989 resultados para Generalized Hypergeometric Function
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2000 Mathematics Subject Classification: 26A33, 33C20
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2000 Mathematics Subject Classification: 33C60, 33C20, 44A15
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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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Includes bibliographical references.
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Exercise brachial blood pressure ( BP) predicts mortality, but because of wave reflection, central ( ascending aortic) pressure differs from brachial pressure. Exercise central BP may be clinically important, and a noninvasive means to derive it would be useful. The purpose of this study was to test the validity of a noninvasive technique to derive exercise central BP. Ascending aortic pressure waveforms were recorded using a micromanometer-tipped 6F Millar catheter in 30 patients (56 +/- 9 years; 21 men) undergoing diagnostic coronary angiography. Simultaneous recordings of the derived central pressure waveform were acquired using servocontrolled radial tonometry at rest and during supine cycling. Pulse wave analysis of the direct and derived pressure signals was performed offline (SphygmoCor 7.01). From rest to exercise, mean arterial pressure and heart rate were increased by 20 +/- 10 mm Hg and 15 +/- 7 bpm, respectively, and central systolic BP ranged from 77 to 229 mm Hg. There was good agreement and high correlation between invasive and noninvasive techniques with a mean difference (+/- SD) for central systolic BP of -1.3 +/- 3.2 mm Hg at rest and -4.7 +/- 3.3 mm Hg at peak exercise ( for both r=0.995; P < 0.001). Conversely, systolic BP was significantly higher peripherally than centrally at rest (155 +/- 33 versus 138 +/- 32mm Hg; mean difference, -16.3 +/- 9.4mm Hg) and during exercise (180 +/- 34 versus 164 +/- 33 mm Hg; mean difference, -15.5 +/- 10.4 mm Hg; for both P < 0.001). True myocardial afterload is not reliably estimated by peripheral systolic BP. Radial tonometry and pulse wave analysis is an accurate technique for the noninvasive determination of central BP at rest and during exercise.
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Mathematics Subject Classification: 26A33, 33C20.
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2000 Mathematics Subject Classification: 26A33, 33C45
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A rough set approach for attribute reduction is an important research subject in data mining and machine learning. However, most attribute reduction methods are performed on a complete decision system table. In this paper, we propose methods for attribute reduction in static incomplete decision systems and dynamic incomplete decision systems with dynamically-increasing and decreasing conditional attributes. Our methods use generalized discernibility matrix and function in tolerance-based rough sets.
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We introduce a modification of the familiar cut function by replacing the linear part in its definition by a polynomial of degree p + 1 obtaining thus a sigmoid function called generalized cut function of degree p + 1 (GCFP). We then study the uniform approximation of the (GCFP) by smooth sigmoid functions such as the logistic and the shifted logistic functions. The limiting case of the interval-valued Heaviside step function is also discussed which imposes the use of Hausdorff metric. Numerical examples are presented using CAS MATHEMATICA.
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MSC2010: 30C45, 33C45
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We here present a sample MATLAB program for the numerical evaluation of the confluent hypergeometric function Φ2. This program is based on the calculation of the inverse Laplace transform using the algorithm suggested by Simon and Alouini in their reference textbook [1].
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Pós-graduação em Física - IFT