Objetivo: avaliar a percepção da dor na fibromialgia por meio de técnica metodológica quantitativa e qualitativa. Métodos: 30 clientes foram avaliadas por meio de uma entrevista analisada através de análise de conteúdo temática e do Instrumento de Descritores de Dor, sendo que para os dados resultantes foram calculados a média aritmética e o desvio padrão para determinar quais descritores caracterizam melhor a dor na fibromialgia. Resultados e discussão: a análise de conteúdo resultou na construção de categorias de análise referentes às percepções de: diagnóstico, motivações, doença, sentimentos, pensamentos e repercussões na qualidade de vida. Já o Instrumento de Descritores de Dor revelou que os descritores de maior atribuição na caracterização da dor foram incômoda, que espalha, latejante, desconfortável e persistente e os de menor atribuição foram desgraçada, demoníaca, maldita, aterrorizante e assustadora. Os dois instrumentos mostraram tendência das clientes em perceber e relatar a dor, principalmente relacionada às características sensorialdiscriminativas. Além disso apresentaram dados relativos à importância do papel da família e do profissional de saúde no manejo da dor. Conclusão: percebeu-se a necessidade de estimular a percepção e a expressão das clientes com relação à dor, abarcando sua multidimensionalidade e que, o manejo da dor deve ser realizado levando-se em conta a tríade equipe de saúde - cliente - família, face à complexidade do fenômeno. / Objective: Evaluate the perception of pain in the fibromyalgia through the quantitative and qualitative methodological technique. Method: A total of 30 clients were assessed through an interview analyzed by the thematic content and through the instrument Descriptors of Pain. Arithmetic mean and standard error were used to determine which descriptors better characterize the pain in the fibromyalgia. Results and Discussion: The result of the content analysis was the construction of categories of analysis regarding the perceptions of: diagnosis, motivation, disease, feelings, thoughts and repercussions on the quality of life. The Descriptors of Pain instrument revealed the descriptors of higher attribution in the characterization of pain were inconvenient, spreading, pulsating, uncomfortable and persistent and the descriptors with the lower attribution were miserable, demoniac, cursed, terrifying and frightening. The two instruments showed the clients\' tendency in perceiving and reporting the pain regarding to the sensorialdiscriminating characteristics. In addition, data related to the importance of the family\'s and the health professional\'s roles in managing the pain were presented. Conclusion: The need to stimulate the perception and expression of clients regarding the pain in its multidimensionality was perceived. It is concluded that the management of pain must be performed considering the complexity of the phenomenon in terms of the triad health team - client - family.

Made available in DSpace on 2014-06-11T19:27:17Z (GMT). No. of bitstreams: 0 Previous issue date: 2009-02-20Bitstream added on 2014-06-13T18:31:13Z : No. of bitstreams: 1 lima_rca_me_jabo.pdf: 1373391 bytes, checksum: 1e1c91f96fd297aab3526cf5a0942f66 (MD5) / Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) / A Caatinga é um bioma exclusivamente brasileiro que, até pouco tempo, era considerado pobre em biodiversidade. O cachorro-do-mato Cerdocyon thous (Linnaeus, 1766) é um canídeo de porte médio com distribuição em quase todo território brasileiro, sendo o único canídeo com ocorrência registrada no semi-árido Nordestino. O presente estudo teve como objetivos identificar a helmintofauna de Cerdocyon thous provenientes da Caatinga do estado da Paraíba e determinar os indicadores ecológicos de infecção helmíntica, na contribuição favorável para o conhecimento da biodiversidade deste bioma ainda pouco conhecido. Para tal, foram utilizados 58 animais encontrados atropelados em rodovias localizadas nas proximidades do município de Patos, dos quais foram colhidos os helmintos gastrintestinais. Todas os animais estudados estavam parasitados por helmintos. Foram identificados 16 espécies de helmintos, sendo dois trematódeos, um cestódeo, um acantocéfalo e 12 nematódeos. Neste estudo, uma nova espécie denominada Pterygodermatites pluripectinata n. sp. foi descrita, além da descrição de novos registros de hospedeiro e localidade. / The ‘Caatinga’ is a biome exclusive to Brazil, and which was, until very recently, cosidered to be poor in biodiversity. The native dog, Cerdocyon thous (Linnaeus, 1766), is a medium sized canine which is found in almost every region of Brazil. It is the only the only registered canine species to be found in the semi-arid Northeastern region of the country. This study has as its objectives the identification of the helminthfauna common to the Cerdocyon thous found in the Caatinga of the state of Paraiba and to determine the ecological indications of helminthic infection. It is hoped that this will make a favourable addition to the understanding of this little known biome. In this study there were used 58 animals that were found as ‘road-kill’ on the highways in the municipality of Patos. From these 58 animals the gastroinestinal helminths were colected. All the animals used were found to be infected with helminths. 16 species of helminths were identified. Two being Trematodes, one being a cestode, one being an acantocefalum, and the remaining twelve being nematodes. In this study a new species, Pterygodermatites pluripectinata n. sp. was discoveredand its host and location described.

