Orientador: Flavia Maria Netto / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia de Alimentos / Made available in DSpace on 2018-08-14T13:49:46Z (GMT). No. of bitstreams: 1 Fernandes_MicheleAugusto_M.pdf: 2050778 bytes, checksum: aedc46d9b78bf413f7e34cfbe46a36a6 (MD5) Previous issue date: 2009 / Resumo: A ß-Lactoglubulina (ß-Lg) é uma das proteínas mais antigênicas presente no leite bovino. Tratamentos físicos, químicos ou enzimáticos podem alterar a antigenicidade desta proteína. Em trabalho anterior, verificou-se que o potencial antigênico da ß-Lg é reduzido quando polimerizada pela enzima transglutaminase (TG) na presença de cisteína (Cys). No entanto, o efeito da polimerização sobre o valor nutricional da ß-Lg ainda não é conhecido. O presente estudo teve como objetivo avaliar o efeito da reação de polimerização catalisada pela TG na digestibilidade in vitro e atividade antigênica da ß-Lg antes e após a ação das enzimas gastrintestinais. A ß-Lg polimerizada pela TG (0, 10 ou 25 U g-1), após tratamento térmico ou na presença de agentes redutores Cys (0, 0,1 e 0,25 mol L- 1) ou ditiotreitol (DTT 0,02 mol -1), foi avaliada quanto à digestibilidade in vitro, utilizando as enzimas pepsina e pancreatina. As amostras, antes e após a digestão in vitro, foram caracterizadas pelos métodos SDS-PAGE, SDSPAGE/ tricina e cromatografia líquida de alta eficiência de fase reversa (CLAE-FR). Posteriormente, as amostras foram avaliadas quanto à antigenicidade, exceto aquelas na presença de DTT, por meio do método de Imunoblote, utilizando soro de camundongos BALB/c sensibilizados com a ß-Lg na forma nativa (ß-Lg N) ou com ß-Lg polimerizada com 25 U de TG g-1, na presença de 0,25 mol L-1 de Cys (ß-Lg 0,25Cys 25TG). A adição de TG resultou na formação de polímeros com massa molar igual ou acima de 97,4 kDa, principalmente na presença de agentes redutores alcançando aproximadamente 96% de polimerização na presença de DTT e 91% na presença de Cys. A digestibilidade in vitro da ß-Lg N foi 53,6% e todos os tratamentos realizados aumentaram a digestibilidade da proteína em até 79%. Os maiores valores de digestibilidade foram obtidos quando a ß-Lg foi tratada com agentes redutores. O processo de polimerização também teve efeito positivo na digestibilidade, principalmente para as amostras polimerizadas na presença de Cys ou DTT, atingindo valores acima de 75%. A análise por Imunoblote mostrou que a polimerização da ß-Lg na presença de agente redutor Cys, na concentração de 0,25 mol L-1, reduziu o reconhecimento da ß-Lg pelas IgE específicas presente nos soros dos animais sensibilizados com ß-Lg N ou com ß- Lg 0,25Cys 25TG. Após a digestão com pepsina e pancreatina, as amostras polimerizadas pós-tratamento térmico ou na presença de Cys apresentaram redução da antigenicidade, como também os digeridos da ß-Lg tratada com Cys (não polimerizada com TG). A desnaturação pelo agente redutor Cys e a polimerização por TG em ambas as condições estudadas mostraram ser métodos efetivos no aumento da digestibilidade da ß-Lg. Por sua vez, a combinação destes métodos com a digestão por enzimas gastrintestinais levou à redução da antigenicidade da proteína, já que os peptídeos gerados apresentaram potencial antigênico baixo / Abstract: The ß-Lactoglubulin (ß-Lg) is one of the most antigenic proteins present in the bovine milk. Physical, chemical or enzymatic treatments can alter the antigenicity of this protein. In previous study, it was shown that the antigenic potential of ß-Lg is reduced when polymerized by transglutaminase (TG) in the presence of cysteine (Cys). However, the effect of polymerization on the nutritional properties of ß-Lg is still unknown. The present study aimed to evaluate the effect of the polymerization reaction catalyzed by TG on the in vitro digestibility and the antigenic activity of ß- Lg, before and after simulate digestion with gastrointestinal enzymes. The in vitro digestibility of the ß-Lg treated with TG (0, 10 or 25 U g-1), after heat treatment or in the presence of reducing agents Cys (0, 0.1 and 0.25 mol L-1) or dithiothreitol (DTT 0.02 mol L-1), was evaluated using the gastrointestinal enzymes, pepsin and pancreatin. The samples, before and after in vitro digestion, were characterized by SDS-PAGE, SDS-PAGE/tricine and reversed-phase high performance liquid chromatography (RP-HPLC). Subsequently, the samples were evaluated for antigenicity, except those prepared in the presence of DTT, by immunochemical methods (Immnoblotting), using sera from BALB/c mice sensitized with native ß-Lg (ß-Lg N) or ß-Lg polymerized with 25 U of TG g-1 in the presence of 0.25 mol L-1 of Cys (ß-Lg 0.25Cys 25TG). The formation of polymers with molar mass equal to or above 97.4 kDa was observed with the addition of TG, especially in the presence of reducing agents, reaching approximately 96% of polymerization in the presence of DTT and 91% in the presence of Cys. The in vitro digestibility of native ß-Lg was 53.6% and the all treatments performed increased the digestibility of protein up to 79%. The highest values of digestibility were obtained in the presence of reducing agents. The polymerization also had a positive effect on the digestibility, especially for those samples polymerized in the presence of Cys or DTT, with values above 75%. Analysis by immunoblotting showed that the polymerization of ß-Lg in the presence of 0.25 mol L-1 Cys, reduced the recognition of ß-Lg specific IgE present in the sera of animals sensitized with ß-Lg N or ß-Lg 0.25 Cys 25TG. After digestion with pepsin and pancreatin, the samples polymerized after heat treatment or in the presence of Cys showed reduced antigenicity. The digest of the samples treated with Cys (not treated with TG) was not recognized as antigens. The denaturation by Cys and polymerization by TG in both conditions were effective in increasing the digestibility of ß-Lg. In turn, the combination of these methods with digestion by gastrointestinal enzymes led to reduction of antigenicity of the protein and that peptides generated showed low antigenic potential / Mestrado / Nutrição Experimental e Aplicada à Tecnologia de Alimentos / Mestre em Alimentos e Nutrição

