14 resultados para Mini-scale method

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo


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Recent studies have implicated adiponectin and other adipocytokines in brain function, particularly in processes related to memory and cognition. Blood levels of adiponectin are reduced in patients with primary cognitive disorders, such as Alzheimer's disease and mild cognitive impairment, and in adult patients with major depression. The aim of the present study is to determine serum levels of adiponectin in a sample of elderly patients with major depressive disorder (MOD) as compared to healthy older adults, and to examine the correlations between adiponectin levels and parameters indicative of mood and cognitive state. We recruited fifty-one unmedicated outpatients with late-life depression (LLD) and 47 age-matched controls in this study. The diagnosis of MDD was made according to the DSM-IV criteria, and the severity of depressive episode was determined with the 21-item Hamilton Depression Scale (HORS). Cognitive state was ascertained with the Cambridge Cognitive Test (CAMCOG) and the Mini-Mental State Examination (MMSE). Serum concentrations of adiponectin were determined using a sandwich ELISA method. Serum levels of adiponectin were significantly reduced in individuals with LLD (F = p < 0.001). Adiponectin level remained significantly reduced in after controlling for BMI index, scores on the CAMCOG, MMSE and HDRS and educational level (p < 0.001). Adiponectin levels showed a negative correlation with HORS scores (r = -0.59, p < 0.001) and BMI index (r = -0.42, p < 0.001); and showed a positive correlation with CAMCOG (r = 0.34, p < 0.01) and MMSE scores (r = 0.20, p = 0.05). The availability of circulating adiponectin is reduced in older adults with major depression, with likely implications on cognitive and mood state. Additional studies are required to determine whether this abnormality pertains to the pathophysiology of geriatric depression per se, or is a consequence of the morbid state. (C) 2012 Elsevier Ltd. All rights reserved.

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Background and Purpose: Oropharyngeal dysphagia is a common manifestation in acute stroke. Aspiration resulting from difficulties in swallowing is a symptom that should be considered due to the frequent occurrence of aspiration pneumonia that could influence the patient's recovery as it causes clinical complications and could even lead to the patient's death. The early clinical evaluation of swallowing disorders can help define approaches and avoid oral feeding, which may be detrimental to the patient. This study aimed to create an algorithm to identify patients at risk of developing dysphagia following acute ischemic stroke in order to be able to decide on the safest way of feeding and minimize the complications of stroke using the National Institutes of Health Stroke Scale (NHISS). Methods: Clinical assessment of swallowing was performed in 50 patients admitted to the emergency unit of the University Hospital, Faculty of Medicine of Ribeirao Preto, Sao Paulo, Brazil, with a diagnosis of ischemic stroke, within 48 h after the beginning of symptoms. Patients, 25 females and 25 males with a mean age of 64.90 years (range 26-91 years), were evaluated consecutively. An anamnesis was taken before the patient's participation in the study in order to exclude a prior history of deglutition difficulties. For the functional assessment of swallowing, three food consistencies were used, i.e. pasty, liquid and solid. After clinical evaluation, we concluded whether there was dysphagia. For statistical analysis we used the Fisher exact test, verifying the association between the variables. To assess whether the NIHSS score characterizes a risk factor for dysphagia, a receiver operational characteristics curve was constructed to obtain characteristics for sensitivity and specificity. Results: Dysphagia was present in 32% of the patients. The clinical evaluation is a reliable method of detection of swallowing difficulties. However, the predictors of risk for the swallowing function must be balanced, and the level of consciousness and the presence of preexisting comorbidities should be considered. Gender, age and cerebral hemisphere involved were not significantly associated with the presence of dysphagia. NIHSS, Glasgow Coma Scale, and speech and language changes had a statistically significant predictive value for the presence of dysphagia. Conclusions: The NIHSS is highly sensitive (88%) and specific (85%) in detecting dysphagia; a score of 12 may be considered as the cutoff value. The creation of an algorithm to detect dysphagia in acute ischemic stroke appears to be useful in selecting the optimal feeding route while awaiting a specialized evaluation. Copyright (C) 2012 S. Karger AG, Basel

