Kinematic and Electromyographic Changes During 200 m Front Crawl at Race Pace

The purpose of this study was to analyse eventual kinematic and electromyographic changes during a maximal 200 m front crawl at race pace. 10 male international level swimmers performed a 200 m maximal front crawl test. Images were recorded by 2 above and 4 under water cameras, and electromyographic signals (EMG) of 7 upper and lower limbs muscles were analysed for 1 stroke cycle in each 50 m lap. Capillary blood lactate concentrations were collected before and after the test. The variables of interest were: swimming speed, stroke length, stroke and kick frequency, hand angular velocity, upper limb and foot displacement, elbow angle, shoulder and roll angle, duration of stroke phases, and EMG for each muscle in each stroke phase. Generally, the kinematic parameters decreased, and a relative duration increased for the entry and pull phases and decreased for the recovery phase. Muscle activation of flexor carpi radialis, biceps brachii, triceps brachii, peitoral major and upper trapezius increased during specific stroke phases over the test. Blood lactate concentration increased significantly after the test. These findings suggest the occurrence of fatigue, characterised by changes in kinematic parameters and selective changes in upper limbs muscle activation according to muscle action.</p

Different fractal properties of positive and negative returns

We perform an analysis of fractal properties of the positive and the negative changes of the German DAX30 index separately using Multifractal Detrended Fluctuation Analysis (MFDFA). By calculating the singularity spectra $f(\alpha)$ we show that returns of both signs reveal multiscaling. Curiously, these spectra display a significant difference in the scaling properties of returns with opposite sign. The negative price changes are ruled by stronger temporal correlations than the positive ones, what is manifested by larger values of the corresponding H\"{o}lder exponents. As regards the properties of dominant trends, a bear market is more persistent than the bull market irrespective of the sign of fluctuations.Comment: presented at FENS2007 conference, 8 pages, 4 Fig

Application of XFaster power spectrum and likelihood estimator to Planck

We develop the XFaster Cosmic Microwave Background (CMB) temperature and polarization anisotropy power spectrum and likelihood technique for the Planck CMB satellite mission. We give an overview of this estimator and its current implementation and present the results of applying this algorithm to simulated Planck data. We show that it can accurately extract the power spectrum of Planck data for the high-l multipoles range. We compare the XFaster approximation for the likelihood to other high-l likelihood approximations such as Gaussian and Offset Lognormal and a low-l pixel-based likelihood. We show that the XFaster likelihood is not only accurate at high-l, but also performs well at moderately low multipoles. We also present results for cosmological parameter Markov Chain Monte Carlo estimation with the XFaster likelihood. As long as the low-l polarization and temperature power are properly accounted for, e.g., by adding an adequate low-l likelihood ingredient, the input parameters are recovered to a high level of accuracy.Comment: 25 pages, 20 figures, updated to reflect published version: slightly extended account of XFaster technique, added improved plots and minor corrections. Accepted for publication in MNRA

Decay of Nuclear Giant Resonances: Quantum Self-similar Fragmentation

Scaling analysis of nuclear giant resonance transition probabilities with increasing level of complexity in the background states is performed. It is found that the background characteristics, typical for chaotic systems lead to nontrivial multifractal scaling properties.Comment: 4 pages, LaTeX format, pc96.sty + 2 eps figures, accepted as: talk at the 8th Joint EPS-APS International Conference on Physics Computing (PC'96, 17-21. Sept. 1996), to appear in the Proceeding

LISA data analysis I: Doppler demodulation

The orbital motion of the Laser Interferometer Space Antenna (LISA) produces amplitude, phase and frequency modulation of a gravitational wave signal. The modulations have the effect of spreading a monochromatic gravitational wave signal across a range of frequencies. The modulations encode useful information about the source location and orientation, but they also have the deleterious affect of spreading a signal across a wide bandwidth, thereby reducing the strength of the signal relative to the instrument noise. We describe a simple method for removing the dominant, Doppler, component of the signal modulation. The demodulation reassembles the power from a monochromatic source into a narrow spike, and provides a quick way to determine the sky locations and frequencies of the brightest gravitational wave sources.Comment: 5 pages, 7 figures. References and new comments adde

Foreground separation using a flexible maximum-entropy algorithm: an application to COBE data

A flexible maximum-entropy component separation algorithm is presented that accommodates anisotropic noise, incomplete sky-coverage and uncertainties in the spectral parameters of foregrounds. The capabilities of the method are determined by first applying it to simulated spherical microwave data sets emulating the COBE-DMR, COBE-DIRBE and Haslam surveys. Using these simulations we find that is very difficult to determine unambiguously the spectral parameters of the galactic components for this data set due to their high level of noise. Nevertheless, we show that is possible to find a robust CMB reconstruction, especially at the high galactic latitude. The method is then applied to these real data sets to obtain reconstructions of the CMB component and galactic foreground emission over the whole sky. The best reconstructions are found for values of the spectral parameters: T_d=19 K, alpha_d=2, beta_ff=-0.19 and beta_syn=-0.8. The CMB map has been recovered with an estimated statistical error of \sim 22 muK on an angular scale of 7 degrees outside the galactic cut whereas the low galactic latitude region presents contamination from the foreground emissions.Comment: 29 pages, 25 figures, version accepted for publication in MNRAS. One subsection and 6 figures added. Main results unchange

Python I, II, and III CMB Anisotropy Measurement Constraints on Open and Flat-Lambda CDM Cosmogonies

We use Python I, II, and III cosmic microwave background anisotropy data to constrain cosmogonies. We account for the Python beamwidth and calibration uncertainties. We consider open and spatially-flat-Lambda cold dark matter cosmogonies, with nonrelativistic-mass density parameter Omega_0 in the range 0.1--1, baryonic-mass density parameter Omega_B in the range (0.005--0.029) h^{-2}, and age of the universe t_0 in the range (10--20) Gyr. Marginalizing over all parameters but Omega_0, the combined Python data favors an open (spatially-flat-Lambda) model with Omega_0 simeq 0.2 (0.1). At the 2 sigma confidence level model normalizations deduced from the combined Python data are mostly consistent with those drawn from the DMR, UCSB South Pole 1994, ARGO, MAX 4 and 5, White Dish, and SuZIE data sets.Comment: 20 pages, 7 figures, accepted by Ap

Non-Gaussian CMBR angular power spectra

In this paper we show how the prediction of CMBR angular power spectra $C_l$ in non-Gaussian theories is affected by a cosmic covariance problem, that is $(C_l,C_{l'})$ correlations impart features on any observed $C_l$ spectrum which are absent from the average $C^l$ spectrum. Therefore the average spectrum is rendered a bad observational prediction, and two new prediction strategies, better adjusted to these theories, are proposed. In one we search for hidden random indices conditional to which the theory is released from the correlations. Contact with experiment can then be made in the form of the conditional power spectra plus the random index distribution. In another approach we apply to the problem a principal component analysis. We discuss the effect of correlations on the predictivity of non-Gaussian theories. We finish by showing how correlations may be crucial in delineating the borderline between predictions made by non-Gaussian and Gaussian theories. In fact, in some particular theories, correlations may act as powerful non-Gaussianity indicators