163 research outputs found
Holder exponent spectra for human gait
The stride interval time series in normal human gait is not strictly
constant, but fluctuates from step to step in a complex manner. More precisely,
it has been shown that the control process for human gait is a fractal random
phenomenon, that is, one with a long-term memory. Herein we study the Holder
exponent spectra for the slow, normal and fast gaits of 10 young healthy men in
both free and metronomically triggered conditions and establish that the stride
interval time series is more complex than a monofractal phenomenon. A slightly
multifractal and non-stationary time series under the three different gait
conditions emerges.Comment: 23 pages, 12 figures, 9 Table
Quantifying the Multivariate ENSO Index (MEI) coupling to CO2 concentration and to the length of day variations
The El Ni\~no Southern Oscillation (ENSO) is the Earth's strongest climate
fluctuation on inter-annual time-scales and has global impacts although
originating in the tropical Pacific. Many point indices have been developed to
describe ENSO but the Multivariate ENSO Index (MEI) is considered the most
representative since it links six different meteorological parameters measured
over the tropical Pacific. Extreme values of MEI are correlated to the extreme
values of atmospheric CO2 concentration rate variations and negatively
correlated to equivalent scale extreme values of the length of day (LOD) rate
variation. We evaluate a first order conversion function between MEI and the
other two indexes using their annual rate of variation. The quantification of
the strength of the coupling herein evaluated provides a quantitative measure
to test the accuracy of theoretical model predictions. Our results further
confirm the idea that the major local and global Earth-atmosphere system
mechanisms are significantly coupled and synchronized to each other at multiple
scales.Comment: Theoretical Applied Climatology (2012
Estimate solar contribution to the global surface warming using the ACRIM TSI satellite composite
We study, by using a wavelet decomposition methodology, the solar signature
on global surface temperature data using the ACRIM total solar irradiance
satellite composite by Willson and Mordvinov. These data present a
+0.047%/decade trend between minima during solar cycles 21-23 (1980-2002). We
estimate that the ACRIM upward trend might have minimally contributed
10-30% of the global surface temperature warming over the period
1980-2002
Scaling detection in time series: diffusion entropy analysis
The methods currently used to determine the scaling exponent of a complex
dynamic process described by a time series are based on the numerical
evaluation of variance. This means that all of them can be safely applied only
to the case where ordinary statistical properties hold true even if strange
kinetics are involved. We illustrate a method of statistical analysis based on
the Shannon entropy of the diffusion process generated by the time series,
called Diffusion Entropy Analysis (DEA). We adopt artificial Gauss and L\'{e}vy
time series, as prototypes of ordinary and anomalus statistics, respectively,
and we analyse them with the DEA and four ordinary methods of analysis, some of
which are very popular. We show that the DEA determines the correct scaling
exponent even when the statistical properties, as well as the dynamic
properties, are anomalous. The other four methods produce correct results in
the Gauss case but fail to detect the correct scaling in the case of L\'{e}vy
statistics.Comment: 21 pages,10 figures, 1 tabl
Diffusion entropy and waiting time statistics of hard x-ray solar flares
We analyze the waiting time distribution of time distances between two
nearest-neighbor flares. This analysis is based on the joint use of two
distinct techniques. The first is the direct evaluation of the distribution
function , or of the probability, , that no time
distance smaller than a given is found. We adopt the paradigm of the
inverse power law behavior, and we focus on the determination of the inverse
power index , without ruling out different asymptotic properties that
might be revealed, at larger scales, with the help of richer statistics. The
second technique, called Diffusion Entropy (DE) method, rests on the evaluation
of the entropy of the diffusion process generated by the time series. The
details of the diffusion process depend on three different walking rules, which
determine the form and the time duration of the transition to the scaling
regime, as well as the scaling parameter . With the first two rules the
information contained in the time series is transmitted, to a great extent, to
the transition, as well as to the scaling regime. The same information is
essentially conveyed, by using the third rules, into the scaling regime, which,