The amount of knowledge increases rapidly due to the increasing number of available data sources. However, the autonomy of data sources and the resulting heterogeneity prevent comprehensive data analysis and applications. Data integration aims to overcome heterogeneity by unifying different data sources and enriching unstructured data. The enrichment of data consists of different subtasks, amongst other the annotation process. The annotation process links document phrases to terms of a standardized vocabulary. Annotated documents enable effective retrieval methods, comparability of different documents, and comprehensive data analysis, such as finding adversarial drug effects based on patient data. A vocabulary allows the comparability using standardized terms. An ontology can also represent a vocabulary, whereas concepts, relationships, and logical constraints additionally define an ontology. The annotation process is applicable in different domains. Nevertheless, there is a difference between generic and specialized domains according to the annotation process. This thesis emphasizes the differences between the domains and addresses the identified challenges. The majority of annotation approaches focuses on the evaluation of general domains, such as Wikipedia. This thesis evaluates the developed annotation approaches with case report forms that are medical documents for examining clinical trials. The natural language provides different challenges, such as similar meanings using different phrases. The proposed annotation method, AnnoMap, considers the fuzziness of natural language. A further challenge is the reuse of verified annotations. Existing annotations represent knowledge that can be reused for further annotation processes. AnnoMap consists of a reuse strategy that utilizes verified annotations to link new documents to appropriate concepts. Due to the broad spectrum of areas in the biomedical domain, different tools exist. The tools perform differently regarding a particular domain. This thesis proposes a combination approach to unify results from different tools. The method utilizes existing tool results to build a classification model that can classify new annotations as correct or incorrect. The results show that the reuse and the machine learning-based combination improve the annotation quality compared to existing approaches focussing on the biomedical domain. A further part of data integration is entity resolution to build unified knowledge bases from different data sources. A data source consists of a set of records characterized by attributes. The goal of entity resolution is to identify records representing the same real-world entity. Many methods focus on linking data sources consisting of records being characterized by attributes. Nevertheless, only a few methods can handle graph-structured knowledge bases or consider temporal aspects. The temporal aspects are essential to identify the same entities over different time intervals since these aspects underlie certain conditions. Moreover, records can be related to other records so that a small graph structure exists for each record. These small graphs can be linked to each other if they represent the same. This thesis proposes an entity resolution approach for census data consisting of person records for different time intervals. The approach also considers the graph structure of persons given by family relationships. For achieving qualitative results, current methods apply machine-learning techniques to classify record pairs as the same entity. The classification task used a model that is generated by training data. In this case, the training data is a set of record pairs that are labeled as a duplicate or not. Nevertheless, the generation of training data is a time-consuming task so that active learning techniques are relevant for reducing the number of training examples. The entity resolution method for temporal graph-structured data shows an improvement compared to previous collective entity resolution approaches. The developed active learning approach achieves comparable results to supervised learning methods and outperforms other limited budget active learning methods. Besides the entity resolution approach, the thesis introduces the concept of evolution operators for communities. These operators can express the dynamics of communities and individuals. For instance, we can formulate that two communities merged or split over time. Moreover, the operators allow observing the history of individuals. Overall, the presented annotation approaches generate qualitative annotations for medical forms. The annotations enable comprehensive analysis across different data sources as well as accurate queries. The proposed entity resolution approaches improve existing ones so that they contribute to the generation of qualitative knowledge graphs and data analysis tasks.