Orientador: Hélio Pedrini / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Computação / Made available in DSpace on 2018-08-19T11:40:39Z (GMT). No. of bitstreams: 1 Rezio_AnaCarolinaCorreia_M.pdf: 2407538 bytes, checksum: cbf48e9214024f2478edcaa47e002852 (MD5) Previous issue date: 2011 / Resumo: Atualmente, há uma crescente demanda por imagens de alta resolução em diversos domínios de conhecimento, como sensoriamento remoto, medicina, automação industrial, microscopia, entre outros. Imagens de alta resolução fornecem detalhes que são importantes para as tarefas de análise e visualização dos dados presentes nas imagens. Entretanto, devido ainda ao custo elevado dos sensores de alta precisão e às limitações existentes para redução do tamanho dos pixels das imagens encontradas no próprio sensor, as imagens de alta resolução têm sido adquiridas a partir de métodos de super-resolução. Este trabalho propõe um método para super-resolver uma imagem ou uma sequência de imagens a partir da compensação residual aprendida pelas características extraídas na imagem residual e no conjunto de treinamento. Resultados experimentais mostram que, na maioria casos, o método proposto provê menores erros quando comparado com outras abordagens do estado da arte. Medidas quantitativas e qualitativas são utilizadas na comparação dos resultados obtidos com as técnicas de super-resolução consideradas nos experimentos / Abstract: There is currently a growing demand for high-resolution images in several domains of knowledge, such as remote sensing, medicine, industrial automation, microscopy, among others. High resolution images provide details that are important to tasks of analysis and visualization of data present in the images. However, due to the cost of high precision sensors and the limitations that exist for reducing the size of the image pixels in the sensor itself, high-resolution images have been acquired from super-resolution methods This work proposes a method for super-resolving an image or a sequence of images from the compensation residual learned by the features extracted in the residual image and the training set. The results are compared with some methods available in the literature. Quantitative and qualitative measures are used to compare the results obtained with the super-resolution techniques considered in the experiments / Mestrado / Ciência da Computação / Mestre em Ciência da Computação

Les descripteurs ISIDA enrichis par propriété ont été introduit pour encoder les structures moléculaires en chémoinformatique en tant que nombre d’occurrence de sous-graphes moléculaires spécifiques dont les sommets représentant les atomes sont colorés par des propriétés locales tel que les pharmacophores dépendant du pH, les identifiants de champs de force, les charges partielles, les incréments LogP ou les propriétés extraites d’un modèle QSAR. Ces descripteurs, par leurs large choix d’option, permettent à l’utilisateur de les adapter au problème à modéliser. Ils ont été utilisés avec succès dans une étude de criblage virtuel sur des inhibiteurs de protéases et plusieurs modèles QSAR sur le coefficient de partage octanol-eau, l’index d’hydrophobicité chromatographique, l’inhibition du canal hERG, la constante de dissociation acide, la force des accepteurs de liaison hydrogène et l’affinité de liaison des GPCR. / ISIDA property-enriched fragment descriptors were introduced as a general framework to numerically encode molecular structures in chemoinformatics, as counts of specific subgraphs in which atom vertices are coloured with respect to a local property - notably pH-dependent pharmacophore, force field, partial charges, logP increments and QSAR model extracted properties. The descriptors leave the user a vast choice in terms of the level of resolution at which chemical information is extracted into the descriptors to adapt them to the problem. They were successfully tested in neighbourhood behaviour and QSAR modelling challenges, with very promising results. They showed excellent results in similarity-based virtual screening for analogue protease inhibitors, and generated highly predictive octanol-water partition coefficient, chromatographic hydrophobicity index, hERG channel inhibition, acidic dissociation constant, hydrogen-bond acceptor strength and GPCR binding affinity models.