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We present a new method to quantify substructures in clusters of galaxies, based on the analysis of the intensity of structures. This analysis is done in a residual image that is the result of the subtraction of a surface brightness model, obtained by fitting a two-dimensional analytical model (beta-model or Sersic profile) with elliptical symmetry, from the X-ray image. Our method is applied to 34 clusters observed by the Chandra Space Telescope that are in the redshift range z is an element of [0.02, 0.2] and have a signal-to-noise ratio (S/N) greater than 100. We present the calibration of the method and the relations between the substructure level with physical quantities, such as the mass, X-ray luminosity, temperature, and cluster redshift. We use our method to separate the clusters in two sub-samples of high-and low-substructure levels. We conclude, using Monte Carlo simulations, that the method recuperates very well the true amount of substructure for small angular core radii clusters (with respect to the whole image size) and good S/N observations. We find no evidence of correlation between the substructure level and physical properties of the clusters such as gas temperature, X-ray luminosity, and redshift; however, analysis suggest a trend between the substructure level and cluster mass. The scaling relations for the two sub-samples (high-and low-substructure level clusters) are different (they present an offset, i. e., given a fixed mass or temperature, low-substructure clusters tend to be more X-ray luminous), which is an important result for cosmological tests using the mass-luminosity relation to obtain the cluster mass function, since they rely on the assumption that clusters do not present different scaling relations according to their dynamical state.

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This new and general method here called overflow current switching allows a fast, continuous, and smooth transition between scales in wide-range current measurement systems, like electrometers. This is achieved, using a hydraulic analogy, by diverting only the overflow current, such that no slow element is forced to change its state during the switching. As a result, this approach practically eliminates the long dead time in low-current (picoamperes) switching. Similar to a logarithmic scale, a composition of n adjacent linear scales, like a segmented ruler, measures the current. The use of a linear wide-range system based on this technique assures fast and continuous measurement in the entire range, without blind regions during transitions and still holding suitable accuracy for many applications. A full mathematical development of the method is given. Several computer realistic simulations demonstrated the viability of the technique.

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In this paper, a new algebraic-graph method for identification of islanding in power system grids is proposed. The proposed method identifies all the possible cases of islanding, due to the loss of a equipment, by means of a factorization of the bus-branch incidence matrix. The main features of this new method include: (i) simple implementation, (ii) high speed, (iii) real-time adaptability, (iv) identification of all islanding cases and (v) identification of the buses that compose each island in case of island formation. The method was successfully tested on large-scale systems such as the reduced south Brazilian system (45 buses/72 branches) and the south-southeast Brazilian system (810 buses/1340 branches). (C) 2011 Elsevier Ltd. All rights reserved.

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The use of the core-annular flow pattern, where a thin fluid surrounds a very viscous one, has been suggested as an attractive artificial-lift method for heavy oils in the current Brazilian ultra-deepwater production scenario. This paper reports the pressure drop measurements and the core-annular flow observed in a 2 7/8-inch and 300 meter deep pilot-scale well conveying a mixture of heavy crude oil (2000 mPa.s and 950 kg/m3 at 35 C) and water at several combinations of the individual flow rates. The two-phase pressure drop data are compared with those of single-phase oil flow to assess the gains due to water injection. Another issue is the handling of the core-annular flow once it has been established. High-frequency pressure-gradient signals were collected and a treatment based on the Gabor transform together with neural networks is proposed as a promising solution for monitoring and control. The preliminary results are encouraging. The pilot-scale tests, including long-term experiments, were conducted in order to investigate the applicability of using water to transport heavy oils in actual wells. It represents an important step towards the full scale application of the proposed artificial-lift technology. The registered improvements in terms of oil production rate and pressure drop reductions are remarkable.

