969 resultados para Computational method


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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

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Canine dirofilariosis is a life-threatening parasitic disease that is increasingly reported worldwide. Once diagnosed the main treatment goals are to improve the animal's clinical condition and to eliminate all life stages of the parasite with minimal posttreatment side effects. This can be achieved through mechanical, surgical, or chemotherapeutical approaches. Currently, manual extraction is the preferred method to remove adult heartworms due to its diminished invasiveness, reduced damage to the vascular endothelium, and shortened anaesthesia duration. However, it remains an expensive technique that can be highly traumatic. To address this issue, a nontraumatic homemade catheter-guided snare was developed for heartworm removal by adapting and folding a 0.014-inch coronary wire (BMW, Abbott Vascular). Transvenous heartworm extraction was performed on a dog severely infected with adult heartworms by inserting the modified snare into a 6-F Judkins right coronary guiding catheter BMW (Cordis) and advancing it into the right ventricle under fluoroscopic guidance. Fifteen adult specimens of Dirofilaria immitis were successfully extracted from the pulmonary artery and right ventricle without complications. To assure the death of both larvae and adults, postoperative treatment was successfully managed using ivermectin, doxycycline, and melarsomine, with no recurrence after surgery.

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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

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Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

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Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

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Dissertation presented to obtain the Ph.D degree in Chemistry.

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Dissertation presented to obtain the Ph.D degree in Biology

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Nowadays, several sensors and mechanisms are available to estimate a mobile robot trajectory and location with respect to its surroundings. Usually absolute positioning mechanisms are the most accurate, but they also are the most expensive ones, and require pre installed equipment in the environment. Therefore, a system capable of measuring its motion and location within the environment (relative positioning) has been a research goal since the beginning of autonomous vehicles. With the increasing of the computational performance, computer vision has become faster and, therefore, became possible to incorporate it in a mobile robot. In visual odometry feature based approaches, the model estimation requires absence of feature association outliers for an accurate motion. Outliers rejection is a delicate process considering there is always a trade-off between speed and reliability of the system. This dissertation proposes an indoor 2D position system using Visual Odometry. The mobile robot has a camera pointed to the ceiling, for image analysis. As requirements, the ceiling and the oor (where the robot moves) must be planes. In the literature, RANSAC is a widely used method for outlier rejection. However, it might be slow in critical circumstances. Therefore, it is proposed a new algorithm that accelerates RANSAC, maintaining its reliability. The algorithm, called FMBF, consists on comparing image texture patterns between pictures, preserving the most similar ones. There are several types of comparisons, with different computational cost and reliability. FMBF manages those comparisons in order to optimize the trade-off between speed and reliability.

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This work is divided into two distinct parts. The first part consists of the study of the metal organic framework UiO-66Zr, where the aim was to determine the force field that best describes the adsorption equilibrium properties of two different gases, methane and carbon dioxide. The other part of the work focuses on the study of the single wall carbon nanotube topology for ethane adsorption; the aim was to simplify as much as possible the solid-fluid force field model to increase the computational efficiency of the Monte Carlo simulations. The choice of both adsorbents relies on their potential use in adsorption processes, such as the capture and storage of carbon dioxide, natural gas storage, separation of components of biogas, and olefin/paraffin separations. The adsorption studies on the two porous materials were performed by molecular simulation using the grand canonical Monte Carlo (μ,V,T) method, over the temperature range of 298-343 K and pressure range 0.06-70 bar. The calibration curves of pressure and density as a function of chemical potential and temperature for the three adsorbates under study, were obtained Monte Carlo simulation in the canonical ensemble (N,V,T); polynomial fit and interpolation of the obtained data allowed to determine the pressure and gas density at any chemical potential. The adsorption equilibria of methane and carbon dioxide in UiO-66Zr were simulated and compared with the experimental data obtained by Jasmina H. Cavka et al. The results show that the best force field for both gases is a chargeless united-atom force field based on the TraPPE model. Using this validated force field it was possible to estimate the isosteric heats of adsorption and the Henry constants. In the Grand-Canonical Monte Carlo simulations of carbon nanotubes, we conclude that the fastest type of run is obtained with a force field that approximates the nanotube as a smooth cylinder; this approximation gives execution times that are 1.6 times faster than the typical atomistic runs.

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Human Activity Recognition systems require objective and reliable methods that can be used in the daily routine and must offer consistent results according with the performed activities. These systems are under development and offer objective and personalized support for several applications such as the healthcare area. This thesis aims to create a framework for human activities recognition based on accelerometry signals. Some new features and techniques inspired in the audio recognition methodology are introduced in this work, namely Log Scale Power Bandwidth and the Markov Models application. The Forward Feature Selection was adopted as the feature selection algorithm in order to improve the clustering performances and limit the computational demands. This method selects the most suitable set of features for activities recognition in accelerometry from a 423th dimensional feature vector. Several Machine Learning algorithms were applied to the used accelerometry databases – FCHA and PAMAP databases - and these showed promising results in activities recognition. The developed algorithm set constitutes a mighty contribution for the development of reliable evaluation methods of movement disorders for diagnosis and treatment applications.

