Biomedical subjects

S Havlin

Publications and source records attributed to S Havlin.

At least 55 records · Page 3Linked to original sources

PubMed1999

Scaling for the critical percolation backbone.

We study the backbone connecting two given sites of a two-dimensional lattice separated by an arbitrary distance r in a system of size L at the percolation threshold. We find a scaling form for the average backbone mass: approximately L(dB)G(r/L), where G can be well approximated by a power law for 0 approximately L(dB-psi)r(psi) for the entire range 0<r<L. We also propose a scaling form for the probability distribution P(M(B)) of backbone mass for a given r. For r approximately L, P(MB) is peaked around L(dB), whereas for r<<L, P(M(B)) decreases as a power law, M(-tauB)B, with tauB approximately 1.20+/-0.03. The exponents psi and tauB satisfy the relation psi=dB(tauB-1), and psi is the codimension of the backbone, psi=d-dB.

Journal Article↗

PubMed1999

Optimal paths in disordered media: scaling of the crossover from self-similar to self-affine behavior.

We study optimal paths in disordered energy landscapes using energy distributions of the type P(log(10) E)=const that lead to the strong disorder limit. If we truncate the distribution, so that P(log(10) E)=const only for E(min) < or =E < or =E(max), and P(log(10) E)=0 otherwise, we obtain a crossover from self-similar (strong disorder) to self-affine (moderate disorder) behavior at a path length l(x). We find that l(x) proportional, variant[log(10)(E(max)/E(min))](kappa), where the exponent kappa has the value kappa=1.60 +/- 0.03 both in d=2 and d=3. We show how the crossover can be understood from the distribution of local energies on the optimal paths.

Journal Article↗

PubMed1998

Multiple-time scales analysis of physiological time series under neural control.

We discuss multiple-time scale properties of neurophysiological control mechanisms, using heart rate and gait regulation as model systems. We find that scaling exponents can be used as prognostic indicators. Furthermore, detection of more subtle degradation of scaling properties may provide a novel early warning system in subjects with a variety of pathologies including those at high risk of sudden death.

Adult↗

PubMed1998

Scaling and universality in heart rate variability distributions.

We find that a universal homogeneous scaling form describes the distribution of cardiac variations for a group of healthy subjects, which is stable over a wide range of time scales. However, a similar scaling function does not exist for a group with a common cardiopulmonary instability associated with sleep apnea. Subtle differences in the distributions for the day- and night-phase dynamics for healthy subjects are detected.

Adult↗

PubMed1997

Aggregation and disaggregation of senile plaques in Alzheimer disease.

We quantitatively analyzed, using laser scanning confocal microscopy, the three-dimensional structure of individual senile plaques in Alzheimer disease. We carried out the quantitative analysis using statistical methods to gain insights about the processes that govern Abeta peptide deposition. Our results show that plaques are complex porous structures with characteristic pore sizes. We interpret plaque morphology in the context of a new dynamical model based on competing aggregation and disaggregation processes in kinetic steady-state equilibrium with an additional diffusion process allowing Abeta deposits to diffuse over the surface of plaques.

Alzheimer Disease↗

PubMed1997

Quantification of DNA patchiness using long-range correlation measures.

We introduce and develop new techniques to quantify DNA patchiness, and to quantify characteristics of its mosaic structure. These techniques, which involve calculating two functions, alpha(l) and beta(l), measure correlations at length scale l and detect distinct characteristic patch sizes embedded in scale-invariant patch size distributions. Using these new methods, we address a number of issues relating to the mosaic structure of genomic DNA. We find several distinct characteristic patch sizes in certain genomic sequences, and compare, contrast, and quantify the correlation properties of different sequences, including a number of yeast, human, and prokaryotic sequences. We exclude the possibility that the correlation properties and the known mosaic structure of DNA can be explained either by simple Markov processes or by tandem repeats of dinucleotides. We find that the distinct patch sizes in all 16 yeast chromosomes are similar. Furthermore, we test the hypothesis that, for yeast, patchiness is caused by the alternation of coding and noncoding regions, and the hypothesis that in human sequences patchiness is related to repetitive sequences. We find that, by themselves, neither the alternation of coding and noncoding regions, nor repetitive sequences, can fully explain the long-range correlation properties of DNA.

Chromosomes↗

PubMed1996

Scaling behaviour of heartbeat intervals obtained by wavelet-based time-series analysis.

Biological time-series analysis is used to identify hidden dynamical patterns which could yield important insights into underlying physiological mechanisms. Such analysis is complicated by the fact that biological signals are typically both highly irregular and non-stationary, that is, their statistical character changes slowly or intermittently as a result of variations in background influences. Previous statistical analyses of heartbeat dynamics have identified long-range correlations and power-law scaling in the normal heartbeat, but not the phase interactions between the different frequency components of the signal. Here we introduce a new approach, based on the wavelet transform and an analytic signal approach, which can characterize non-stationary behaviour and elucidate such phase interactions. We find that, when suitably rescaled, the distributions of the variations in the beat-to-beat intervals for all healthy subjects are described by a single function stable over a wide range of timescales. However, a similar scaling function does not exist for a group with cardiopulmonary instability caused by sleep apnoea. We attribute the functional form of the scaling observed in the healthy subjects to underlying nonlinear dynamics, which seem to be essential to normal heart function. The approach introduced here should be useful in the analysis of other nonstationary biological signals.

Adult↗

PubMed1996