in fact, emerges very quickly after a fast transition process. We show that the
significant information hidden within the time series concerns memory induced
by the solar cycle, as well as the power index . The scaling parameter
becomes a simple function of , when memory is annihilated. Thus,
the three walking rules yield a unique and precise value of if the memory
is wisely taken under control, or cancelled by shuffling the data. All this
makes compelling the conclusion that .Comment: 23 pages, 13 figure
Compression and diffusion: a joint approach to detect complexity
The adoption of the Kolmogorov-Sinai (KS) entropy is becoming a popular
research tool among physicists, especially when applied to a dynamical system
fitting the conditions of validity of the Pesin theorem. The study of time
series that are a manifestation of system dynamics whose rules are either
unknown or too complex for a mathematical treatment, is still a challenge since
the KS entropy is not computable, in general, in that case. Here we present a
plan of action based on the joint action of two procedures, both related to the
KS entropy, but compatible with computer implementation through fast and
efficient programs. The former procedure, called Compression Algorithm
Sensitive To Regularity (CASToRe), establishes the amount of order by the
numerical evaluation of algorithmic compressibility. The latter, called Complex
Analysis of Sequences via Scaling AND Randomness Assessment (CASSANDRA),
establishes the complexity degree through the numerical evaluation of the
strength of an anomalous effect. This is the departure, of the diffusion
process generated by the observed fluctuations, from ordinary Brownian motion.
The CASSANDRA algorithm shares with CASToRe a connection with the Kolmogorov
complexity. This makes both algorithms especially suitable to study the
transition from dynamics to thermodynamics, and the case of non-stationary time
series as well. The benefit of the joint action of these two methods is proven
by the analysis of artificial sequences with the same main properties as the
real time series to which the joint use of these two methods will be applied in
future research work.Comment: 27 pages, 9 figure
ACRIM-gap and total solar irradiance revisited: Is there a secular trend between 1986 and 1996?
A gap in the total solar irradiance (TSI) measurements between ACRIM-1 and
ACRIM-2 led to the ongoing debate on the presence or not of a secular trend
between the minima preceding cycles 22 (in 1986) and 23 (1996). It was recently
proposed to use the SATIRE model of solar irradiance variations to bridge this
gap. When doing this, it is important to use the appropriate SATIRE-based
reconstruction, which we do here, employing a reconstruction based on
magnetograms. The accuracy of this model on months to years timescales is
significantly higher than that of a model developed for long-term
reconstructions used by the ACRIM team for such an analysis. The constructed
`mixed' ACRIM - SATIRE composite shows no increase in the TSI from 1986 to
1996, in contrast to the ACRIM TSI composite.Comment: 4 figure
Memory beyond memory in heart beating: an efficient way to detect pathological conditions
We study the long-range correlations of heartbeat fluctuations with the
method of diffusion entropy. We show that this method of analysis yields a
scaling parameter that apparently conflicts with the direct evaluation
of the distribution of times of sojourn in states with a given heartbeat
frequency. The strength of the memory responsible for this discrepancy is given
by a parameter , which is derived from real data. The
distribution of patients in the (, )-plane yields a neat
separation of the healthy from the congestive heart failure subjects.Comment: submitted to Physical Review Letters, 5 figure
Evidences for a quasi 60-year North Atlantic Oscillation since 1700 and its meaning for global climate change
The North Atlantic Oscillation (NAO) obtained using instrumental and
documentary proxy predictors from Eurasia is found to be characterized by a
quasi 60-year dominant oscillation since 1650. This pattern emerges clearly
once the NAO record is time integrated to stress its comparison with the
temperature record. The integrated NAO (INAO) is found to well correlate with
the length of the day (since 1650) and the global surface sea temperature
record HadSST2 and HadSST3 (since 1850). These findings suggest that INAO can
be used as a good proxy for global climate change, and that a 60-year cycle
exists in the global climate since at least 1700. Finally, the INAO ~60-year
oscillation well correlates with the ~60- year oscillations found in the
historical European aurora record since 1700, which suggests that this 60-year
dominant climatic cycle has a solar-astronomical origin
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