1000 resultados para D. PZT


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Coronary heart disease (CHDis a common cardiovascular disease in the elderly, is also a typical psychosomatic disease. Personality factors are very important in many psychological factors impacting on the prognosis of patients with CHD. The most influential personality factors to CHD are Type A and Type D personality. The previous research has shown that although Type A personality increased the prevalence of CHD, it cannot predict the development and prognosis after diagnosis. In contradict, Type D personality can predict prognosis. There is still no clinic-based or theory-based answer to the question: Why Type A personality cannot predict the outcome while Type D personality could predict the prognosis independently. The current research conducted a systematic investigation to the above question, which included one comparison study between CHD patients and control group, and four studies on reaction experiment and answered the question: why Type A personality cannot predict whereas Type D personality could effectively predict prognosis of CHD. The findings of the current research were: Type A and Type D personality influence CHD prognosis through different psychological mechanisms: both dimensions of Type D personality have direct influence on social support, whereas neither dimensions of Type A personality related to social support, directly of indirectly. Negative affection component of Type D personality significantly related to anxiety and depression, Social repression significantly related to anxiety but not depression. Both dimensions of Type A personality significantly related to anxiety but not depression. Neither under rest or diaphragmatic breathing conditions, Type A personality had no significant influence on vestibular autonomic reaction among healthy young males. Neither Type A nor Type D personality had significant influence on vestibular autonomic reaction among old CHD patients under rest condition. Type D personality predicted lower sympathetic excitation under rest condition, and lower cardiac vagal tone under diaphragmatic breathing condition among healthy young males. When actively reacted to stimuli (math calculation) under rest condition, Type A personality increased sympathetic excitation among healthy young males. When actively reacted to stimuli (math calculation) under diaphragmatic breathing condition, Type A personality increased cardiac vagal tone among the same group of subjects. When actively reacted to stimuli under neither condition, Type D personality showed no significant influence on vestibular autonomic reaction among young males. When passively reacted to stimuli under neither condition, Type A personality showed no significant influence on vestibular autonomic reaction among young males. When passively stimulated followed rest, Type D personality increased sympathetic excitation and decreased cardiac vagal tone among young males. When passively stimulated followed diaphragmatic breathing, Typed showed no significant influence on vestibular autonomic reaction among young males. The above results indicated that Type A and Type D personalities had different psychological mechanisms to the outcome of CHD treatment: neither dimensions of Type A personality had direct or indirect effects on social support; both dimensions of Type D personality had direct and indirect effects on social support. Negative affection component of Type D personality significantly related to anxiety and depression, Social repression significantly related to anxiety but not depression. Both dimensions of Type A personality significantly related to anxiety but not depression. Social support positively related to the outcome after CHD treatment. The biological mechanisms of Type A and Type B personality to CHD prognosis differed in the following ways: Type A personality increased sympathetic excitation when actively stimulated, but had no influence when passively stimulated among young male subjects. When passively stimulated after rest, Type D personality predicted high sympathetic excitation and low cardiac vagal tone among young males, but not vestibular autonomic reaction among young males. Key words: Type A personality, Type D personality, Coronary Heart Disease (CHD), Prognosis, Psychobiological Mechanisms

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2005

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Divulga os resultados do amplo levantamento agrossocioeconômico realizado em Machadinho d'Oeste, Rondnia, no ano de 2002.

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O Código Florestal brasileiro, juntamente com a resolução Conama no 303/2002, definiu áreas do território nacional classificadas como de preservação permanente (APP). Essas áreas englobam margens dos cursos e corpos d'água, terrenos com declividade acentuada, bordas de chapadas, topos de morro, entre outras feições. No entanto, a escassez de dados cartográficos em escala adequada e de abrangência nacional dificultam ou até impossibilitam as estimativas do alcance territorial da legislação ambiental brasileira. Um exemplo é a delimitação das APPs nas margens dos rios, que, para identificação correta, requer, além da localização, informações sobre a largura dos cursos d'água na época de cheias, dados raramente disponíveis. Este trabalho utilizou dados provenientes da Agência Nacional de Águas (ANA) para estimar as APPs das margens dos rios pertencentes à bacia do Rio Ji-Paraná, RO, identificados na escala 1:1.000.000, levando-se em consideração as larguras dos cursos d'água. Dados de todas as dez estações fluviométricas presentes na bacia com medidas de cota e perfil transversal da calha foram utilizados para estimar a largura máxima do canal de duas maneiras distintas. A primeira delimitou as sub-bacias definidas pelas estações fluviométricas e considerou que todos os cursos d'água pertencentes à sub-bacia apresentavam a mesma largura observada em seu ponto final. A segunda utilizou a relação empírica obtida entre a área de drenagem e a largura da calha nas nove estações para definir a largura de todos os trechos dos cursos d'água da bacia. Por fim, as APPs nas margens dos rios foram delimitadas seguindo os critérios estabelecidos na resolução Conama no 303/2002. A título de comparação, foram também delimitadas as APPs utilizando larguras constantes de 100 m, 200 m e 500 m de faixa marginal para toda a bacia. Entre os diferentes métodos utilizados, a APP nas margens dos rios variou de 1.541 km2 a 15.876 km2 (2,04% a 21,04% da área da bacia, respectivamente). A grande variação na delimitação das áreas marginais deixa claro que estimativas efetuadas para grandes regiões estarão sempre sujeitas a incertezas, de acordo com os métodos utilizados, e que, portanto, é imprescindvel o detalhamento dos procedimentos efetuados para esclarecer as vantagens e limitações a que tais estimativas estão sujeitas.

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We describe a psychophysical investigation of the effects of object complexity and familiarity on the variation of recognition time and recognition accuracy over different views of novel 3D objects. Our findings indicate that with practice the response times for different views become more uniform and the initially orderly dependency of the response time on the distance to a "good" view disappears. One possible interpretation of our results is in terms of a tradeoff between memory needed for storing specific-view representations of objects and time spent in recognizing the objects.

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This thesis examines a complete design framework for a real-time, autonomous system with specialized VLSI hardware for computing 3-D camera motion. In the proposed architecture, the first step is to determine point correspondences between two images. Two processors, a CCD array edge detector and a mixed analog/digital binary block correlator, are proposed for this task. The report is divided into three parts. Part I covers the algorithmic analysis; part II describes the design and test of a 32$\time $32 CCD edge detector fabricated through MOSIS; and part III compares the design of the mixed analog/digital correlator to a fully digital implementation.

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We discuss a strategy for visual recognition by forming groups of salient image features, and then using these groups to index into a data base to find all of the matching groups of model features. We discuss the most space efficient possible method of representing 3-D models for indexing from 2-D data, and show how to account for sensing error when indexing. We also present a convex grouping method that is robust and efficient, both theoretically and in practice. Finally, we combine these modules into a complete recognition system, and test its performance on many real images.

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Techniques, suitable for parallel implementation, for robust 2D model-based object recognition in the presence of sensor error are studied. Models and scene data are represented as local geometric features and robust hypothesis of feature matchings and transformations is considered. Bounds on the error in the image feature geometry are assumed constraining possible matchings and transformations. Transformation sampling is introduced as a simple, robust, polynomial-time, and highly parallel method of searching the space of transformations to hypothesize feature matchings. Key to the approach is that error in image feature measurement is explicitly accounted for. A Connection Machine implementation and experiments on real images are presented.