883 resultados para Multimodal Biometrics
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Background: There are few studies reporting pain and postoperative analgesia associated with mastectomy in dogs. The aim of this study was to evaluate postoperative pain after unilateral mastectomy using two different surgical techniques in the dog.Findings: Twenty female dogs were assigned (n=10/group) to undergo unilateral mastectomy using either the combination of sharp and blunt dissection (SBD) or the modified SBD (mSBD) technique, in which the mammary chain is separated from the abdominal wall entirely by blunt (hand and finger) dissection except for a small area cranial to the first gland, in a prospective, randomized, clinical trial. All dogs were premedicated with intramuscular acepromazine (0.05 mg/kg) and morphine (0.3 mg/kg). Anesthesia was induced with intravenous ketamine (5 mg/kg) and diazepam (0.25 mg/kg), and maintained with isoflurane. Subcutaneous meloxicam (0.2 mg/kg) was administered before surgery. Postoperative pain was evaluated according to the University of Melbourne pain scale (UMPS) by an observer who was blinded to the surgical technique.. Rescue analgesia was provided by the administration of intramuscular morphine (0.5 mg/kg) if pain scores were > 14 according to the UMPS. Data were analyzed using t-tests and ANOVA (P>0.05). There were no significant differences between the groups for age, weight, extubation time, and duration of surgery and anesthesia (P>0.05). There were no significant differences for postoperative pain scores between groups. Rescue analgesia was required in one dog in each group.Conclusions: The two surgical techniques produced similar surgical times, incidence of perioperative complications and postoperative pain. Multimodal analgesia is recommended for treatment of postoperative pain in dogs undergoing unilateral mastectomy.
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The purpose of this study was to determine a shape factor to estimate area of leaflets of two peanut cultivars (IAC TATU ST, IAC RUNNER 886). Correlation studies were conducted involving real leaf area (Sf) and leaf length (C), maximum leaf width (L) and the product between C and L. For each cultivar was determined a form factor (f) by means of regression analysis between the product of the length by the width and the actual area of leaves and the correlation between leaf area estimated by the correction factor and direct measurement. All evaluated models (linear, exponential or geometric) provided good estimates of leaf area (above 87%). Linear models had the best fit, passing or not through the origin. From a practical viewpoint, it is suggested to use the linear model involving the C and L product, using a linear coefficient equal to zero, with values of factor f equal to 0.7111 and 0.7266 for IAC RUNNER 886 and IAC TATU ST, respectively. The method of dimensions is feasible for the estimation of leaf area for both peanut cultivars, for showing good r(2) values (0.97), with errors below 3%, even when used with independent data.
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Pós-graduação em Agronomia (Agricultura) - FCA
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Pós-graduação em Agronomia (Irrigação e Drenagem) - FCA
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Pós-graduação em Engenharia Elétrica - FEIS
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The effects of body biometrics on cardiac measurements and description of cardiac anatomy were performed in red-tailed boas (Boa constrictor constrictor) (n = 29) using real-time B-mode ultrasonography. Statistical comparison of measured cardiac metrics according to sex and body measurements demonstrated no significant difference between sexes but a highly significant linear increase between body length and mass and all cardiac metrics.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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The use of multimodal neuroimaging techniques has been helpful in the investigation of epileptogenic zone in patients with refractory epilepsies. This work aims to describe an ictal event during EEG-fMRI performed simultaneously in a 39-year-old man with refractory epilepsy. The EEG data were recorded at a sampling rate of 5 kHz, using a BrainAmp (BrainProducts, München, Germany) amplifier, with 64 MR (magnetic resonance) compatible Ag/AgCl electrodes. MR images were acquired using a 3T scanner in 3 sequences of 6 minutes of echo-planar images (EPIs), with TR = 2s, being the last sequence stopped after the ictal event. The EEG was corrected for gradient and pulse artifacts using the Brain Vision Analyzer2 software (BrainProducts), and the functional images were realigned, slice-timing corrected, normalized and smoothed. The start of the ictal changes was used for the evaluation of the BOLD response in MR images, using a t-test with a minimum cluster of 5 voxels, p <0.005 (T>2.5). The patient had a partial complex seizure, as noted by neurologist. The fMRI data showed positive BOLD responses (activation) in dysplastic areas, but showed the most significant activation outside the lesion, in areas compatible with secondary spread of the epileptic focus, probably caused by motor reaction also observed during the seizure. As a conclusion, we note that the technique of EEG-fMRI can detect the epileptogenic zone in patients with refractory epilepsy, but areas of dissemination of primary epileptogenic focus may show significant activation, introducing additional difficulties to the interpretation of the results
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This monograph aims to study the problem of thinning, also known by Image Skeletonization, to explore their applications in areas such as, Biometrics, Medicine, Engineering and Cartography. The algorithms of thinning can be classi ed into two major groups: iterative algorithms and non-iterative algorithms. Iterative are sub-divided into sequential algorithms and parallel algorithms. In order to develop a computer system able to extract the skeleton of an image, were studied, analyzed and implemented di erent algorithms for this problem, precisely those of Stentiford, Zhang Suen, and Holt
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The use of physical characteristics for human identification is known as biometrics. Among the many biometrics traits available, the fingerprint is the most widely used. The fingerprint identification is based on the impression patterns, as the pattern of ridges and minutiae, characteristics of first and second levels respectively. The current identification systems use these two levels of fingerprint features due to the low cost of the sensors. However, the recent advances in sensor technology, became possible to use third level features present within the ridges, such as the perspiration pores. Recent studies show that the use of third-level features can increase security and fraud protection in biometric systems, since they are difficult to reproduce. In addition, recent researches have also focused on multibiometrics recognition due to its many advantages. The goal of this research project was to apply fusion techniques for fingerprint recognition in order to combine minutia, ridges and pore-based methods and, thus, provide more robust biometrics recognition systems, and also to develop an automated fingerprint identification system using these three methods of recognition. We evaluated isotropic-based and adaptive-based automatic pore extraction methods, and the fusion of pore-based method with the identification methods based on minutiae and ridges. The experiments were performed on the public database PolyUHRF and showed a reduction of approximately 16% in the EER compared to the best results obtained by the methods individually
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Pós-graduação em Ciências da Motricidade - IBRC
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Pós-graduação em Agronomia (Produção Vegetal) - FCAV