Response of Autonomic Nervous System to Body Positions: Fourier and Wavelet Analysis

Two mathematical methods, the Fourier and wavelet transforms, were used to study the short term cardiovascular control system. Time series, picked from electrocardiogram and arterial blood pressure lasting 6 minutes, were analyzed in supine position (SUP), during the first (HD1), and the second parts (HD2) of $90^{\circ}$ head down tilt and during recovery (REC). The wavelet transform was performed using the Haar function of period $T=2^j$ ($$,2,$...$,6) to obtain wavelet coefficients. Power spectra components were analyzed within three bands, VLF (0.003-0.04), LF (0.04-0.15) and HF (0.15-0.4) with the frequency unit cycle/interval. Wavelet transform demonstrated a higher discrimination among all analyzed periods than the Fourier transform. For the Fourier analysis, the LF of R-R intervals and VLF of systolic blood pressure show more evident difference for different body positions. For the wavelet analysis, the systolic blood pressures show much more evident difference than the R-R intervals. This study suggests a difference in the response of the vessels and the heart to different body positions. The partial dissociation between VLF and LF results is a physiologically relevant finding of this work.Comment: RevTex,8 figure

Anisotropic dynamical scaling in a spin model with competing interactions

Results are presented for the kinetics of domain growth of a two-dimensional Ising spin model with competing interactions quenched from a disordered to a striped phase. The domain growth exponent are $\beta=1/2$ and $\beta=1/3$ for single-spin-flip and spin-exchange dynamics, as found in previous simulations. However the correlation functions measured in the direction parallel and transversal to the stripes are different as suggested by the existence of different interface energies between the ground states of the model. In the case of single-spin-flip dynamics an anisotropic version of the Ohta-Jasnow-Kawasaki theory for the pair scaling function can be used to fit our data.Comment: 4 pages, REVTeX fil

Clustering data by inhomogeneous chaotic map lattices

A new approach to clustering, based on the physical properties of inhomogeneous coupled chaotic maps, is presented. A chaotic map is assigned to each data-point and short range couplings are introduced. The stationary regime of the system corresponds to a macroscopic attractor independent of the initial conditions. The mutual information between couples of maps serves to partition the data set in clusters, without prior assumptions about the structure of the underlying distribution of the data. Experiments on simulated and real data sets show the effectiveness of the proposed algorithm.Comment: 8 pages, 6 figures. Revised version accepted for publication on Physical Review Letter

Stochastic learning in a neural network with adapting synapses

We consider a neural network with adapting synapses whose dynamics can be analitically computed. The model is made of $N$ neurons and each of them is connected to $K$ input neurons chosen at random in the network. The synapses are $n$-states variables which evolve in time according to Stochastic Learning rules; a parallel stochastic dynamics is assumed for neurons. Since the network maintains the same dynamics whether it is engaged in computation or in learning new memories, a very low probability of synaptic transitions is assumed. In the limit $N\to\infty$ with $K$ large and finite, the correlations of neurons and synapses can be neglected and the dynamics can be analitically calculated by flow equations for the macroscopic parameters of the system.Comment: 25 pages, LaTeX fil

Kernel Granger causality and the analysis of dynamical networks

We propose a method of analysis of dynamical networks based on a recent measure of Granger causality between time series, based on kernel methods. The generalization of kernel Granger causality to the multivariate case, here presented, shares the following features with the bivariate measures: (i) the nonlinearity of the regression model can be controlled by choosing the kernel function and (ii) the problem of false-causalities, arising as the complexity of the model increases, is addressed by a selection strategy of the eigenvectors of a reduced Gram matrix whose range represents the additional features due to the second time series. Moreover, there is no {\it a priori} assumption that the network must be a directed acyclic graph. We apply the proposed approach to a network of chaotic maps and to a simulated genetic regulatory network: it is shown that the underlying topology of the network can be reconstructed from time series of node's dynamics, provided that a sufficient number of samples is available. Considering a linear dynamical network, built by preferential attachment scheme, we show that for limited data use of bivariate Granger causality is a better choice w.r.t methods using $L1$ minimization. Finally we consider real expression data from HeLa cells, 94 genes and 48 time points. The analysis of static correlations between genes reveals two modules corresponding to well known transcription factors; Granger analysis puts in evidence nineteen causal relationships, all involving genes related to tumor development.Comment: 14 pages, 10 figure