Publicly editable knowledge bases such as Wikipedia and Wikidata have over the years grown tremendously in size. Despite the quick growth, they can never be fully complete due to the continuous stream of events happening in the world. In the task of Entity Linking, it is attempted to link mentions of objects in a document to its respective corresponding entries in a knowledge base. However, due to the incompleteness of knowledge bases, new or emerging entities cannot be linked. Attempts to solve this issue have created the field referred to as Emerging Entities. Recent state-of-the-art work has addressed the issue with promising results in English. In this thesis, the previous work is examined by evaluating its method in the context of a much smaller language; Swedish. The results reveal an expected drop in overall performance although remaining relative competitiveness. This indicates that the method is a feasible approach to the problem of Emerging Entities even for much less used languages. Due to limitations in the scope of the related work, this thesis also suggests a method for evaluating the accuracy of how the Emerging Entities are modeled in a knowledge base. The study also provides a comprehensive look into the landscape of Emerging Entities and suggests further improvements.

The study responds to the increasing effect that climate change has on earth and society. In a global context of rapid urbanization and population growth the project aims to establish the role that architecture can play in the mitigation of climate change. It addresses the embodied energy and carbon footprint of architecture in an urban context. The architectural building type that will be investigated is a transport interchange, specifically the BRT terminal at Pretoria Main Station and associated prototypical BRT stations. An architectural response that promotes public transport use will be investigated. The proposed transport interchange will act as a seam to linking Salvokop with the city, while linking the whole of Tshwane. The architectural intervention will use strategies to respond to predicted climate changes for Tshwane, and adopt strategies to mitigate it. Architectural technologies will be investigated to ensure that the structure has a low carbon footprint and low embodied energy. Through energy conscious design strategies the energy use of the structure will be kept to a minimum. The design will also address the social and historical context of the Pretoria Main Station, to ensure a coherent transport interchange that integrates all modes of transport. The design will contribute to the historical character of the site with an ecosystemic layered approach, adding new functions and layers to the existing, to ensure its adaptability and sustainability. This study forms the part of a departmental research study through the department of Architecture at Pretoria University - “Environmental potential” and the United Nations Development Programme [UNDP] and Global Environment Facility [GEF]. It aims to comply with the prerequisites for an M[Prof]Arch degree while achieving the goals and objectives set by the research study. / Dissertation (MArch(Prof))--University of Pretoria, 2010. / Architecture / unrestricted

The current paper is aimed at providing an overview of the current state of research regarding the potential of linking series of crimes to single offenders through repeated modus operandi behaviors. A systematic literature review was conducted to document findings from previous evaluation research as to the predictive accuracy of crime linkage specific to residential burglary. The findings indicate that predictions of linked burglaries can be made with moderate to high predictive accuracy. In order to get an understanding of the extent to which residential burglary offenders repeat their crime scene behaviors, the findings are discussed in relation to the criminological theories Routine activities theory and the Rational Choice perspective. Future research is suggested.

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Cellulose nanofibrils are a biobased and renewable material with potential to be used in many different applications. Such applications include air filtration, absorption of liquids, and thermal insulation.  To be used for these applications the cellulose nanofibrils must form a porous and dry material. However, maintaining some degree of porosity after drying is difficult, since the fibrils are extracted in liquid and tend to collapse into a dense material upon drying. Certain methods have proven effective for making a dry porous material from cellulose nanofibrils, but these are often expensive and not suitable for large scale production. The aim of this project is to test possible methods for making a highly porous cellulose nanofibril-based material. These methods must be environmentally sustainable and suitable for large scale production. An extensive screening has been conducted with the aim of identifying methods resulting in materials with high porosity. The obtained materials have been analysed further to give a more thorough understanding of the porosity as well as other characteristics. The results indicate that cross-links in the material strengthen the structure, and that drying samples from water always results in complete collapse or very dense materials while drying samples from certain solvents other than water results in more porous materials. The analysed materials had very different porosities, some of which were relatively high. The most porous material analysed by Brunauer-Emmett-Teller gas adsorption had a surface area of 9.5 m2/g. This project gives insight into how cross-linking chemistries and treatment with different solvents and pH affect the resulting cellulose nanofibril-based material, as well as knowledge about which methods can be used to successfully produce dry porous cellulose nanofibril-based materials.

京都大学 / 新制・課程博士 / 博士(経済学) / 甲第23448号 / 経博第646号 / 新制||経||299(附属図書館) / 京都大学大学院経済学研究科経済学専攻 / (主査)教授 諸富 徹, 教授 岡 敏弘, 准教授 長谷川 誠, 特定准教授 Rudolph Sven / 学位規則第4条第1項該当 / Doctor of Economics / Kyoto University / DFAM

This thesis explores approaches for extracting company mentions from financial newsarticles that carry a central role in the news. The thesis introduces the task of salient named entity extraction (SNEE): extract all salient named entity mentions in a text document. Moreover, a neural sequence labeling approach is explored to address the SNEE task in an end-to-end fashion, both using a single-task and a multi-task learning setup. In order to train the models, a new procedure for automatically creating SNEE annotations for an existing news article corpus is explored. The neural sequence labeling approaches are compared against a two-stage approach utilizing NLP parsers, a knowledge base and a salience classifier. Textual features inspired from related work in salient entity detection are evaluated to determine what combination of features results in the highest performance on the SNEE task when used by a salience classifier. The experiments show that the difference in performance between the two-stage approach and the best performing sequence labeling approach is marginal, demonstrating the potential of the end-to-end sequence labeling approach on the SNEE task.