111 research outputs found
Climate Dynamics: A Network-Based Approach for the Analysis of Global Precipitation
Precipitation is one of the most important meteorological variables for defining the climate dynamics, but the spatial patterns of precipitation have not been fully investigated yet. The complex network theory, which provides a robust tool to investigate the statistical interdependence of many interacting elements, is used here to analyze the spatial dynamics of annual precipitation over seventy years (1941-2010). The precipitation network is built associating a node to a geographical region, which has a temporal distribution of precipitation, and identifying possible links among nodes through the correlation function. The precipitation network reveals significant spatial variability with barely connected regions, as Eastern China and Japan, and highly connected regions, such as the African Sahel, Eastern Australia and, to a lesser extent, Northern Europe. Sahel and Eastern Australia are remarkably dry regions, where low amounts of rainfall are uniformly distributed on continental scales and small-scale extreme events are rare. As a consequence, the precipitation gradient is low, making these regions well connected on a large spatial scale. On the contrary, the Asiatic South-East is often reached by extreme events such as monsoons, tropical cyclones and heat waves, which can all contribute to reduce the correlation to the short-range scale only. Some patterns emerging between mid-latitude and tropical regions suggest a possible impact of the propagation of planetary waves on precipitation at a global scale. Other links can be qualitatively associated to the atmospheric and oceanic circulation. To analyze the sensitivity of the network to the physical closeness of the nodes, short-term connections are broken. The African Sahel, Eastern Australia and Northern Europe regions again appear as the supernodes of the network, confirming furthermore their long-range connection structure. Almost all North-American and Asian nodes vanish, revealing that extreme events can enhance high precipitation gradients, leading to a systematic absence of long-range patterns
Characterization of a Si(Li) Compton polarimeter for the hard x-ray regime, using synchrotron radiation.
BACKGROUND: Buruli ulcer (BU), caused by Mycobacterium ulcerans (M. ulcerans), is a necrotizing skin disease found in more than 30 countries worldwide. BU incidence is highest in West Africa; however, cases have substantially increased in coastal regions of southern Australia over the past 30 years. Although the mode of transmission remains uncertain, the spatial pattern of BU emergence in recent years seems to suggest that there is an environmental niche for M. ulcerans and BU prevalence. METHODOLOGY/PRINCIPAL FINDINGS: Network analysis was applied to BU cases in Victoria, Australia, from 1981-2008. Results revealed a non-random spatio-temporal pattern at the regional scale as well as a stable and efficient BU disease network, indicating that deterministic factors influence the occurrence of this disease. Monthly BU incidence reported by locality was analyzed with landscape and climate data using a multilevel Poisson regression approach. The results suggest the highest BU risk areas occur at low elevations with forested land cover, similar to previous studies of BU risk in West Africa. Additionally, climate conditions as far as 1.5 years in advance appear to impact disease incidence. Warmer and wetter conditions 18-19 months prior to case emergence, followed by a dry period approximately 5 months prior to case emergence seem to favor the occurrence of BU. CONCLUSIONS/SIGNIFICANCE: The BU network structure in Victoria, Australia, suggests external environmental factors favor M. ulcerans transmission and, therefore, BU incidence. A unique combination of environmental conditions, including land cover type, temperature and a wet-dry sequence, may produce habitat characteristics that support M. ulcerans transmission and BU prevalence. These findings imply that future BU research efforts on transmission mechanisms should focus on potential vectors/reservoirs found in those environmental niches. Further, this study is the first to quantitatively estimate environmental lag times associated with BU outbreaks, providing insights for future transmission investigations
Statistical Laws Governing Fluctuations in Word Use from Word Birth to Word Death
We analyze the dynamic properties of 10^7 words recorded in English, Spanish
and Hebrew over the period 1800--2008 in order to gain insight into the
coevolution of language and culture. We report language independent patterns
useful as benchmarks for theoretical models of language evolution. A
significantly decreasing (increasing) trend in the birth (death) rate of words
indicates a recent shift in the selection laws governing word use. For new
words, we observe a peak in the growth-rate fluctuations around 40 years after
introduction, consistent with the typical entry time into standard dictionaries
and the human generational timescale. Pronounced changes in the dynamics of
language during periods of war shows that word correlations, occurring across
time and between words, are largely influenced by coevolutionary social,
technological, and political factors. We quantify cultural memory by analyzing
the long-term correlations in the use of individual words using detrended
fluctuation analysis.Comment: Version 1: 31 pages, 17 figures, 3 tables. Version 2 is streamlined,
eliminates substantial material and incorporates referee comments: 19 pages,
14 figures, 3 table
Local Difference Measures between Complex Networks for Dynamical System Model Evaluation
Acknowledgments We thank Reik V. Donner for inspiring suggestions that initialized the work presented herein. Jan H. Feldhoff is credited for providing us with the STARS simulation data and for his contributions to fruitful discussions. Comments by the anonymous reviewers are gratefully acknowledged as they led to substantial improvements of the manuscript.Peer reviewedPublisher PD
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Fractal Dimension Analysis of Transient Visual Evoked Potentials: Optimisation and Applications
Purpose
The visual evoked potential (VEP) provides a time series signal response to an external visual stimulus at the location of the visual cortex. The major VEP signal components, peak latency and amplitude, may be affected by disease processes. Additionally, the VEP contains fine detailed and non-periodic structure, of presently unclear relevance to normal function, which may be quantified using the fractal dimension. The purpose of this study is to provide a systematic investigation of the key parameters in the measurement of the fractal dimension of VEPs, to develop an optimal analysis protocol for application.