Phase diagram of a generalized Winfree model

We study the phase diagram of a generalized Winfree model. The modification is such that the coupling depends on the fraction of synchronized oscillators, a situation which has been noted in some experiments on coupled Josephson junctions and mechanical systems. We let the global coupling k be a function of the Kuramoto order parameter r through an exponent z such that z=1 corresponds to the standard Winfree model, z<1 strengthens the coupling at low r (low amount of synchronization) and, at z>1, the coupling is weakened for low r. Using both analytical and numerical approaches, we find that z controls the size of the incoherent phase region, and one may make the incoherent behavior less typical by choosing z<1. We also find that the original Winfree model is a rather special case, indeed the partial locked behavior disappears for z>1. At fixed k and varying gamma, the stability boundary of the locked phase corresponds to a transition that is continuous for z1. This change in the nature of the transition is in accordance with a previous study on a similarly modified Kuramoto model.Comment: 9 pages, 3 figure

Temperature dependent local inhomogeneity and magnetic moments of (Li1−xFex)OHFeSe superconductors

We have combined the extended X-ray absorption fine structure (EXAFS) and X-ray emission spectroscopy (XES) to investigate the local structure and the local iron magnetic moments of (Li1−xFex)OHFeSe (x∼0.2) superconductors. The local structure, studied by Fe K-edge EXAFS measurements, is found to be inhomogeneous that is characterized by different Fe–Se bond lengths. The inhomogeneous phase exhibits a peculiar temperature dependence with lattice anomalies in the local structural parameters at the critical temperature Tc (36 K) and at the spin density wave (SDW) transition temperature TN (130 K). Fe Kβ XES shows iron to be in a low spin state with the local Fe magnetic moment evolving anomalously as a function of temperature. Apart from a quantitative measurement of the local structure of (Li1−xFex)OHFeSe, providing direct evidence of nanoscale inhomogeneity, the results provide further evidence of the vital role that the coupled electronic, lattice and magnetic degrees of freedom play in the iron-based superconductors

Study of charmonium production in b -hadron decays and first evidence for the decay Bs0

Using decays to φ-meson pairs, the inclusive production of charmonium states in b-hadron decays is studied with pp collision data corresponding to an integrated luminosity of 3.0 fb−1, collected by the LHCb experiment at centre-of-mass energies of 7 and 8 TeV. Denoting byBC ≡ B(b → C X) × B(C → φφ) the inclusive branching fraction of a b hadron to a charmonium state C that decays into a pair of φ mesons, ratios RC1C2 ≡ BC1 /BC2 are determined as Rχc0ηc(1S) = 0.147 ± 0.023 ± 0.011, Rχc1ηc(1S) =0.073 ± 0.016 ± 0.006, Rχc2ηc(1S) = 0.081 ± 0.013 ± 0.005,Rχc1 χc0 = 0.50 ± 0.11 ± 0.01, Rχc2 χc0 = 0.56 ± 0.10 ± 0.01and Rηc(2S)ηc(1S) = 0.040 ± 0.011 ± 0.004. Here and below the first uncertainties are statistical and the second systematic.Upper limits at 90% confidence level for the inclusive production of X(3872), X(3915) and χc2(2P) states are obtained as RX(3872)χc1 < 0.34, RX(3915)χc0 < 0.12 andRχc2(2P)χc2 < 0.16. Differential cross-sections as a function of transverse momentum are measured for the ηc(1S) andχc states. The branching fraction of the decay B0s → φφφ is measured for the first time, B(B0s → φφφ) = (2.15±0.54±0.28±0.21B)×10−6. Here the third uncertainty is due to the branching fraction of the decay B0s → φφ, which is used for normalization. No evidence for intermediate resonances is seen. A preferentially transverse φ polarization is observed.The measurements allow the determination of the ratio of the branching fractions for the ηc(1S) decays to φφ and p p asB(ηc(1S)→ φφ)/B(ηc(1S)→ p p) = 1.79 ± 0.14 ± 0.32