Newly found evidence of Sun-climate relationships

Solar radiation cycles drive climatic changes intercyclically. These interdecadal changes were detected as variations in solar total irradiances over the time period of recorded global surface-air-temperature (SAT) and have been restored utilizing Earth Radiation Budget Channel 10C measurements (1978-1990), Greenwich Observatory faculae data (1874-1975), and Taipei Observatory Active Region data (1964-1991). Analysis of the two separate events was carried out by treating each as a discrete time series determined by the length of each solar cycle. The results show that the global SAT responded closely to the input of solar cyclical activities, S, with a quantitative relation of T = 1.62 * S with a correlation coefficient of 0.61. This correlation peaks at 0.71 with a built-in time lag of 32 months in temperature response. Solar forcing in interannual time scale was also detected and the derived relationship of T = 0.17 * S with a correlation coefficient of 0.66 was observed. Our analysis shows derived climate sensitivities approximately fit the theoretical feedback slope, 4T(sup 3)

A new view of nonlinear water waves: the Hilbert spectrum

We survey the newly developed Hilbert spectral analysis method and its applications to Stokes waves, nonlinear wave evolution processes, the spectral form of the random wave field, and turbulence. Our emphasis is on the inadequacy of presently available methods in nonlinear and nonstationary data analysis. Hilbert spectral analysis is here proposed as an alternative. This new method provides not only a more precise definition of particular events in time-frequency space than wavelet analysis, but also more physically meaningful interpretations of the underlying dynamic processes

Computing frequency by using generalized zero-crossing applied to intrinsic mode functions

This invention presents a method for computing Instantaneous Frequency by applying Empirical Mode Decomposition to a signal and using Generalized Zero-Crossing (GZC) and Extrema Sifting. The GZC approach is the most direct, local, and also the most accurate in the mean. Furthermore, this approach will also give a statistical measure of the scattering of the frequency value. For most practical applications, this mean frequency localized down to quarter of a wave period is already a well-accepted result. As this method physically measures the period, or part of it, the values obtained can serve as the best local mean over the period to which it applies. Through Extrema Sifting, instead of the cubic spline fitting, this invention constructs the upper envelope and the lower envelope by connecting local maxima points and local minima points of the signal with straight lines, respectively, when extracting a collection of Intrinsic Mode Functions (IMFs) from a signal under consideration

Computing Instantaneous Frequency by normalizing Hilbert Transform

This invention presents Normalized Amplitude Hilbert Transform (NAHT) and Normalized Hilbert Transform(NHT), both of which are new methods for computing Instantaneous Frequency. This method is designed specifically to circumvent the limitation set by the Bedorsian and Nuttal Theorems, and to provide a sharp local measure of error when the quadrature and the Hilbert Transform do not agree. Motivation for this method is that straightforward application of the Hilbert Transform followed by taking the derivative of the phase-angle as the Instantaneous Frequency (IF) leads to a common mistake made up to this date. In order to make the Hilbert Transform method work, the data has to obey certain restrictions

Analyzing nonstationary financial time series via hilbert-huang transform (HHT)

An apparatus, computer program product and method of analyzing non-stationary time varying phenomena. A representation of a non-stationary time varying phenomenon is recursively sifted using Empirical Mode Decomposition (EMD) to extract intrinsic mode functions (IMFs). The representation is filtered to extract intrinsic trends by combining a number of IMFs. The intrinsic trend is inherent in the data and identifies an IMF indicating the variability of the phenomena. The trend also may be used to detrend the data

Mass transport induced by wave motion

The problem of mass transport induced by waves is re-examined. Under the usual boundary-layer assumptions, the whole field is divided into three regions: surface-boundary layers, bottom-boundary layers, and the inviscid interior. Then, by considering Reynolds stress in the boundary layers, an expression of the mass-transport velocity in the viscous fluid is derived...

Update on EMD and Hilbert-Spectra Analysis of Time Series

This method is especially well suited for analyzing time-series data that represent nonstationary and nonlinear physical phenomena. The method is based principally on the concept of empirical mode decomposition (EMD), according to which any complicated signal (as represented by digital samples) can be decomposed into a finite number of functions, called "intrinsic mode functions" (IMFs), that admit well-behaved Hilbert transforms. The local energies and the instantaneous frequencies derived from the IMFs through Hilbert transforms can be used to construct an energy-frequency-time distribution, denoted a Hilbert spectrum

System and method of analyzing vibrations and identifying failure signatures in the vibrations

An apparatus, computer program product and method of analyzing structures. Intrinsic Mode Functions (IMFs) are extracted from the data and the most energetic IMF is selected. A spline is fit to the envelope for the selected IMF. The spline derivative is determined. A stability spectrum is developed by separating the positive and negative results into two different spectra representing stable (positive) and unstable (negative) damping factors. The stability spectrum and the non-linearity indicator are applied to the data to isolate unstable vibrations

Ibuprofen Ameliorates Fatigue- And Depressive-Like Behavior in Tumor-Bearing Mice

Aims: Cancer-related fatigue (CRF) is often accompanied by depressed mood, both of which reduce functional status and quality of life. Research suggests that increased expression of pro-inflammatory cytokines is associated with skeletal muscle wasting and depressive- and fatigue-like behaviors in rodents and cancer patients. We have previously shown that treatment with ibuprofen, a nonsteroidal anti-inflammatory drug, preserved muscle mass in tumor-bearing mice. Therefore, the purpose of the present study was to determine the behavioral effects of ibuprofen in a mouse model of CRF. Main methods: Mice were injected with colon-26 adenocarcinoma cells and treated with ibuprofen (10 mg/kg) in the drinking water. Depressive-like behavior was determined using the forced swim test (FST). Fatigue-like behaviors were determined using voluntary wheel running activity (VWRA) and grip strength. The hippocampus, gastrocnemius muscle, and serum were collected for cytokine analysis. Key findings: Tumor-bearing mice showed depressive-like behavior in the FST, which was not observed in mice treated with ibuprofen. VWRA and grip strength declined in tumor-bearing mice, and ibuprofen attenuated this decline. Tumor-bearing mice had decreased gastrocnemius muscle mass and increased expression of IL-6, MAFBx and MuRF mRNA, biomarkers of protein degradation, in the muscle. Expression of IL-1β and IL-6 was also increased in the hippocampus. Treatment with ibuprofen improved muscle mass and reduced cytokine expression in both the muscle and hippocampus of tumor-bearing mice. Significance: Ibuprofen treatment reduced skeletal muscle wasting, inflammation in the brain, and fatigue- and depressive-like behavior in tumor-bearing mice. Therefore, ibuprofen warrants evaluation as an adjuvant treatment for CRF