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The aim of solving the Optimal Power Flow problem is to determine the optimal state of an electric power transmission system, that is, the voltage magnitude and phase angles and the tap ratios of the transformers that optimize the performance of a given system, while satisfying its physical and operating constraints. The Optimal Power Flow problem is modeled as a large-scale mixed-discrete nonlinear programming problem. This paper proposes a method for handling the discrete variables of the Optimal Power Flow problem. A penalty function is presented. Due to the inclusion of the penalty function into the objective function, a sequence of nonlinear programming problems with only continuous variables is obtained and the solutions of these problems converge to a solution of the mixed problem. The obtained nonlinear programming problems are solved by a Primal-Dual Logarithmic-Barrier Method. Numerical tests using the IEEE 14, 30, 118 and 300-Bus test systems indicate that the method is efficient. (C) 2012 Elsevier B.V. All rights reserved.

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Evaluation of outcomes after aesthetic surgery still is a challenge in plastic surgery. The evaluation frequently is based on subjective criteria. This study used a new clinical grading scale to evaluate aesthetic results for plastic surgeries to the abdomen. The method scores each of the following five parameters: volume of subcutaneous tissue, contour, excess of skin, aspect of the navel, and quality of the scar on the abdominal wall. The scale options are 0 (poor), 1 (fair), and 2 (good), and the total rate can range from 0 to 10. The study included 40 women ages 18-53 years. Of these 40 women, 20 underwent traditional abdominoplasty, and 20 had liposuction alone. Preoperatively and at least 1 year later, photographic results were analyzed and scored by three independent plastic surgeons. In the abdominoplasty group, the average grade rose from 2.9 +/- A 0.4 to 6.8 +/- A 0.4 postoperatively. In the liposuction group, the average grade was 5.3 +/- A 0.5 preoperatively and 7.7 +/- A 0.4 postoperatively. In both groups, the average postoperative grade was significantly higher than the preoperative grade. The mean scores for groups A and L were significantly different, demonstrating that the scale was sensitive in identifying different anatomic abnormalities in the abdomen. The rating scale used for the aesthetic evaluation of the abdomen was effective in the analysis of two different procedures: conventional abdominoplasty and liposuction. Abdominoplasty provided the greater gain according to a comparison of the pre- and postoperative scores.

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The current cosmological dark sector (dark matter plus dark energy) is challenging our comprehension about the physical processes taking place in the Universe. Recently, some authors tried to falsify the basic underlying assumptions of such dark matterdark energy paradigm. In this Letter, we show that oversimplifications of the measurement process may produce false positives to any consistency test based on the globally homogeneous and isotropic ? cold dark matter (?CDM) model and its expansion history based on distance measurements. In particular, when local inhomogeneity effects due to clumped matter or voids are taken into account, an apparent violation of the basic assumptions (Copernican Principle) seems to be present. Conversely, the amplitude of the deviations also probes the degree of reliability underlying the phenomenological DyerRoeder procedure by confronting its predictions with the accuracy of the weak lensing approach. Finally, a new method is devised to reconstruct the effects of the inhomogeneities in a ?CDM model, and some suggestions of how to distinguish between clumpiness (or void) effects from different cosmologies are discussed.

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The exploration of novel synthetic methodologies that control both size and shape of functional nanostructure opens new avenues for the functional application of nanomaterials. Here, we report a new and versatile approach to synthesize SnO2 nanocrystals (rutile-type structure) using microwave-assisted hydrothermal method. Broad peaks in the X-ray diffraction spectra indicate the nanosized nature of the samples which were indexed as a pure cassiterite tetragonal phase. Chemically and physically adsorbed water was estimated by TGA data and FT-Raman spectra to account for a new broad peak around 560 cm(-1) which is related to defective surface modes. In addition, the spherical-like morphology and low dispersed distribution size around 3-5 nm were investigated by HR-TEM and FE-SEM microscopies. Room temperature PL emission presents two broad bands at 438 and 764 nm, indicating the existence of different recombination centers. When the size of the nanospheres decreases, the relative intensity of 513 nm emission increases and the 393 nm one decreases. UV-Visible spectra show substantial changes in the optical absorbance of crystalline SnO2 nanoparticles while the existence of a small tail points out the presence of localized levels inside the forbidden band gap and supplies the necessary condition for the PL emission.