Methods
VEP time series were mathematically transformed using delay time, Ï, and embedding dimension, m, parameters. The fractal dimension of the transformed data was obtained from a scaling analysis based on straight line fits to the numbers of pairs of points with separation less than r versus log(r) in the transformed space. Optimal Ï, m, and scaling analysis were obtained by comparing the consistency of results using different sampling frequencies. The optimised method was then piloted on samples of normal and abnormal VEPs.
Results
Consistent fractal dimension estimates were obtained using Ï = 4 ms, designating the fractal dimension = D2 of the time series based on embedding dimension m = 7 (for 3606 Hz and 5000 Hz), m = 6 (for 1803 Hz) and m = 5 (for 1000Hz), and estimating D2 for each embedding dimension as the steepest slope of the linear scaling region in the plot of log(C(r)) vs log(r) provided the scaling region occurred within the middle third of the plot. Piloting revealed that fractal dimensions were higher from the sampled abnormal than normal achromatic VEPs in adults (p = 0.02). Variances of fractal dimension were higher from the abnormal than normal chromatic VEPs in children (p = 0.01).
Conclusions
A useful analysis protocol to assess the fractal dimension of transformed VEPs has been developed
Localizing triplet periodicity in DNA and cDNA sequences
<p>Abstract</p> <p>Background</p> <p>The protein-coding regions (coding exons) of a DNA sequence exhibit a triplet periodicity (TP) due to fact that coding exons contain a series of three nucleotide codons that encode specific amino acid residues. Such periodicity is usually not observed in introns and intergenic regions. If a DNA sequence is divided into small segments and a Fourier Transform is applied on each segment, a strong peak at frequency 1/3 is typically observed in the Fourier spectrum of coding segments, but not in non-coding regions. This property has been used in identifying the locations of protein-coding genes in unannotated sequence. The method is fast and requires no training. However, the need to compute the Fourier Transform across a segment (window) of arbitrary size affects the accuracy with which one can localize TP boundaries. Here, we report a technique that provides higher-resolution identification of these boundaries, and use the technique to explore the biological correlates of TP regions in the genome of the model organism <it>C. elegans</it>.</p> <p>Results</p> <p>Using both simulated TP signals and the real <it>C. elegans </it>sequence F56F11 as an example, we demonstrate that, (1) Modified Wavelet Transform (MWT) can better define the boundary of TP region than the conventional Short Time Fourier Transform (STFT); (2) The scale parameter (a) of MWT determines the precision of TP boundary localization: bigger values of a give sharper TP boundaries but result in a lower signal to noise ratio; (3) RNA splicing sites have weaker TP signals than coding region; (4) TP signals in coding region can be destroyed or recovered by frame-shift mutations; (5) 6 bp periodicities in introns and intergenic region can generate false positive signals and it can be removed with 6 bp MWT.</p> <p>Conclusions</p> <p>MWT can provide more precise TP boundaries than STFT and the boundaries can be further refined by bigger scale MWT. Subtraction of 6 bp periodicity signals reduces the number of false positives. Experimentally-introduced frame-shift mutations help recover TP signal that have been lost by possible ancient frame-shifts. More importantly, TP signal has the potential to be used to detect the splice junctions in fully spliced mRNA sequence.</p
Dynamic Community Detection into Analyzing of Wildfires Events
The study and comprehension of complex systems are crucial intellectual and
scientific challenges of the 21st century. In this scenario, network science
has emerged as a mathematical tool to support the study of such systems.
Examples include environmental processes such as wildfires, which are known for
their considerable impact on human life. However, there is a considerable lack
of studies of wildfire from a network science perspective. Here, employing the
chronological network concept -- a temporal network where nodes are linked if
two consecutive events occur between them -- we investigate the information
that dynamic community structures reveal about the wildfires' dynamics.
Particularly, we explore a two-phase dynamic community detection approach,
i.e., we applied the Louvain algorithm on a series of snapshots. Then we used
the Jaccard similarity coefficient to match communities across adjacent
snapshots. Experiments with the MODIS dataset of fire events in the Amazon
basing were conducted. Our results show that the dynamic communities can reveal
wildfire patterns observed throughout the year.Comment: 16 pages, 8 figure
Languages cool as they expand: Allometric scaling and the decreasing need for new words
We analyze the occurrence frequencies of over 15 million words recorded in millions of books published during the past two centuries in seven different languages. For all languages and chronological subsets of the data we confirm that two scaling regimes characterize the word frequency distributions, with only the more common words obeying the classic Zipf law. Using corpora of unprecedented size, we test the allometric scaling relation between the corpus size and the vocabulary size of growing languages to demonstrate a decreasing marginal need for new words, a feature that is likely related to the underlying correlations between words. We calculate the annual growth fluctuations of word use which has a decreasing trend as the corpus size increases, indicating a slowdown in linguistic evolution following language expansion. This ââcooling patternââ forms the basis of a third statistical regularity, which unlike the Zipf and the Heaps law, is dynamical in nature
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
Complex networks for climate model evaluation with application to statistical versus dynamical modeling of South American climate
Acknowledgments: This paper was developed within the scope of the IRTG 1740/TRP 2011/50151-0, funded by the DFG/FAPESP. Furthermore, this work has been financially supported by the Leibniz Society (project ECONS), and the Stordalen Foundation (JFD). For certain calculations, the software packages pyunicorn (Donges et al. 2013a) and igraph (CsaÂŽrdi and Nepusz 2006) were used. The authors would like to thank Manoel F. Cardoso, Niklas Boers, and the reviewers for helpful comments on the manuscript. Open Access: This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.Peer reviewedPostprin
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