El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado. / Nutritional deficiencies detection for coffee leaves is a task which is often undertaken manually by experts on the field known as agronomists. The process they follow to carry this task is based on observation of the different characteristics of the coffee leaves while relying on their own experience. Visual fatigue and human error in this empiric approach cause leaves to be incorrectly labeled and thus affecting the quality of the data obtained. In this context, different crowdsourcing approaches can be applied to enhance the quality of the data extracted. These approaches separately propose the use of voting systems, association rule filters and evolutive learning. In this paper, we extend the use of association rule filters and evolutive approach by combining them in a methodology to enhance the quality of the data while guiding the users during the main stages of data extraction tasks. Moreover, our methodology proposes a reward component to engage users and keep them motivated during the crowdsourcing tasks. The extracted dataset by applying our proposed methodology in a case study on Peruvian coffee leaves resulted in 93.33% accuracy with 30 instances collected by 8 experts and evaluated by 2 agronomic engineers with background on coffee leaves. The accuracy of the dataset was higher than independently implementing the evolutive feedback strategy and an empiric approach which resulted in 86.67% and 70% accuracy respectively under the same conditions. / Revisión por pares

La dernière décennie a vu l'exploitation d’application d’inspection automatique dans plusieurs domaines grâce à l’avancé des capteurs de vision et des méthodes d’analyse de texture et de segmentation d’images. Cependant, la nature difficile des images de chaussées (fortement texturée), la petite taille des défauts (fissures) conduisent au constat que l’inspection dans ce domaine est réalisée manuellement. Chaque année, en France, des opérateurs doivent visualiser des milliers de kilomètres d'images de route pour y relever des dégradations. Cette façon de faire est couteuse, lente et a un résultat plutôt subjectif. L’objectif de ce travail de thèse est de développer une méthode permettant la détection et la classification des fissures automatiquement sur ces images de chaussées. Le coeur de la thèse est une nouvelle méthode de segmentation, la Free Form Anisotropy (FFA). D'une part, elle permet de prendre en compte simultanément les attributs concernant la forme et l’intensité des pixels d’une fissure pour la détection. D’autre part, une nouvelle modélisation est utilisée en recherchant des chemins minima dans des graphes (images) afin de trouver la forme de la fissure dès qu'elle est présente dans l’image. Après la segmentation, l’extraction et la classification de défauts sont réalisées par une transformée de Hough et par le calcul de l’orientation locale des pixels. Les résultats expérimentaux ont été obtenus à partir de plusieurs bases d’images et compares avec des méthodes existantes. / These last decades have seen application of automatic inspection in many fields thanks to advanced vision sensors and image analysis methods. However, the difficult nature of pavement images, the small size of defects (cracks) lead to the fact that inspection in this area is done mostly manually. Each year in France, operator must view images of thousands kilometers of roads to detect these degradations. This method is expensive, slow and has a rather subjective result. The objective of this thesis is to develop a method for the detection and the classification of cracks on these pavement images automatically. In this thesis, a new method of segmentation has been developed: the Free Form Anisotropy (FFA). On one hand, this method allows to take into account both the features concerning form and intensity of cracks, for the detection. On the other hand, a new model is used to search minimum paths in graphs (images). This minimum path follows crack form when crack is present. After segmentation, extraction and classification of defects are performed by the Standard Hough Transform and by calculating local orientation of pixels. Experimental results have been obtained from different image databases and compared with other existing methods.

