925 resultados para Classification of functioning
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Trabalho apresentado no âmbito do Mestrado em Engenharia Informática, como requisito parcial para obtenção do grau de Mestre em Engenharia Informática
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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do grau de Mestre em Engenharia Informática
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For an interval map, the poles of the Artin-Mazur zeta function provide topological invariants which are closely connected to topological entropy. It is known that for a time-periodic nonautonomous dynamical system F with period p, the p-th power [zeta(F) (z)](p) of its zeta function is meromorphic in the unit disk. Unlike in the autonomous case, where the zeta function zeta(f)(z) only has poles in the unit disk, in the p-periodic nonautonomous case [zeta(F)(z)](p) may have zeros. In this paper we introduce the concept of spectral invariants of p-periodic nonautonomous discrete dynamical systems and study the role played by the zeros of [zeta(F)(z)](p) in this context. As we will see, these zeros play an important role in the spectral classification of these systems.
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Thesis presented in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the subject of Electrical and Computer Engineering
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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Conservação e Restauro,Área de especialização Cerâmica e Vidro
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This paper reports a case of cutaneous infection of nontraumatic origin caused by Nocardia asteroides in a hospitalized patient with chronic obstructive pulmonary disease. Diagnosis was established by direct and histological examination, cultures from exudate and biopsy specimen. We discuss the classification of clinical forms of Nocardia infections affecting the skin.
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Dissertação para obtenção do Grau de Mestre em Conservação e Restauro
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INTRODUCTION: HIV positive patients co-infected with HTLV-1 may have an increase in their T CD4+ cell counts, thus rendering this parameter useless as an AIDS-defining event. OBJECTIVE: To study the effects induced by the co-infection of HIV-1 and HTLV-1 upon CD4+ cells. MATERIAL AND METHODS: Since 1997, our group has been following a cohort of HTLV-1-infected patients, in order to study the interaction of HTLV-1 with HIV and/or with hepatitis C virus (HCV), as well as HTLV-1-only infected asymptomatic carriers and those with tropical spastic paraparesis/HTLV-1 associated myelopathy (TSP/HAM). One hundred and fifty HTLV-1-infected subjects have been referred to our clinic at the Institute of Infectious Diseases "Emílio Ribas", São Paulo. Twenty-seven of them were also infected with HIV-1 and HTLV-1-infection using two ELISAs and confirmed and typed by Western Blot (WB) or polymerase chain reaction (PCR). All subjects were evaluated by two neurologists, blinded to the patient's HTLV status, and the TSP/HAM diagnostic was based on the World Health Organization (WHO) classification. AIDS-defining events were in accordance with the Centers for Disease Control (CDC) classification of 1988. The first T CD4+ cells count available before starting anti-retroviral therapy are shown compared to the HIV-1-infected subjects at the moment of AIDS defining event. RESULTS: A total of 27 HIV-1/HTLV-1 co-infected subjects were identified in this cohort; 15 already had AIDS and 12 remained free of AIDS. The median of T CD4+ cell counts was 189 (98-688) cells/mm³ and 89 (53-196) cells/mm³ for co-infected subjects who had an AIDS-defining event, and HIV-only infected individuals, respectively (p = 0.036). Eight of 27 co-infected subjects (30%) were diagnosed as having a TSP/HAM simile diagnosis, and three of them had opportunistic infections but high T CD4+ cell counts at the time of their AIDS- defining event. DISCUSSION: Our results indicate that higher T CD4+ cells count among HIV-1/HTLV-1-coinfected subjects was found in 12% of the patients who presented an AIDS-defining event. These subjects also showed a TSP/HAM simile picture when it was the first manifestation of disease; this incidence is 20 times higher than that for HTLV-1-only infected subjects in endemic areas.
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Quality of life is a concept influenced by social, economic, psychological, spiritual or medical state factors. More specifically, the perceived quality of an individual's daily life is an assessment of their well-being or lack of it. In this context, information technologies may help on the management of services for healthcare of chronic patients such as estimating the patient quality of life and helping the medical staff to take appropriate measures to increase each patient quality of life. This paper describes a Quality of Life estimation system developed using information technologies and the application of data mining algorithms to access the information of clinical data of patients with cancer from Otorhinolaryngology and Head and Neck services of an oncology institution. The system was evaluated with a sample composed of 3013 patients. The results achieved show that there are variables that may be significant predictors for the Quality of Life of the patient: years of smoking (p value 0.049) and size of the tumor (p value < 0.001). In order to assign the variables to the classification of the quality of life the best accuracy was obtained by applying the John Platt's sequential minimal optimization algorithm for training a support vector classifier. In conclusion data mining techniques allow having access to patients additional information helping the physicians to be able to know the quality of life and produce a well-informed clinical decision.
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The method used by YAGYU et al. for the subtype-specific polymerase chain reaction (PCR) amplification of the gp41 transmembrane region of the human immunodeficiency virus type-1 (HIV-1) env gene, was tested. HIV-1 proviral DNA from 100 infected individuals in Itajaí, South Brazil was used to analyze this method. Seventy individuals were determined according to this method as having PCR products at the expected size for subtypes B, C, D and F. Of these individuals, 26 (37.1%) were observed as having the expected amplification for subtype C, and 42 (60%) were observed as having the expected products for subtypes B and D. Of the subtype B and D amplicons, 16 (22.9%) were classified as subtype D, and 26 (37.1%) were classified as subtype B. Two individuals (2.9%) had amplicons that were observed after subtype F-specific amplification was performed. Sequencing and comparing the patient sequences to reference sequences confirmed the classification of sequences of subtypes C and B. However, sequences that were falsely determined as being D and F in the PCR assay were determined as being subtypes C and B, respectively, by sequence analysis. For those individuals from whom no amplified products were obtained, a low viral load that was indicated in their patient history may explain the difficulty in subtyping by PCR methods. This issue was demonstrated by the results of ANOVA when testing the effect of viral load on the success of PCR amplification. The alignment of the obtained sequences with HIV-1 reference sequences demonstrated that there is high intra-subtype diversity. This indicates that the subtype-specific primer binding sites were not conserved or representative of the subtypes that are observed in the Brazilian populations, and that they did not allow the correct classification of HIV-1 subtypes. Therefore, the proposed method by YAGYU et al. is not applicable for the classification of Brazilian HIV-1 subtypes.
