Verfolgung von ASA und dessen Reaktionsprodukten ermöglichen, um anschließend den Einfluss und die Wechselwirkungen verschiedenster Parameter auf die ASA-Leimung untersuchen zu können. Weiterhin sollte bei Untersuchungen zur Emulgierung versucht werden, die wichtigsten Einflussgrößen auf die Partikelgröße, Stabilität und Hydrolyse des ASA aufzuzeigen. Im ersten Teil der Arbeit konnten bei den Untersuchungen zur Emulgierung wichtige Einflussgrößen auf die Partikelgröße, Stabilität und Hydrolyse von ASA-Emulsionen aufgeklärt werden. Weiterhin wurde eine Methode zur genauen Bestimmung der Reaktionskinetik der ASA-Hydrolyse sowie der Ablagerungsneigung entwickelt. Bei den Untersuchungen zur analytischen Bestimmung wurde über die NIR-Spektroskopie ein einfaches Analyseverfahren zur exakten quantitativen Bestimmung von ASA und AKD entwickelt. Es wurde gefunden, dass eine quantitative Erfassung von synthetischen Leimungsmitteln (ASA / AKD) mittels NIR in den Regionen der CH2-Schwingungen um 4300 cm-1 und 5750 cm-1 mit hoher statistischer Genauigkeit möglich ist. Der Methodenfehler für die Bestimmung von AKD liegt bei ± 0,010 % und bei ± 0,013 % für ASA. Dadurch ist eine wesentlich genauere Bewertung von Wechselwirkungen bei der Leimung als bisher möglich, da nicht nur die Leimungswirkung, sondern über NIR auch Menge und Art (gebunden / ungebunden) an Leimungsmittel in einer bisher nicht erreichbaren Messzeit betrachtet werden können. Mittels HPLC und Pyrolyse-GC/MS konnten die erstellten NIR-Kalibrationen erfolgreich validiert werden. Im letzten Teil der Arbeit wurden Wechselwirkungen von ASA mit Füllstoffen und chemischen Additiven aufgeklärt, sowie mechanistische Grundlagen zur Leimung mit ASA erarbeitet. Hier hat sich gezeigt, dass der Mechanismus der ASA-Leimung nicht nur, wie oft in der Literatur beschrieben, auf eine Veresterung mit den Hydroxylgruppen der Cellulose zurückzuführen ist. Vielmehr ist die optimale Wirkung von Leimungsmitteln sehr stark von deren Verteilung, Mobilität und Orientierung abhängig. Weiterhin konnte festgestellt werden, dass der größte Anteil des Leimungsmittels im Papier in ungebundener (hydrolisierter) Form vorliegt und somit zur Wanderung (Migration) durch das Papiergefüge befähigt ist. Trotzdem kann der hydrolisierte Anteil deutlich zur Hydrophobierung des Papiers beitragen, wenn dieser richtig orientiert und fein verteilt ist. Schlecht orientierte Leimungsmittel tragen nicht zur Leimung bei bzw. können diese sogar reduzieren. In der vorliegenden Arbeit wurden unter Einsatz moderner Methoden wichtige Grundlagen zur Papierleimung mit ASA erarbeitet. Dabei wurden insbesondere Beiträge zu den Themen Emulgierung, Hydrolyse- und Ablagerungsneigung, analytische Bestimmung, Wechselwirkungen sowie Mechanismen von ASA geleistet. Diese Ergebnisse zeigen Möglichkeiten auf, wie in Unternehmen der Papierindustrie zukünftig ASA-Leimungsmittel gezielter dosiert, Produktionsstörungen vermieden und Kosten reduziert werden können. / The purpose of this work was to develop a deeper understanding of the mechanisms in ASA sizing and to minimise interactions with fillers and other chemical additives. Therefore analytical test methods were developed, to enable a simple mass balance approach for ASA and its reaction products. Afterwards, the influence of various factors affecting ASA sizing and retention could be investigated and explained. Furthermore, the most important factors which influence particle size, stability, and hydrolysis of ASA emulsions had to be determined. In the first part of this work, studies regarding the emulsification of ASA were carried out. Here, the most important factors with regard to particle size, stability, and hydrolysis of ASA emulsions were investigated. Furthermore, a method for the exact determination of ASA hydrolysis as well as the agglomeration tendency was developed. For the investigations regarding the analytical determination, a fast and easy-to-use method for the quantification of ASA and AKD has been developed. The investigations have shown that a quantitative determination of synthetic sizing agents (ASA / AKD) is possible using NIR spectroscopy. With the help of multivariate data analysis and PLS regression, mainly the region of the CH2-bands around 4300 cm-1 and 5750 cm-1 were evaluated. The prediction error (RMSEP) for the determination of AKD is 0.01 %, and 0.013 % for ASA. Even an analysis of the percentage of bound and unbound ASA / AKD is possible by NIR spectroscopy of extracted paper samples. Thus, a fast and detailed investigation of mechanisms as regards sizing is possible. The developed NIR methods were validated using HPLC and Pyrolysis-GC/MS. In the last part of the work, interactions of ASA with fillers and chemical additives were investigated, and mechanisms of ASA sizing were studied. It was shown that the mechanism of ASA sizing - as often described in the literature - can not only be attributed to the esterification with the hydroxyl groups of the cellulose. In fact, the optimal effect of sizing agents is much more dependant on a fine distribution, mobility and orientation of ASA molecules. It was observed that the main part of the ASA is present in an unbound (hydrolysed) form and therefore is able to migrate through the paper structure. However, the hydrolysed ASA can significantly contribute to sizing when it is finely distributed and well orientated. Sizing agents orientated in the opposite do not contribute to sizing but they can even decrease the existing sizing level. To summarize, it can be concluded that, in this work important fundamentals as regards ASA sizing were developed using modern test methods. Thereby important contributions were made to the topics of emulsification, hydrolysis- and emulsion-stability, analytical determination, interactions and mechanisms of ASA. These results show possibilities how ASA sizing agents can be used more effectively, process disturbances avoided, and costs reduced.