La richesse moléculaire des végétaux constitue une source importante de molécules bioactives d‘origine naturelle. La mise en évidence de ces molécules nécessite de nombreuses étapes souvent longues et couteuses. L‘objectif de cette thèse a donc consisté en l‘innovation et le développement de nouvelles méthodologies d‘extraction, de fractionnement et d‘identification de produits naturels d‘origine végétale. Pour cela nous avons utilisé comme modèle végétal l‘argousier (Hippophaë rhamnoides, Elaeagnaceae) qui est un arbuste épineux du plateau Eurasiatique connu pour sa richesse phytochimique et son potentiel thérapeutique. Ce travail a d‘abord conduit au développement d‘une méthode d‘extraction « verte » sans solvant assistée par micro-ondes, basée sur l‘utilisation combinée de la pression, de la température et des micro-ondes. Il a pu être démontré que cette méthodologie permet d‘extraire rapidement et efficacement des composés phénoliques tout en conservant un potentiel antioxydant important. Dans une seconde partie, une nouvelle approche multidimensionnelle couplant la CPC et l‘HPLC-UV-MS a été développée. Cette technique permet la séparation à l‘échelle semi-préparative et l‘identification en ligne des molécules séparées. Il a ainsi pu être identifié par HPLC-MS/MS 3 acides phénoliques et 20 dérivés de flavonols dans l‘extrait micro-ondes sans solvant de baies d‘argousier. L‘activité antioxydante et la cytotoxicité des fractions a également été étudiée in vitro et in cellulo. Enfin la dernière partie de ce travail a démontré le potentiel antioxydant et antimicrobien de différents organes de l‘argousier, qui a été corrélé à la présence flavonoïdes et de proanthocyanidine. L‘intérêt du couplage CPC-HPLC-UV-MS a également été illustré par le fractionnement de deux molécules d‘un extrait actif de racines d‘argousier. / Plant materials constitute an important source of natural bioactive molecules. Characterisation of these molecules requires often multiple, long and expensive development steps. The aim of this PhD thesis consists of innovation and development of new methods of extraction, fractionation and identification of natural metabolites from plants. We used sea buckthorn as plant model (Hippophaë rhamnoides, Elaeagnaceae) an Eurasian thorny shrub known to possess various phytochemical properties and pharmaceutical effects. In the first part of this work a ―green‖ solvent-free microwave assisted extraction, based on the combined use of pressure, temperature and microwave irradiation has been developed. This approach allows fast and efficient extraction of phenolic compounds while maintaining an important antioxidant capacity. In the second part of this work, a new multidimensional approach coupling CPC and HPLC-UV-MS was developed. This technique allows the separation at semi-preparative scale and the online identification of isolated molecules. Using this approach, 3 phenolic acids and 20 flavonols from the solvent free sea buckthorn berries extract were identified by HPLC-MS/MS. Antioxidant activity and cytotoxicity of fractions were studied in vitro and in cellulo. In the last part of this work, the antioxidant and antimicrobial potentials of different sea buckthorn organs, which were correlated to the presence of flavonoids and proanthocyanidins has been demonstrated. The CPC-HPLC-UV-MS technique was also applied to the fractionation and the partial identification of compounds extracted from sea buckthorn root.

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Bidentate imidazole-based extractants, 1-octylimidazole-2-aldoxime (OIMOX) and 1-octyl-2-(2′-pyridyl)imidazole (OPIM), along with dinonylnaphthalene sulfonic acid (DNNSA) as a synergist, were investigated as potential selective extractants for Cu²⁺and Ni²⁺ respectively from base metals in a solvent extraction system. The study was extended to evaluate the sorption and separation of Ni²⁺ from other base metals in a solid-solution system using microspherical Merrifield resins and nanofibers functionalized with 2,2′-pyridylimidazole. Copper was effectively separated with OIMOX and DNNSA as extractants from nickel with ΔpH½ ≈1.05 and the extraction order of Cu²⁺ > Ni²⁺ > Zn²⁺ > Cd²⁺> Co²⁺ was achieved as a function of pH. At pH 1.65 the extracted copper, from a synthetic mixture of the base metals reached 90.13(±0.90)%, and through a two-step extraction process 98.22(±0.29)% copper was recovered with negligible nickel and cobalt impurities. Stripping of the copper from the loaded organic phase using TraceSelect sulphuric acid at pH 0.35 yielded 96.60(±0.44)% of the loaded quantity after the second stage of stripping. The separation of Ni²⁺ from the borderline and hard acids; Co²⁺, Cu²⁺, Zn²⁺, Fe2²⁺, Fe²⁺, Mn²⁺, Mg2²⁺ and Ca²⁺ at a pH range of 0.5-3.5 with OPIM and DNNSA was acvieved to the tune of a ΔpH½≈ 1.6 with respect to cobalt from a sulfate and sulfate/chloride media. A three-stage counter-current extraction of Ni²⁺, at the optimized pH of 1.89, from a synthetic mixture of Ni²⁺, Co²⁺ and Cu²⁺, yielded 99.01(±1.79)%. The total co-extracted Cu²⁺ was 48.72(±0.24)% of the original quantity in the mixture, and it was 19.85(±0.28%) for Co²⁺. The co-extracted Cu²⁺ was scrubbed off from the loaded organic phase at pH≈8.5 by using an ammonium buffer, while co-extracted Co²⁺ was selectively and quantitatively stripped with H₂SO₄ at pH 1.64. The total recovery of Ni²⁺ by stripping at pH 0.32 was 94.05(±1.70)%. In the solid-liquid system, Ni²⁺ was separated from Co²⁺, Cu²⁺, and Fe²⁺ with the microspherical resins funtionalised with 2,2′-pyridylimidazole by a separation factor (β) in the range 22-45. Electrospun nanofibers as sorbents yielded high sorption capacity in the range of 0.97 - 1.45 mmol.g⁻¹ for the same metals ions. Thus, 1-octylimidazole-2-aldoxime (OIMOX), and1-octyl-2-(2′-pyridyl)imidazole (OPIM) can be effectively utilized alongside DNNSA as a co-extractant in the separation of Cu²⁺ and Ni²⁺ respectively from base metals in acidic sulfate medium in a solvent extraction process, and the latter as a selective ligand in the solid-liquid separation of Ni²⁺ from Co²⁺, Cu²⁺, and Fe²⁺.

