791 resultados para Inaccuracy Measure


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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Background: Rheumatic diseases in children are associated with significant morbidity and poor health-related quality of life (HRQOL). There is no health-related quality of life (HRQOL) scale available specifically for children with less common rheumatic diseases. These diseases share several features with systemic lupus erythematosus (SLE) such as their chronic episodic nature, multi-systemic involvement, and the need for immunosuppressive medications. HRQOL scale developed for pediatric SLE will likely be applicable to children with systemic inflammatory diseases.Findings: We adapted Simple Measure of Impact of Lupus Erythematosus in Youngsters (SMILEY (c)) to Simple Measure of Impact of Illness in Youngsters (SMILY (c)-Illness) and had it reviewed by pediatric rheumatologists for its appropriateness and cultural suitability. We tested SMILY (c)-Illness in patients with inflammatory rheumatic diseases and then translated it into 28 languages. Nineteen children (79% female, n= 15) and 17 parents participated. The mean age was 12 +/- 4 years, with median disease duration of 21 months (1-172 months). We translated SMILY (c)-Illness into the following 28 languages: Danish, Dutch, French (France), English (UK), German (Germany), German (Austria), German (Switzerland), Hebrew, Italian, Portuguese (Brazil), Slovene, Spanish (USA and Puerto Rico), Spanish (Spain), Spanish (Argentina), Spanish (Mexico), Spanish (Venezuela), Turkish, Afrikaans, Arabic (Saudi Arabia), Arabic (Egypt), Czech, Greek, Hindi, Hungarian, Japanese, Romanian, Serbian and Xhosa.Conclusion: SMILY (c)-Illness is a brief, easy to administer and score HRQOL scale for children with systemic rheumatic diseases. It is suitable for use across different age groups and literacy levels. SMILY (c)-Illness with its available translations may be used as useful adjuncts to clinical practice and research.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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In this work, crystalline titanium dioxide (TiO2) nanoparticles with variable average crystallite sizes (e.g., 8 nm) and surface areas (e.g., 192 m² g-1) were synthesized in pure anatase phase using H2O2 to reduce the hydrolysis rate of the titanium ions. An isopropanol (IP) solution was employed as the reaction medium. The TiO2 nanoparticles were characterized by powder X-ray diffraction analysis (XRD), Raman spectroscopy and transmission electron microscopy (TEM). By changing the synthesis parameters it was possible to control nanoparticle size and avoid the coalescence process. A dependence of the Raman wavenumber on the nanocrystal sizes was determined, which is quite useful for a quick check of the size of TiO2 nanocrystals.

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This document is one of a series which contains the results of research carried out during a 1969 Summer Study of Urban Decentralization at the Oak Ridge National Laboratory, sponsored by the Department of Housing and Urban Development and the U.S. Atomic Energy Commission. The summary of the Summer Study is contained in "An Introduction to Urban Decentralization Research," ORNL-HUD-3.

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High intake of saturated fat from meats has been associated with cardiovascular disease, cancer, diabetes, and others diseases. In this paper, we are introducing a simple, high-throughput, and non-destructive low-resolution nuclear magnetic resonance method that has the potential to analyze the intramuscular fat content (IMF) in more than 1,000 beef portions per hour. The results can be used in nutritional fact labels, replacing the currently used average value. The method is based on longitudinal (T(1)) and transverse (T(2)) relaxation time information obtained by a continuous wave-free precession (CWFP) sequence. CWFP yields a higher correlation coefficient (r=0.9) than the conventional Carr-Purcell-Meiboom- Gill (CPMG) method (r=-0.25) for IMF in beef and is just as fast and a simpler pulse sequence than CPMG. The method can also be applied to other meat products.

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We study measure functional differential equations and clarify their relation to generalized ordinary differential equations. We show that functional dynamic equations on time scales represent a special case of measure functional differential equations. For both types of equations, we obtain results on the existence and uniqueness of solutions, continuous dependence, and periodic averaging.