Abstract Image appearance descriptors are needed for different computer vision applications dealing with, for example, detection, recognition and classification of objects, textures, humans, etc. Typically, such descriptors should be discriminative to allow for making the distinction between different classes, yet still robust to intra-class variations due to imaging conditions, natural changes in appearance, noise, and other factors. The purpose of this thesis is the development and analysis of photometric descriptors for the appearance of real life images. The two application areas included in this thesis are face recognition and texture classification. To facilitate the development and analysis of descriptors, a general framework for image description using statistics of quantized filter bank responses modeling their joint distribution is introduced. Several texture and other image appearance descriptors, including the local binary pattern operator, can be presented using this model. This framework, within which the thesis is presented, enables experimental evaluation of the significance of each of the components of this three-part chain forming a descriptor from an input image. The main contribution of this thesis is a face representation method using distributions of local binary patterns computed in local rectangular regions. An important factor of this contribution is to view feature extraction from a face image as a texture description problem. This representation is further developed into a more precise model by estimating local distributions based on kernel density estimation. Furthermore, a face recognition method tolerant to image blur using local phase quantization is presented. The thesis presents three new approaches and extensions to texture analysis using quantized filter bank responses. The first two aim at increasing the robustness of the quantization process. The soft local binary pattern operator accomplishes this by making a soft quantization to several labels, whereas Bayesian local binary patterns make use of a prior distribution of labelings, and aim for the one maximizing the a posteriori probability. Third, a novel method for computing rotation invariant statistics from histograms of local binary pattern labels using the discrete Fourier transform is introduced. All the presented methods have been experimentally validated using publicly available image datasets and the results of experiments are presented in the thesis. The face description approach proposed in this thesis has been validated in several external studies, and it has been utilized and further developed by several research groups working on face analysis.

Orientadores: Hélio Pedrini, William Robson Schwartz / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Computação / Made available in DSpace on 2018-08-24T04:06:04Z (GMT). No. of bitstreams: 1 Siqueira_FernandoRobertide_M.pdf: 20841189 bytes, checksum: 62053b7b36d54bbdccc8b5aa3650fe6a (MD5) Previous issue date: 2013 / Resumo: Visão computacional e processamento de imagens desempenham um papel importante em diversas áreas, incluindo detecção de objetos e classificação de imagens, tarefas muito importantes para aplicações em imagens médicas, sensoriamento remoto, análise forense, detecção de pele, entre outras. Estas tarefas dependem fortemente de informação visual extraída de imagens que possa ser utilizada para descrevê-las eficientemente. Textura é uma das principais propriedades usadas para descrever informação tal como distribuição espacial, brilho e arranjos estruturais de superfícies. Para reconhecimento e classificação de imagens, um grande grupo de descritores de textura foi investigado neste trabalho, sendo que apenas parte deles é realmente multiescala. Matrizes de coocorrência em níveis de cinza (GLCM) são amplamente utilizadas na literatura e bem conhecidas como um descritor de textura efetivo. No entanto, este descritor apenas discrimina informação em uma única escala, isto é, a imagem original. Escalas podem oferecer informações importantes em análise de imagens, pois textura pode ser percebida por meio de diferentes padrões em diferentes escalas. Dessa forma, duas estratégias diferentes para estender a matriz de coocorrência para múltiplas escalas são apresentadas: (i) uma representação de escala-espaço Gaussiana, construída pela suavização da imagem por um filtro passa-baixa e (ii) uma pirâmide de imagens, que é definida pelo amostragem de imagens em espaço e escala. Este descritor de textura é comparado com outros descritores em diferentes bases de dados. O descritor de textura proposto e então aplicado em um contexto de detecção de pele, como forma de melhorar a acurácia do processo de detecção. Resultados experimentais demonstram que a extensão multiescala da matriz de coocorrência exibe melhora considerável nas bases de dados testadas, exibindo resultados superiores em relação a diversos outros descritores, incluindo a versão original da matriz de coocorrência em escala única / Abstract: Computer vision and image processing techniques play an important role in several fields, including object detection and image classification, which are very important tasks with applications in medical imagery, remote sensing, forensic analysis, skin detection, among others. These tasks strongly depend on visual information extracted from images that can be used to describe them efficiently. Texture is one of the main used characteristics that describes information such as spatial distribution, brightness and surface structural arrangements. For image recognition and classification, a large set of texture descriptors was investigated in this work, such that only a small fraction is actually multi-scale. Gray level co-occurrence matrices (GLCM) have been widely used in the literature and are known to be an effective texture descriptor. However, such descriptor only discriminates information on a unique scale, that is, the original image. Scales can offer important information in image analysis, since texture can be perceived as different patterns at distinct scales. For that matter, two different strategies for extending the GLCM to multiple scales are presented: (i) a Gaussian scale-space representation, constructed by smoothing the image with a low-pass filter and (ii) an image pyramid, which is defined by sampling the image both in space and scale. This texture descriptor is evaluated against others in different data sets. Then, the proposed texture descriptor is applied in skin detection context, as a mean of improving the accuracy of the detection process. Experimental results demonstrated that the GLCM multi-scale extension has remarkable improvements on tested data sets, outperforming many other feature descriptors, including the original GLCM / Mestrado / Ciência da Computação / Mestre em Ciência da Computação