Les lignanes sont des métabolites secondaires végétaux, dont la fonction biologique reste aujourd’hui inconnue in planta, mais qui présentent un intérêt en santé humaine. Cette étude vise à progresser dans la connaissance de la fonction des lignanes dans la plante en étudiant la régulation de la biosynthèse de ces molécules. Cette étude a été menée chez des lins : Linum usitatissimum (espèce cultivée) et Linum flavum (espèce sauvage). Chez Linum usitatissimum, la régulation spatio-temporelle de la biosynthèse des lignanes a été établie et il a été démontré que l’acide abscissique régulait la biosynthèse des lignanes dans la graine. Chez Linum flavum, un gène clé dans la production de lignanes a été isolé et la régulation spatiotemporelle de la biosynthèse des lignanes a été établie. Un protocole amélioré d’extraction de sécoisolaricirésinol utilisant une cellulase a été mis au point à partir de téguments de graines de Linum usitatissimum. Enfin de nouvelles sources de lignanes cytotoxiques parmi les Juniperus et Callitris ont été identifiées, et l’extraction de ces composés à partir de feuilles a été optimisée. / Lignans are plant secondary metabolites whose in planta biological function is still unknown but are of interest for human health. This work aims at understanding the function of plant lignans through the study of the lignans biosynthesis regulation. This study was conducted in flax: Linum usitatissimum (cultivated species) and Linum flavum (wild species). In Linum usitatissimum, spatial and temporal regulation of lignans biosynthesis has been established and it has been shown that abscisic acid regulates the lignan biosynthesis in seed coats. In Linum flavum, a key gene of lignans production has been isolated, spatial and temporal regulation of lignans biosynthesis has been established. An improved protocol for secoisolariciresinol extraction from Linum usitatissimum seed teguments involving the use of a cellulase was developed. Finally new sources of cytotoxic lignans were identified among Juniperus and Callitris species and extraction from leaves was optimized.

Purpose. This work addresses an escalating problem within the realm of scientific publishing, that stems from accelerated publication rates of article formats difficult to process automatically. The amount of manual labour required to organise a comprehensive corpus of relevant literature has long been impractical. This has, in effect, reduced research efficiency and delayed scientific advancement. Two complementary approaches meant to alleviate this problem are detailed and improved upon beyond the current state-of-the-art, namely logical structure recovery of articles and keyphrase extraction. Methodology. The first approach targets the issue of flat-format publishing. It performs a structural analysis of the camera-ready PDF article and recognises its fine-grained organisation over logical units. The second approach is the application of a keyphrase extraction algorithm that relies on rhetorical information from the recovered structure to better contour an article’s true points of focus. A recount of the scientific article’s function, content and structure is provided, along with insights into how different logical components such as section headings or the bibliography can be automatically identified and utilised for higher-quality keyphrase extraction. Findings. Structure recovery can be carried out independently of an article’s formatting specifics, by exploiting conventional dependencies between logical components. In addition, access to an article’s logical structure is beneficial across term extraction approaches, reducing input noise and facilitating the emphasis of regions of interest. Value. The first part of this work details a novel method for recovering the rhetorical structure of scientific articles that is competitive with state-of-the-art machine learning techniques, yet requires no layout-specific tuning or prior training. The second part showcases a keyphrase extraction algorithm that outperforms other solutions in an established benchmark, yet does not rely on collection statistics or external knowledge sources in order to be proficient.