The global energy demand supplies mainly from fossil fuels, which is neither sustainable nor environmentally friendly and aims to global warming. Therefore, both more investments in renewable energy sources such as bioenergy are required, as well as new technologies such as carbon capture and storage (CCS) to handle the emissions from existing combined heat and power (CHP) plants. In this degree project, the focus is to determine the moisture content, ash content, heating value, and elemental compositions of solid biofuel mixtures in real-time by utilizing the optical technique of near-infrared (NIR) spectroscopy. A total number of 150 samples of solid biofuel mixtures were prepared and illuminated by NIR light. All spectra of the samples were recorded in a wavenumber range of 12000 cm-1 – 400 cm-1 in a dish on a turn table which was in a moving mode with a speed of 0.5 m/s. Each sample was scanned three times to avoid, or at least minimize the deviation of the spectra and the samples were mixed between each scan to get more reliable representative spectra data. Partial least square regression models were created to analyze the spectra data. A data split was done randomly, 100 for calibration and 50 for validation. Then the data was pre-processed with different methods including multiplicative scatter correction (MSC), standard normal variate (SNV), Savitzky-Golay 1st derivative (SG 1st), Savitzky-Golay 2nd derivative (SG 2nd), and orthogonal signal correction (OSC) to reduce noise and scatter effect. The results of NIR spectra treated by OSC method obtained  , RMSE and SE of 0.900, 2.241 and 2.204, respectively for prediction of moisture content, 0.424, 0.913 and 0.922 for prediction of ash content, 0.640, 0.370 and 0.368 for prediction of heating value, respectively. The obtained prediction of  , RMSE and SE were 0.687, 0.066 and 0.058 for nitrogen, 0.636, 0.361 and 0.364 for carbon, 0.483, 0.269 and 0.270 for hydrogen, respectively. As the results shows, these models to predict the ash content and hydrogen content has a lower accuracy than what is expected in process modeling while the prediction of moisture content has the highest accuracy.

This thesis presented an overview of the development of a geolocating algorithm as part of a geoprocessor for raw satellite imagery. This algorithm was devised for and limited by the specifications of a state-of-the-art multispectral telescope designed by Aistech Space, hosted onboard the Guardian spacecraft, which will observe Earth through the visible, near infrared, and thermal infrared bands of the electromagnetic spectrum. The geolocation algorithm presented here is composed of the combination of two models. The first is a physical model, which makes use of spacecraft telemetry and external satellite-tracking data to approximate the geographical center of a sensed scene. Secondly, an optical model obtains a reference Landsat image based on the timestamp and approximated location of the sensed scene and utilizes image processing techniques to pinpoint a more precise geographical location of the sensed scene within acceptable limits. This performance was achieved in 77% of the cases considered. To conclude, a roadmap of the subsequent development topics and their relevance was laid out. / Detta examensarbete presenterar en översikt för utvecklingen av en geolokaliseringsalgoritm som en del av en geoprocessor för obearbetade satellitbilder. Algoritmen anpassades för och begränsades av specifikationerna för ett toppmodernt multispektralt teleskop designat av Aistech Space. Teleskopet kommer att finnas ombord på rymdfarkosten Guardian, där den är avsedd att observera jorden i de synliga, nära infraröda och termiska infraröda delarna av det elektromagnetiska spektrumet. Geolokaliseringsalgoritmen som presenteras i detta arbete är sammansatt av en kombination av två modeller. Den första är en fysisk modell, vilken använder sig av rymdfarkostens telemetri och extern satellitspårningsdata för att approximera det geografiska centrumet av en plats. Den andra är en optisk modell, vilken använder sig av en Landsat-referensbild baserad på tidsstämpeln och den ungefärliga positionen av platsen och använder sedan bildbehandlingstekniker för att fastställa en mer exakt geografisk position av platsen inom acceptabla gränser. Denna prestation lyckades uppnås i 77% av de övervägda fallen. Avslutningsvis lades en plan ut för de efterföljande utvecklingsämnena och deras relevans.