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Augmented Lagrangian methods are effective tools for solving large-scale nonlinear programming problems. At each outer iteration, a minimization subproblem with simple constraints, whose objective function depends on updated Lagrange multipliers and penalty parameters, is approximately solved. When the penalty parameter becomes very large, solving the subproblem becomes difficult; therefore, the effectiveness of this approach is associated with the boundedness of the penalty parameters. In this paper, it is proved that under more natural assumptions than the ones employed until now, penalty parameters are bounded. For proving the new boundedness result, the original algorithm has been slightly modified. Numerical consequences of the modifications are discussed and computational experiments are presented.

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Many engineering sectors are challenged by multi-objective optimization problems. Even if the idea behind these problems is simple and well established, the implementation of any procedure to solve them is not a trivial task. The use of evolutionary algorithms to find candidate solutions is widespread. Usually they supply a discrete picture of the non-dominated solutions, a Pareto set. Although it is very interesting to know the non-dominated solutions, an additional criterion is needed to select one solution to be deployed. To better support the design process, this paper presents a new method of solving non-linear multi-objective optimization problems by adding a control function that will guide the optimization process over the Pareto set that does not need to be found explicitly. The proposed methodology differs from the classical methods that combine the objective functions in a single scale, and is based on a unique run of non-linear single-objective optimizers.

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In Brazil, the large quantities of solid waste produced are out of step with public policies, technological developments, and government budgets for the division. In small municipalities, the common lack of technological knowledge and financial conditions for suitable waste disposal has resulted in a large number of illegal dumps. Therefore, small sanitary landfill facilities are working with simplified operations focusing on cost reduction and meeting the economic and technological standards of the city without endangering the environment or public health. Currently, this activity is regulated at a federal level although there is some uncertainty regarding the risk of soil and aquifer contamination as theses facilities do not employ liners. Thus, this work evaluates a small landfill to identify changes in soil and groundwater using geotechnical parameters, monitoring wells, and geophysical tests performed by electrical profiling. It is verified that based on current conditions, no contaminants have migrated via underground water aquifers, and overall no significant changes have occurred in the soil. It is concluded that, despite its simplicity, the method investigated is a viable alternative for the final disposal of municipal solid waste from small cities, especially in developing countries.

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Network reconfiguration for service restoration (SR) in distribution systems is a complex optimization problem. For large-scale distribution systems, it is computationally hard to find adequate SR plans in real time since the problem is combinatorial and non-linear, involving several constraints and objectives. Two Multi-Objective Evolutionary Algorithms that use Node-Depth Encoding (NDE) have proved able to efficiently generate adequate SR plans for large distribution systems: (i) one of them is the hybridization of the Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) with NDE, named NSGA-N; (ii) the other is a Multi-Objective Evolutionary Algorithm based on subpopulation tables that uses NDE, named MEAN. Further challenges are faced now, i.e. the design of SR plans for larger systems as good as those for relatively smaller ones and for multiple faults as good as those for one fault (single fault). In order to tackle both challenges, this paper proposes a method that results from the combination of NSGA-N, MEAN and a new heuristic. Such a heuristic focuses on the application of NDE operators to alarming network zones according to technical constraints. The method generates similar quality SR plans in distribution systems of significantly different sizes (from 3860 to 30,880 buses). Moreover, the number of switching operations required to implement the SR plans generated by the proposed method increases in a moderate way with the number of faults.