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High-content analysis has revolutionized cancer drug discovery by identifying substances that alter the phenotype of a cell, which prevents tumor growth and metastasis. The high-resolution biofluorescence images from assays allow precise quantitative measures enabling the distinction of small molecules of a host cell from a tumor. In this work, we are particularly interested in the application of deep neural networks (DNNs), a cutting-edge machine learning method, to the classification of compounds in chemical mechanisms of action (MOAs). Compound classification has been performed using image-based profiling methods sometimes combined with feature reduction methods such as principal component analysis or factor analysis. In this article, we map the input features of each cell to a particular MOA class without using any treatment-level profiles or feature reduction methods. To the best of our knowledge, this is the first application of DNN in this domain, leveraging single-cell information. Furthermore, we use deep transfer learning (DTL) to alleviate the intensive and computational demanding effort of searching the huge parameter's space of a DNN. Results show that using this approach, we obtain a 30% speedup and a 2% accuracy improvement.
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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.
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The term “mastocytosis” denotes a heterogeneous group of disorders characterised by abnormal growth and accumulation of mast cells (MC) in one or more organ systems. Symptoms result from MC chemical mediator’s release, pathologic infiltration of neoplastic MC in tissues or both. Multiple molecular, genetic and chromosomal defects seem to contribute to an autonomous growth, but somatic c-kit D816V mutation is more frequently encountered, especially in systemic disease. We present a literature review of mastocytosis and a rare case report of an 18 month-old-girl with a bullous dermatosis, respiratory distress and anaphylaxis, as clinical manifestations of mastocytosis. The developments of accepted classification systems and novel useful markers allowed a re-evaluation and updating of the classification of mastocytosis. In paediatric age cutaneous forms of disease prevail and may regress spontaneously. SM is more frequently diagnosed in adults and is a persistent(clonal) disease of bone marrow. The clinical course in these patients is variable.Today diagnostic criteria for each disease variant are reasonably well defined. There are, however, peculiarities, namely in paediatric age, that makes the diagnostic approach difficult. Systemic disease may pose differential diagnostic problems resulting from multiple organ systems involvement. Coversly, the “unexplained” appearance of those symptoms with no skin lesions should raise the suspicion of MC disease. This case is reported in order to stress the clinical severity and difficult diagnostic approach that paediatric mastocytosis may assume.
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The extraction of relevant terms from texts is an extensively researched task in Text- Mining. Relevant terms have been applied in areas such as Information Retrieval or document clustering and classification. However, relevance has a rather fuzzy nature since the classification of some terms as relevant or not relevant is not consensual. For instance, while words such as "president" and "republic" are generally considered relevant by human evaluators, and words like "the" and "or" are not, terms such as "read" and "finish" gather no consensus about their semantic and informativeness. Concepts, on the other hand, have a less fuzzy nature. Therefore, instead of deciding on the relevance of a term during the extraction phase, as most extractors do, I propose to first extract, from texts, what I have called generic concepts (all concepts) and postpone the decision about relevance for downstream applications, accordingly to their needs. For instance, a keyword extractor may assume that the most relevant keywords are the most frequent concepts on the documents. Moreover, most statistical extractors are incapable of extracting single-word and multi-word expressions using the same methodology. These factors led to the development of the ConceptExtractor, a statistical and language-independent methodology which is explained in Part I of this thesis. In Part II, I will show that the automatic extraction of concepts has great applicability. For instance, for the extraction of keywords from documents, using the Tf-Idf metric only on concepts yields better results than using Tf-Idf without concepts, specially for multi-words. In addition, since concepts can be semantically related to other concepts, this allows us to build implicit document descriptors. These applications led to published work. Finally, I will present some work that, although not published yet, is briefly discussed in this document.
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INTRODUCTION: Study of the temporal activity of malaria vectors during the implantation of a hydroelectric power station on the River Paraná, intended to generate electrical energy. The river separates the States of São Paulo and Mato Grosso do Sul, in Brazil. The objective was to verify whether alterations occurred in the wealth and diversity indices of Anopheles, following two successive floods, extended to the temporal activity and nycthemeral rhythm followed over a five year period. METHODS: Mosquito capture was performed monthly using the Human Attraction Technique and Shannon Traps. The first, executed for 24h, provided the nycthemeral rhythm and the second, lasting 15h, permitted the tracking of Anopheles during the two floods. RESULTS: The bimodal pattern of Anopheles darlingi defined before these floods was modified throughout the environment interventions. The same effect had repercussions on the populations of An albitarsis s.l., An triannulatus and An galvaoi. Activity prior to twilight was less affected by the environment alterations. CONCLUSIONS: The dam construction provoked changes in Anopheles temporal activity patterns, permitting classification of the area as an ecologically steady and unstable situation. Differences observed in Anopheles behavior due to the capture methods revealed the influence of solo and multiple attractiveness inside the populations studied.