807 resultados para Vetores
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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A Erliquiose é uma doença zoonótica causada por bactérias gram-negativas e intracelulares obrigatórias. A Anaplasmose Granulocítica Equina - AGE (anteriormente denominada Erliquiose Granulocítica Equina, EGE) é uma enfermidade sazonal, normalmente auto-limitante em equinos. No Brasil, existem poucos relatos deste agente erliquial, bem como de seus vetores naturais. Atualmente, veterinários têm levantado a suspeita de casos de AGE em equinos com sinais clínicos sugestivos de erliquiose e não responsivos ao tratamento para a piroplasmose equina. O objetivo do presente estudo foi identificar equinos expostos a A. phagocytophilum por meio de técnicas sorológicas e moleculares. Vinte amostras de sangue e soro de equinos da região Centro-oeste do Brasil foram avaliados por meio do exame microscópico de capa leucocitária, ensaio imunoenzimático indireto (ELISA), reação de imunofluorescência indireta (RIFI) e reação em cadeia da polimerase (nested PCR). Adicionalmente, o diagnóstico sorológico de Theileria equi pela RIFI e ELISA foram realizados, assim como o diagnóstico molecular pelo nPCR. Treze (65%) amostras de soro foram positivas para A. phagocytophilum pelo teste de ELISA, entretanto nenhum equino foi positivo pelo exame microscópico da capa leucocitária ou nPCR. Anticorpos IgG anti-T. equi foram detectados em 18 (90%) e 17 (85%) equinos pela RIFI e ELISA, respectivamente e o agente foi detectado em 9 (45%) animais pelo nPCR. Estes dados sugerem importante informação para o entendimento da ocorrência da AGE e piroplasmose equina no Centro-oeste do Brasil.
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The skin cancer is the most common of all cancers and the increase of its incidence must, in part, caused by the behavior of the people in relation to the exposition to the sun. In Brazil, the non-melanoma skin cancer is the most incident in the majority of the regions. The dermatoscopy and videodermatoscopy are the main types of examinations for the diagnosis of dermatological illnesses of the skin. The field that involves the use of computational tools to help or follow medical diagnosis in dermatological injuries is seen as very recent. Some methods had been proposed for automatic classification of pathology of the skin using images. The present work has the objective to present a new intelligent methodology for analysis and classification of skin cancer images, based on the techniques of digital processing of images for extraction of color characteristics, forms and texture, using Wavelet Packet Transform (WPT) and learning techniques called Support Vector Machine (SVM). The Wavelet Packet Transform is applied for extraction of texture characteristics in the images. The WPT consists of a set of base functions that represents the image in different bands of frequency, each one with distinct resolutions corresponding to each scale. Moreover, the characteristics of color of the injury are also computed that are dependants of a visual context, influenced for the existing colors in its surround, and the attributes of form through the Fourier describers. The Support Vector Machine is used for the classification task, which is based on the minimization principles of the structural risk, coming from the statistical learning theory. The SVM has the objective to construct optimum hyperplanes that represent the separation between classes. The generated hyperplane is determined by a subset of the classes, called support vectors. For the used database in this work, the results had revealed a good performance getting a global rightness of 92,73% for melanoma, and 86% for non-melanoma and benign injuries. The extracted describers and the SVM classifier became a method capable to recognize and to classify the analyzed skin injuries
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The human voice is an important communication tool and any disorder of the voice can have profound implications for social and professional life of an individual. Techniques of digital signal processing have been used by acoustic analysis of vocal disorders caused by pathologies in the larynx, due to its simplicity and noninvasive nature. This work deals with the acoustic analysis of voice signals affected by pathologies in the larynx, specifically, edema, and nodules on the vocal folds. The purpose of this work is to develop a classification system of voices to help pre-diagnosis of pathologies in the larynx, as well as monitoring pharmacological treatments and after surgery. Linear Prediction Coefficients (LPC), Mel Frequency cepstral coefficients (MFCC) and the coefficients obtained through the Wavelet Packet Transform (WPT) are applied to extract relevant characteristics of the voice signal. For the classification task is used the Support Vector Machine (SVM), which aims to build optimal hyperplanes that maximize the margin of separation between the classes involved. The hyperplane generated is determined by the support vectors, which are subsets of points in these classes. According to the database used in this work, the results showed a good performance, with a hit rate of 98.46% for classification of normal and pathological voices in general, and 98.75% in the classification of diseases together: edema and nodules