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INTRODUCTION: The goal was to develop an in-house serological method with high specificity and sensitivity for diagnosis and monitoring of Chagas disease morbidity. METHODS: With this purpose, the reactivities of anti-T. cruzi IgG and subclasses were tested in successive serum dilutions of patients from Berilo municipality, Jequitinhonha Valley, Minas Gerais, Brazil. The performance of the in-house ELISA was also evaluated in samples from other relevant infectious diseases, including HIV, hepatitis C (HCV), syphilis (SYP), visceral leishmaniasis (VL), and American tegumentary leishmaniasis (ATL), and noninfected controls (NI). Further analysis was performed to evaluate the applicability of this in-house methodology for monitoring Chagas disease morbidity into three groups of patients: indeterminate (IND), cardiac (CARD), and digestive/mixed (DIG/Mix), based on their clinical status. RESULTS: The analysis of total IgG reactivity at serum dilution 1:40 was an excellent approach to Chagas disease diagnosis (100% sensitivity and specificity). The analysis of IgG subclasses showed cross-reactivity, mainly with NI, VL, and ATL, at all selected serum dilutions. Based on the data analysis, the IND group displayed higher IgG3 levels and the DIG/Mix group presented higher levels of total IgG as compared with the IND and CARD groups. CONCLUSIONS: These findings demonstrated that methodology presents promising applicability in the analysis of anti-T. cruzi IgG reactivity for the differential diagnosis and evaluation of Chagas disease morbidity.

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INTRODUCTION: Spontaneous sedimentation is an important procedure for stool examination. A modification of this technique using conical tubes was performed and evaluated. METHODS: Fifty fecal samples were processed in sedimentation glass and in polypropylene conical tubes. Another 50 samples were used for quantitative evaluation of protozoan cysts. RESULTS: Although no significant differences occurred in the frequency of protozoa and helminths detected, significant differences in protozoan cyst counts did occur. CONCLUSIONS: The use of tube predicts a shorter path in the sedimentation of the sample, increases concentration of parasites for microscopy analysis, minimizes the risks of contamination, reduces the odor, and optimizes the workspace.

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This thesis evaluates a start-up company (Jogos Almirante Lda) whose single asset is a board game named Almirante. It aims to conclude whether it makes sense to create a company or just earn copyrights. The thesis analyzes the board game’s market, as part of the general toy’s market, from which some data exists: European countries as well as the USA. In this work it is analyzed the several ways to finance a start-up company and then present an overview of the valuation of the Jogos Almirante based on three different methods: Discounted Cash Flow, Venture Capital Method and Real Options.

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INTRODUCTION: The aim of this study was to identify a rapid and simple phenotypic method for extended-spectrum β-lactamase (ESBL) detection in Enterobacter cloacae. METHODS: A total of 79 consecutive, non-repeated samples of E. cloacae were evaluated. Four phenotypic methods were applied for ESBL detection, results were compared to multiplex polymerase chain reaction (PCR) as the gold standard reference method: 1) ceftazidime and cefotaxime disks with and without clavulanate, both with boronic acid added; 2) disk approximation using cefepime and amoxicillin/clavulanate; 3) ESBL screening by minimum inhibitory concentration (MIC) ≥ 16µg/mL and 4) by MIC ≥ 2µg/mL for cefepime. RESULTS: Method 4 showed the best combination of sensitivity (100%) and specificity (94%). CONCLUSIONS: MIC ≥ 2µg/mL for cefepime would be very useful for the phenotypic detection of ESBL in samples of E. cloacae.

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ABSTRACTINTRODUCTION: In the Americas, mucosal leishmaniasis is primarily associated with infection by Leishmania (Viannia) braziliensis. However, Leishmania (Viannia) guyanensis is another important cause of this disease in the Brazilian Amazon. In this study, we aimed at detecting Leishmaniadeoxyribonucleic acid (DNA) within paraffin-embedded fragments of mucosal tissues, and characterizing the infecting parasite species.METHODS: We evaluated samples collected from 114 patients treated at a reference center in the Brazilian Amazon by polymerase chain reaction (PCR) and restriction fragment length polymorphism (RFLP) analyses.RESULTS: Direct examination of biopsy imprints detected parasites in 10 of the 114 samples, while evaluation of hematoxylin and eosin-stained slides detected amastigotes in an additional 17 samples. Meanwhile, 31/114 samples (27.2%) were positive for Leishmania spp. kinetoplast deoxyribonucleic acid (kDNA) by PCR analysis. Of these, 17 (54.8%) yielded amplification of the mini-exon PCR target, thereby allowing for PCR-RFLP-based identification. Six of the samples were identified as L. (V.) braziliensis, while the remaining 11 were identified as L. (V.) guyanensis.CONCLUSIONS: The results of this study demonstrate the feasibility of applying molecular techniques for the diagnosis of human parasites within paraffin-embedded tissues. Moreover, our findings confirm that L. (V.) guyanensisis a relevant causative agent of mucosal leishmaniasis in the Brazilian Amazon.