Orientador: Everson Alves Miranda, Paulo de Tarso Vieira e Rosa / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Química / Made available in DSpace on 2018-08-18T17:30:17Z (GMT). No. of bitstreams: 1 Costa_MaxAdilsonLima_M.pdf: 2358919 bytes, checksum: 4bfe6ce2439dc359cd00e7a3a2bb2d86 (MD5) Previous issue date: 2011 / Resumo: Madeiras sofrem ataques de fungos que comprometem a sua resistência e valor de mercado, levando a indústria madeireira a buscar fungicidas capazes de reduzir as perdas no setor. Nesse contexto, a espécie Senna reticulata aparece como possibilidade promissora, pois estudos preliminares revelaram a existência de substâncias, ainda não identificadas, em diferentes partes dessa planta com atividade fungicida e/ou fungistática. Assim, o presente trabalho objetivou a obtenção de compostos antifúngicos a partir de folhas secas de S. reticulata por extração convencional e supercrítica. Estudou-se o efeito da temperatura, pH, força iônica e tipo de solvente (água, etanol e composição destes) sobre a concentração de compostos fenólicos e proteínas nos extratos produzidos em tanque agitado. Na extração supercrítica, estudou-se o efeito da pressão e da temperatura sobre a concentração de compostos fenólicos nos extratos. Na extração convencional a composição do solvente, temperatura e pH apresentaram efeito sobre a concentração de compostos fenólicos e proteínas nos extratos. Para a extração supercrítica, o rendimento dos extratos foi afetado pela pressão do sistema. No entanto, o extrato com o menor rendimento em massa teve o maior teor de compostos fenólicos. Nos testes de atividade antifúngica, todos os extratos convencionais apresentaram ação contra os fungos utilizados. Os extratos supercríticos em baixas concentrações (baixas concentrações foram necessárias devido à utilização de etanol como solvente/diluente) apresentaram pequena ou nenhuma atividade sobre o crescimento dos fungos. Portanto, a extração convencional mostrou ser uma técnica promissora para a obtenção de extratos com efeito antifúngico de S. reticulata por apresentar alto rendimento, atividade antifúngica considerável, tempo de extração curto / Abstract: Wood suffers fungal attacks which undertake its resistance and market value, taking the wood industry to search for fungicides capable of to reduce losses in the sector. In this context, Senna reticulata appears as a promising possibility because preliminary studies revealed the existence of yet unidentified substances from various parts of this plant with fungicide and/or fungistatic activity. Thus, this work aimed to obtain antifungal compounds from dried leaves of S. reticulata by conventional and supercritical extraction. We studied the effect of temperature, pH, ionic strength, and type of solvent (water, ethanol and composition of this two) on the concentration of phenolic compounds and proteins in the extracts produced using stirred tanks. In the supercritical extraction we studied the effect of pressure and temperature on the phenolic compounds extraction. In the conventional extraction the solvent composition, temperature, and pH showed effect on the concentration of phenolic compounds and proteins in the extracts. For the supercritical extraction, yield of extracts was affected by the pressure of the system. However, the extract with the lowest yield in mass, had the highest content of phenolic compounds. In tests for antifungal activity, all conventional extracts showed activity against the fungi used. Supercritical extracts at low concentrations (low concentration required due to the ethanol used as a solvent/diluents) showed small and no activity on fungal growth. Therefore, the conventional extraction showed to be as a promising technique for obtaining extracts with antifungal effect from S. reticulata because of high yield, considerable antifungal activity, and short extraction time / Mestrado / Desenvolvimento de Processos Biotecnologicos / Mestre em Engenharia Química

In my dissertation, I elaborate on the work that I have done to extract temporally-anchored spatial knowledge from text, including both intra- and inter-sentential knowledge. I also detail multiple approaches to infer spatial timeline of a person from biographies and social media. I present and analyze two strategies to annotate information regarding whether a given entity is or is not located at some location, and for how long with respect to an event. Specifically, I leverage semantic roles or syntactic dependencies to generate potential spatial knowledge and then crowdsource annotations to validate the potential knowledge. The resulting annotations indicate how long entities are or are not located somewhere, and temporally anchor this spatial information. I present an in-depth corpus analysis and experiments comparing the spatial knowledge generated by manipulating roles or dependencies. In my work, I also explore research methodologies that go beyond single sentences and extract spatio-temporal information from text. Spatial timelines refer to a chronological order of locations where a target person is or is not located. I present corpus and experiments to extract spatial timelines from Wikipedia biographies. I present my work on determining locations and the order in which they are actually visited by a person from their travel experiences. Specifically, I extract spatio-temporal graphs that capture the order (edges) of locations (nodes) visited by a person. Further, I detail my experiments that leverage both text and images to extract spatial timeline of a person from Twitter.