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With the rapid growth of databases of various types (text, multimedia, etc..), There exist a need to propose methods for ordering, access and retrieve data in a simple and fast way. The images databases, in addition to these needs, require a representation of the images so that the semantic content characteristics are considered. Accordingly, several proposals such as the textual annotations based retrieval has been made. In the annotations approach, the recovery is based on the comparison between the textual description that a user can make of images and descriptions of the images stored in database. Among its drawbacks, it is noted that the textual description is very dependent on the observer, in addition to the computational effort required to describe all the images in database. Another approach is the content based image retrieval - CBIR, where each image is represented by low-level features such as: color, shape, texture, etc. In this sense, the results in the area of CBIR has been very promising. However, the representation of the images semantic by low-level features is an open problem. New algorithms for the extraction of features as well as new methods of indexing have been proposed in the literature. However, these algorithms become increasingly complex. So, doing an analysis, it is natural to ask whether there is a relationship between semantics and low-level features extracted in an image? and if there is a relationship, which descriptors better represent the semantic? which leads us to a new question: how to use descriptors to represent the content of the images?. The work presented in this thesis, proposes a method to analyze the relationship between low-level descriptors and semantics in an attempt to answer the questions before. Still, it was observed that there are three possibilities of indexing images: Using composed characteristic vectors, using parallel and independent index structures (for each descriptor or set of them) and using characteristic vectors sorted in sequential order. Thus, the first two forms have been widely studied and applied in literature, but there were no records of the third way has even been explored. So this thesis also proposes to index using a sequential structure of descriptors and also the order of these descriptors should be based on the relationship that exists between each descriptor and semantics of the users. Finally, the proposed index in this thesis revealed better than the traditional approachs and yet, was showed experimentally that the order in this sequence is important and there is a direct relationship between this order and the relationship of low-level descriptors with the semantics of the users
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One of the most important goals of bioinformatics is the ability to identify genes in uncharacterized DNA sequences on world wide database. Gene expression on prokaryotes initiates when the RNA-polymerase enzyme interacts with DNA regions called promoters. In these regions are located the main regulatory elements of the transcription process. Despite the improvement of in vitro techniques for molecular biology analysis, characterizing and identifying a great number of promoters on a genome is a complex task. Nevertheless, the main drawback is the absence of a large set of promoters to identify conserved patterns among the species. Hence, a in silico method to predict them on any species is a challenge. Improved promoter prediction methods can be one step towards developing more reliable ab initio gene prediction methods. In this work, we present an empirical comparison of Machine Learning (ML) techniques such as Na¨ýve Bayes, Decision Trees, Support Vector Machines and Neural Networks, Voted Perceptron, PART, k-NN and and ensemble approaches (Bagging and Boosting) to the task of predicting Bacillus subtilis. In order to do so, we first built two data set of promoter and nonpromoter sequences for B. subtilis and a hybrid one. In order to evaluate of ML methods a cross-validation procedure is applied. Good results were obtained with methods of ML like SVM and Naïve Bayes using B. subtilis. However, we have not reached good results on hybrid database
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This dissertation presents a new proposal for the Direction of Arrival (DOA) detection problem for more than one signal inciding simultaneously on an antennas array with linear or planar geometry by using intelligent algorithms. The DOA estimator is developed by using techniques of Conventional Beam-forming (CBF), Blind Source Separation (BSS), and the neural estimator MRBF (Modular Structure of Radial Basis Functions). The developed MRBF estimator has its capacity extended due to the interaction with the BSS technique. The BSS makes an estimation of the steering vectors of the multiple plane waves that reach the array in the same frequency, that means, obtains to separate mixed signals without information a priori. The technique developed in this work makes possible to identify the multiple sources directions and to identify and to exclude interference sources
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Nowadays, classifying proteins in structural classes, which concerns the inference of patterns in their 3D conformation, is one of the most important open problems in Molecular Biology. The main reason for this is that the function of a protein is intrinsically related to its spatial conformation. However, such conformations are very difficult to be obtained experimentally in laboratory. Thus, this problem has drawn the attention of many researchers in Bioinformatics. Considering the great difference between the number of protein sequences already known and the number of three-dimensional structures determined experimentally, the demand of automated techniques for structural classification of proteins is very high. In this context, computational tools, especially Machine Learning (ML) techniques, have become essential