Research has shown that when individuals are in situations that do not occasion one form of motoric responding, they will engage in another so that the overall level of motoric responding is homeostatic. The purpose of this study was to test whether students would substitute task-related behaviors for stereotypic or other challenging behaviors when the opportunity for active responding did or did not match the level of motoric responding in a free-operant baseline. Four students with mental retardation participated. Results showed that they did substitute behaviors, with stereotypic and other challenging behaviors occurring 1.5-14 times as much in the Non-matched condition for the four students. Further analysis showed considerably more of these behaviors in passive than in active tasks (by a factor up to 21 times as much). Results were discussed in terms of homeostasis, functional assessment, and opportunities to improve educational behaviors.

Yes / Literature solubilities and NMR and IR studies have been used to obtain properties or descriptors of edaravone. These show that edaravone has a significant hydrogen bond acidity so that it must exist in solution partly as the OH and NH forms, as found by Freyer et al. Descriptors have been assigned to the keto form which has a low hydrogen bond acidity, and which is the dominant form in nonpolar solvents. Physicochemical properties of the keto form can be been calculated such as solubilities in nonpolar solvents, partition coefficients from water to nonpolar solvents, and partition coefficients from air to biological phases.

Hydrogen Sulfide (H2S), is a negative off aroma produced during yeast fermentation and is common in cider and leads to consumer rejection. H2S has a very low odor detection threshold (ODT) and is often described as "rotten egg". H2S is produced when juice is deficient in yeast nutrients, such as amino acids and yeast assimilable nitrogen (YAN), which is a common problem in apples since they naturally low in nutrients. The purpose of this research was to investigate the effects of yeast nutrient addition to cider fermentation by adding four different nitrogen-rich supplements and evaluating the effects on H2S production, fermentation kinetics, and aroma quality during cider. Three yeast strains (M2, EC1118 and ICV OKAY), four yeast nutrients (Fermaid K, Fermaid O, Experimental Nutrient, and DAP) and single addition versus split addition of nutrient were tested. For single addition, all nutrient was added pre-fermentation and for split additions, the first addition was pre-fermentation and the second at one-third total soluble solid (TTS) depletion as measured by °Brix. Sensory evaluation was conducted on selected treatments. The greatest H2S was produced by M2 yeast strain (525 .63 ± 53.31 µg mL-1) while the least H2S on average was produced by EC1118 (118.26 ± 26.33 µg mL-1) and ICV OKAY produced an intermediate amount of H2S (209.26 ± 31.63 µg mL-1). Significant differences were observed between treatments and total H2S production within yeast strains. Yeast strain had the largest effect on H2S production. The second largest effect was yeast nutrient type. Classical text analysis of descriptions of cider aroma were evaluated and 25 attributes were chosen to describe the ciders. Check- all-that-apply (CATA), a rapid sensory technique that askes panelists, revealed that there was no clear pattern between variables tested. This work demonstrates that yeast nutrient type and yeast strain affect H2S production during cider fermentation. These findings provide a basis for improving the effectiveness of strategies used to prevent H2S production in cider fermentation. / Master of Science in Life Sciences / Cider, an alcoholic beverage made from fermenting apple juice, has grown in popularity and production in the United States in recent years. With increased in production and sales there is increase demand for high quality cider, but cider is prone to sensory faults. A common fault in cider aroma includes negative off aromas know as volatile sulfur compounds (VSCs). These aromas are often described as "rotten eggs", or "cabbage" and lead to consumer rejection of the product. One of the most recognized VSCs is hydrogen sulfide (H2S) which has a characteristic smell of "rotten eggs". These negative off aromas are thought to be produced during yeast fermentation under nutrient lacking conditions. Apples, depending on cultivar, ripeness, and other factors, naturally lack yeast assimilable nitrogen, vitamins, amino acids, and other nutrients needed for a successful yeast fermentation leading to off aromas. Yeast nutrients can be added to apple juice to increase nutrient availability, but little research has been focused on nutrient addition and timing of additions to prevent H2S production in cider. Most research focused on H2S production has been studied in wine must or grape juice. This knowledge may be limited when applying practices to apple juice due to differences in juice chemistry. Providing cider makers with specific scientific strategies to prevent off aromas, such as H2S, is important to the continued growth of the cider industry. This research is focused on exploring aroma quality and H2S prevention strategies in cider by evaluating how yeast nutrient addition via four exogenous nitrogen rich yeast nutrient and timing of yeast nutrient addition affect H2S production, fermentation kinetics, and consumer perception of aroma in cider fermentation.

No description available.