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In the past decades, all of the efforts at quantifying systems complexity with a general tool has usually relied on using Shannon's classical information framework to address the disorder of the system through the Boltzmann-Gibbs-Shannon entropy, or one of its extensions. However, in recent years, there were some attempts to tackle the quantification of algorithmic complexities in quantum systems based on the Kolmogorov algorithmic complexity, obtaining some discrepant results against the classical approach. Therefore, an approach to the complexity measure is proposed here, using the quantum information formalism, taking advantage of the generality of the classical-based complexities, and being capable of expressing these systems' complexity on other framework than its algorithmic counterparts. To do so, the Shiner-Davison-Landsberg (SDL) complexity framework is considered jointly with linear entropy for the density operators representing the analyzed systems formalism along with the tangle for the entanglement measure. The proposed measure is then applied in a family of maximally entangled mixed state.

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Semi-supervised learning techniques have gained increasing attention in the machine learning community, as a result of two main factors: (1) the available data is exponentially increasing; (2) the task of data labeling is cumbersome and expensive, involving human experts in the process. In this paper, we propose a network-based semi-supervised learning method inspired by the modularity greedy algorithm, which was originally applied for unsupervised learning. Changes have been made in the process of modularity maximization in a way to adapt the model to propagate labels throughout the network. Furthermore, a network reduction technique is introduced, as well as an extensive analysis of its impact on the network. Computer simulations are performed for artificial and real-world databases, providing a numerical quantitative basis for the performance of the proposed method.

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Objective: To assess the evolution of motor function in patients with Duchenne muscular dystrophy (DMD) treated with steroids (prednisolone or deflazacort) through the Motor Function Measure (MFM), which evaluates three dimensions of motor performance (D1, D2, D3). Methods: Thirty-three patients with DMD (22 ambulant, 6 non-ambulant and 5 who lost the capacity to walk during the period of the study) were assessed using the MFM scale six times over a period of 18 months. Results: All the motor functions remained stable for 14 months in all patients, except D1 for those who lost their walking ability. In ambulant patients, D2 (axial and proximal motor capacities) motor functions improved during six months; an improvement in D3 (distal motor capacity) was noted during the total follow-up. D1 (standing posture and transfers) and total score were useful to predict the loss of the ability to walk. Conclusions: The use of the MFM in DMD patients confirms the benefits of the steroid treatment for slowing the progression of the disease.

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In this paper, we give a possible solution to the cosmological constant problem. It is shown that the traditional approach, based on volume weighting of probabilities, leads to an incoherent conclusion: the probability that a randomly chosen observer measures Lambda = 0 is exactly equal to 1. Using an alternative, volume averaging measure, instead of volume weighting can explain why the cosmological constant is non-zero.

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Background: Psychosis has various causes, including mania and schizophrenia. Since the differential diagnosis of psychosis is exclusively based on subjective assessments of oral interviews with patients, an objective quantification of the speech disturbances that characterize mania and schizophrenia is in order. In principle, such quantification could be achieved by the analysis of speech graphs. A graph represents a network with nodes connected by edges; in speech graphs, nodes correspond to words and edges correspond to semantic and grammatical relationships. Methodology/Principal Findings: To quantify speech differences related to psychosis, interviews with schizophrenics, manics and normal subjects were recorded and represented as graphs. Manics scored significantly higher than schizophrenics in ten graph measures. Psychopathological symptoms such as logorrhea, poor speech, and flight of thoughts were grasped by the analysis even when verbosity differences were discounted. Binary classifiers based on speech graph measures sorted schizophrenics from manics with up to 93.8% of sensitivity and 93.7% of specificity. In contrast, sorting based on the scores of two standard psychiatric scales (BPRS and PANSS) reached only 62.5% of sensitivity and specificity. Conclusions/Significance: The results demonstrate that alterations of the thought process manifested in the speech of psychotic patients can be objectively measured using graph-theoretical tools, developed to capture specific features of the normal and dysfunctional flow of thought, such as divergence and recurrence. The quantitative analysis of speech graphs is not redundant with standard psychometric scales but rather complementary, as it yields a very accurate sorting of schizophrenics and manics. Overall, the results point to automated psychiatric diagnosis based not on what is said, but on how it is said.

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A total internal reflection-based differencial refractometer, capable of measuring the real and imaginary parts of the complex refractive index in real time, is presented. The device takes advantage of the phase difference acquired by s- and p-polarized light to generate an easily detectable minimum at the reflected profile. The method allows to sensitively measuring transparent and turbid liquid samples. (C)2012 Optical Society of America