to deal with this problem. In this work, ML techniques are used in the recognition of protein structural classes: Decision Trees, k-Nearest Neighbor, Naive Bayes, Support Vector Machine and Neural Networks. These methods have been chosen because they represent different paradigms of learning and have been widely used in the Bioinfornmatics literature. Aiming to obtain an improvment in the performance of these techniques (individual classifiers), homogeneous (Bagging and Boosting) and heterogeneous (Voting, Stacking and StackingC) multiclassification systems are used. Moreover, since the protein database used in this work presents the problem of imbalanced classes, artificial techniques for class balance (Undersampling Random, Tomek Links, CNN, NCL and OSS) are used to minimize such a problem. In order to evaluate the ML methods, a cross-validation procedure is applied, where the accuracy of the classifiers is measured using the mean of classification error rate, on independent test sets. These means are compared, two by two, by the hypothesis test aiming to evaluate if there is, statistically, a significant difference between them. With respect to the results obtained with the individual classifiers, Support Vector Machine presented the best accuracy. In terms of the multi-classification systems (homogeneous and heterogeneous), they showed, in general, a superior or similar performance when compared to the one achieved by the individual classifiers used - especially Boosting with Decision Tree and the StackingC with Linear Regression as meta classifier. The Voting method, despite of its simplicity, has shown to be adequate for solving the problem presented in this work. The techniques for class balance, on the other hand, have not produced a significant improvement in the global classification error. Nevertheless, the use of such techniques did improve the classification error for the minority class. In this context, the NCL technique has shown to be more appropriated
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O presente artigo apresenta uma análise do Plano Nacional de Saúde publicado em 2004. Este documento expressa um importante período de transição na gestão do SUS, uma vez que foi predecessor do Pacto pela Saúde. A partir de um estudo descritivo com base em procedimentos quantitativos e qualitativos, o objetivo foi compreender as ideias centrais do documento, identificando as conexões existentes entre seus princípios, objetivos e prioridades. O principal resultado do estudo foi a identificação da integralidade das ações, da capacitação dos recursos humanos e mudança do marco regulatório com base numa visão intersetorial como núcleo central do documento. Essas ideias, por sua vez, circulam pelo discurso das diretrizes do plano, fortalecendo os laços do eixo central do texto na reorganização da atenção ambulatorial e na qualificação profissional. Por fim, quando comparadas metas e ações previstas nas diretrizes, observa-se uma tensão entre o que foram denominados vetores da verticalidade e da horizontalidade, deixando em aberto o rumo do lugar social em disputa.
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A aceitação de 11 amostras de aguardentes de cana envelhecidas e não envelhecidas foi avaliada por testes sensoriais afetivos e análises estatísticas uni e multivariada. As aguardentes estudadas compreenderam seis amostras comerciais de diferentes marcas, (sendo três não envelhecidas e três envelhecidas) e ainda outras cinco amostras correspondentes a zero, 12, 24, 36 e 48 meses de envelhecimento em um tonel de carvalho de 200L. As amostras foram avaliadas por 100 provadores consumidores do produto, recrutados por questionário de avaliação quanto à afetividade. Para os testes afetivos foi utilizada escala hedônica não estruturada de 9cm, sendo os dados obtidos avaliados por dois métodos estatísticos distintos: o Mapa de Preferência Interno (MDPREF) e a análise de variância univariada (ANOVA) com comparação de médias pelo teste de Tukey e análise de correlação. As amostras de aguardente envelhecidas por 12, 36 e 48 meses obtiveram maior aceitação, com médias ao redor de 7,0 na escala hedônica. A amostra com menor aceitação foi a correspondente ao tempo zero de envelhecimento (controle). As demais amostras obtiveram aceitação intermediária. A análise por MDPREF gerou em espaço multidimensional (onde as variações com relação aos dados de preferência foram extraídas em eixos ortogonais e para cada dimensão de preferência), coordenadas relativas aos produtos, que foram geradas em função da resposta dos consumidores. Os dados de aceitação de cada provador foram utilizados para o desenvolvimento de vetores individuais de preferência, resultando na construção de um mapa mutidimensional das amostras, em função dos dados de aceitação. No presente estudo o MDPREF foi gerado pelas primeira e segunda dimensões de preferência, as quais explicaram em conjunto 89,83% das variações observadas entre as amostras com relação à aceitação. O MDPREF confirmou os resultados da ANOVA, indicando uma maior preferência dos provadores pelas amostras de aguardentes envelhecidas. Os resultados sugerem também que aguardentes envelhecidas por mais de 24 meses em tonel de carvalho de 200L são preferidas pelos consumidores, em detrimento das comerciais não envelhecidas e mesmo das comerciais envelhecidas, que podem ser adicionadas de aguardente não envelhecida (processo denominado corte) e também ter correção da cor, conforme permite a Legislação Brasileira. O conteúdo de polifenóis totais e a intensidade de cor também foram determinados, e ambos apresentaram correlação linear positiva significativa (p<=0,05) com o aumento do tempo de envelhecimento das amostras.
