Fractional Spectral Moments for Digital Simulation of Multivariate Wind Velocity Fields

In this paper, a method for the digital simulation of wind velocity fields by Fractional Spectral Moment function is proposed. It is shown that by constructing a digital filter whose coefficients are the fractional spectral moments, it is possible to simulate samples of the target process as superposition of Riesz fractional derivatives of a Gaussian white noise processes. The key of this simulation technique is the generalized Taylor expansion proposed by the authors. The method is extended to multivariate processes and practical issues on the implementation of the method are reported.Comment: 12 pages, 2 figure

Damage identification by a modified Ant Colony Optimization for not well spaced frequency systems

Recently, it has been shown , that a damage detection strategy based on a proper functional calculated on the analytical signal of the structural dynamical response, consents to identify very low damage level. In this regard, they stressed the efficiency of Hilbert Transform to obtain the analytical response representation that shows more sensitivity for predicting damage with respect to the simple signal response. Then, a damage identification procedure based on the minimization of the difference between theoretical and measured data was proposed with satisfactory results. Unfortunately, this procedure, since the need of use of band pass filter around the natural frequency of the system, fails for structures having closed natural frequencies. By the way, performing procedures for sharply detecting damage in not well spaced frequency structure is a hoary problem. Aim of this paper is to extend the aforementioned procedure to these systems. To aim at this, it is desirable to go further insight into optimization algorithms, suitable for this kind of systems. For instance, it will be interesting considering, the ant colony optimization algorithm (ACO) that is a probabilistic technique for solving computational problems which can be reduced to finding good paths through graphs. Recently ACO has been extended to continuous domain and labeled as ACOð. A novel aspect of the proposed paper is introducing ACOð into the previous procedure avoiding the use of filters, such that may be available for not well spaced frequency system. Moreover, it will be desirable avoiding the use of Hilbert transform, that means apply the identification procedure directly on the acceleration responses and not on the analytical signal response. Therefore, in this paper it will be introduced a procedure for detecting damage in structures having close frequencies, without using analytical signal response

Incipient damage identification through characteristics of the analytical signal response

The analytical signal is a complex representation of a time domain signal: the real part is the time domain signal itself, while the imaginary part is its Hilbert transform. It has been observed that damage, even at a very low level, yields clearly detectable variations of analytical signal quantities such as phase and instantaneous frequency. This observation can represent a step toward a quick and effective tool to recognize the presence of incipient damage where other frequency-based techniques fail. In this paper a damage identification procedure based on an adimensional functional of the square of the difference between the characteristics of the analytical theoretical and measured signal is proposed. Numerical examples, on a single degree of freedom system and of 3 degrees of freedom building model, prove the efficacy of the proposed method, its robustness in the presence of measuring errors, and show that the use of the signal phase leads to the best damage parameter estimation. Copyright © 2008 John Wiley & Sons, Ltd

Statistics of non-linear stochastic dynamical systems under L\'evy noises by a convolution quadrature approach

This paper describes a novel numerical approach to find the statistics of the non-stationary response of scalar non-linear systems excited by L\'evy white noises. The proposed numerical procedure relies on the introduction of an integral transform of Wiener-Hopf type into the equation governing the characteristic function. Once this equation is rewritten as partial integro-differential equation, it is then solved by applying the method of convolution quadrature originally proposed by Lubich, here extended to deal with this particular integral transform. The proposed approach is relevant for two reasons: 1) Statistics of systems with several different drift terms can be handled in an efficient way, independently from the kind of white noise; 2) The particular form of Wiener-Hopf integral transform and its numerical evaluation, both introduced in this study, are generalizations of fractional integro-differential operators of potential type and Gr\"unwald-Letnikov fractional derivatives, respectively.Comment: 20 pages, 5 figure

Relationship Between Short-Term Blood Pressure Variability and Subclinical Renal Damage in Essential Hypertensive Patients

The authors aimed to analyze the relationship between subclinical renal damage, defined as the presence of microalbuminuria or an estimated glomerular filtration rate (eGFR) between 30 mL/min/1.73 m(2) and 60 mL/min/1.73 m(2) and short-term blood pressure (BP) variability, assessed as average real variability (ARV), weighted standard deviation (SD) of 24-hour BP, and SD of daytime and nighttime BP. A total of 328 hypertensive patients underwent 24-hour ambulatory BP monitoring, 24-hour albumin excretion rate determination, and eGFR calculation using the Chronic Kidney Disease Epidemiology Collaboration equation. ARV of 24-hour systolic BP (SBP) was significantly higher in patients with subclinical renal damage (P=.001). This association held (P=.04) after adjustment for potential confounders. In patients with microalbuminuria, ARV of 24-hour SBP, weighted SD of 24-hour SBP, and SD of daytime SBP were also independently and inversely related to eGFR. These results seem to suggest that in essential hypertension, short-term BP variability is independently associated with early renal abnormalities

[OP.7B.08] INFLUENCE OF GENDER ON THE RELATIONSHIPS BETWEEN NEW INDICES OF ADIPOSITY AND LEFT VENTRICULAR MASS AND HYPERTROPHY IN HYPERTENSIVE PATIENTS

OBJECTIVE: The unfavourable effects of the association of obesity with hypertension on cardiac structure and function have been extensively studied. However, controversy still exists about the influence of gender on the relationship between obesity and left ventricular mass (LVM) and hypertrophy (LVH). Even if body mass index (BMI) and waist circumference (WC) are widely used as anthropometric predictors for cardiovascular diseases (CVD), their validity has been questioned. Recently, Body Shape Index (ABSI) and Body Roundness Index (BRI) were proposed as alternative measures of adiposity that may better reflect health status (1-2).Our study was aimed to assess the ability of ABSI and BRI in identifying LVH and to determine whether they are superior to BMI and WC. Moreover, the influence of gender on the relationships between all these indices of adiposity and LVM was also evaluated. DESIGN AND METHOD: We enrolled 724 subjects with EH (mean age 45 ± 12 years, 63 % men) without cardiovascular complications.In all subjects the anthropometric indices (weight, height and waist circumference) and the routine biochemical parameters were determined. BMI, ABSI and BRI were calculated. Furthermore, all patients underwent a 24-h blood pressure monitoring and an echocardiogram. LVM was indexed for body surface area (LVMI) and for height2.7 (LVMH2.7). RESULTS: The univariate correlations of LVMI and LVMH2.7 with the measures of adiposity evaluated are shown in the table 1.ROC curves analysis revealed that in overall population (table 2) and in men BRI has a greater ability to identify LVH defined as LVMH2.7 > 51 g/m2.7.(Figure is included in full-text article.) CONCLUSIONS: : Our results seems to suggest that in men, but not in women, the BRI has a greater sensitivity to detect LVH than ABSI and the traditional measures of adiposity

Nonlinear SDE Excited by External Lévy White Noise Processes

A numerical method for approximating the statistics of the solution of nonlinear stochastic systems excited by Gaussian and non-Gaussian external white noises is proposed. The differential equation governing the evolution in time of the characteristic function is resolved by the convolution quadrature method. This approach is especially suited for those problems in which the nonlinear drift term is not of polynomial form. In such cases the equation governing the evolution in time of the characteristic function is not a partial differential equation. Statistics are found by introducing an integral operator of Wiener-Hopf type, called the transformation operator, and applying the Lubich's convolution quadrature. This leads to find the statistics of the response by solving a linear system of differential equations