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INTRODUÇÃO: Populações de Triatoma sordida Stål, 1859 foram investigadas quanto à suscetibilidade à deltametrina. MÉTODOS: Análise por meio de bioensaios por aplicação tópica em 11 populações de T. sordida procedentes dos Estados de Goiás, Mato Grosso e Mato Grosso do Sul. RESULTADOS: As estimativas de DL50 e RR50 demonstraram elevados níveis de suscetibilidade (DL50 < 1 e RR50 < 2). Entretanto, as análises do coeficiente angular da curva dose resposta revelaram que as populações de triatomíneos dos municípios de Firminópolis/GO, Posse/GO, Poxoréu/MT, Douradina/MS e Aparecida do Taboado/MS apresentam maiores probabilidades de evolução de resistência, portanto, mais propícias a tolerar o tratamento com deltametrina. CONCLUSÕES: Detectaram-se pequenas alterações de suscetibilidade e baixos níveis de resistência, porém as alterações temporais de suscetibilidade deverão ser continuamente monitoradas, a fim de nortear adequadamente as ações de controle dos vetores da DC.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico
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The magnetic order of bylayers composed by a ferromagnetic film (F) coupled with an antiferromagnetic film (AF) is studied. Piles of coupled monolayers describe the films and the interfilm coupling is described by an exchange interaction between the magnetic moments at the interface. The F has a cubic anisotropy while the AF has a uniaxial anisotropy. We analyze the effects of an external do magnetic field applied parallel to the interface. We consider the intralayer coupling is strong enough to keep parallel all moments of the monolayer an then they are described by one vector proportional to the magnetization of the layer. The interlayer coupling is represented by an exchange interaction between these vectors. The magnetic energy of the system is the sum of the exchange. Anisotropy and Zeeman energies and the equilibrium configuration is one that gives the absolute minimum of the total energy. The magnetization of the system is calculated and the influence of the external do field combined with the interfilm coupling and the unidirectional anisotropy is studied. Special attention is given to the region near of the transition fields. The torque equation is used to study dynamical behavior of these systems. We consider small oscillations around the equilibrium position and we negleet nonlinear terms to obtain the natural frequencies of the system. The dependence of the frequencies with the external do field and their behavior in the phase transition region is analized
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Broadly speaking, the concept of gene therapy involves the transfer of a genetic material into a cell, tissue, or organ in order to cure a disease or at least improve the clinical status of a patient. Making it simple, gene therapy consists in the insertion of functional genes into cells containing defective genes by substituting, complementing or inhibiting them. The achievement of a foreigner DNA expression into a population of cells requires its transfer to the target. Therefore, it is a key issue to create systems able to transfer and protect the DNA until it reaches the target, the vectors. The disadvantages related to the use of viral vectors have encouraged efforts to develop emulsions as non-viral vectors. In fact, they are easily produced, present controllable stability and enable transfection. The aim of this work was to develop an emulsion for gene therapy and evaluate its ability to compact nucleic acids by the development of a complex with the plasmid pIRES2-EGFP. The first step was to determine the Hydrophilic Lipophilic Balance (HLB) of the Captex® 355 (oily internal phase of the emulsion) through long and short term stability assays. Based on the results, emulsions composed of Captex® 355, Tween 20® and Span 60® with 10.7 HLB were produced by three different methods: phase inversion, spontaneous emulsification and sonication. The results showed that the lowest diameter and best stability of the emulsions were achieved by the sonication method. The cationic emulsions were made by adding DOTAP to the basic emulsion. Its association with pIRES2-EGFP was evaluated by electrophoresis. Several rates of emulsion and DNA were evaluated and the results showed that 100% of the complex was formed when the rate DOTAP/DNA(nmol/µg) was 130. In conclusion, the overall results show the ability of the proposed emulsion to compact pIRES2-EGFP, which is a requirement to a successful transfection. Therefore, such formulation may be considered a promising candidate for gene therapy
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The development of epidemiological practices in the last years of the nineteenth and early twentieth century was characterized by both an influence of medical geography and the emergence of microbes and vectors of diseases. Both theories were used to explain outbreaks in Rio Grande do Norte specially in Natal. In this process were organized new institutions linked to public health, unhealthy spaces and prescribed hygiene measures. The redefinitions of the spaces were linked to updated elements of Hippocratic medicine such as aerism and emphasis on medical topography. How the physicians of the town were organized in the face of new meanings and fields of expertise in the demarcation of diseases and regulation of their own practices against the illegal medical practitioners? Likewise, the very occurrence of epidemics mobilized people, urban institutions and apparatuses. But how the Hippocratic legacy that leads to the idea of bad air originated by swamps from the eighteenth and nineteenth century has been linked to new microbial assumptions and disease vectors in the early twentieth century? How an invader from Africa, (the mosquito A. gambiae) mobilized transnational efforts to combat malaria and redefined the epidemiological practices? The aim of this work is to understand how epidemiological practices redefine the way we define spaces, practices and disease from both an approach influenced by a relational history of spaces and a theoretical synergy which includes topics in Science Studies, Post Structuralist Geography and some elements of Feminist Studies. Documentary research were surveyed in the reports of the provincial presidents, government posts to the Provincial Assembly, specialized medical articles and theses, and documents from the Rockefeller Foundation and national and international journals. In this regard shall be given to both material and discursive aspects of space-related practical epidemiological that Natal as much (in general) Rio Grande do Norte between bad air and malaria.