66,725 research outputs found
Graph theoretical approaches for the characterization of damage in hierarchical materials
We discuss the relevance of methods of graph theory for the study of damage
in simple model materials described by the random fuse model. While such
methods are not commonly used when dealing with regular random lattices, which
mimic disordered but statistically homogeneous materials, they become relevant
in materials with microstructures that exhibit complex multi-scale patterns. We
specifically address the case of hierarchical materials, whose failure, due to
an uncommon fracture mode, is not well described in terms of either damage
percolation or crack nucleation-and-growth. We show that in these systems,
incipient failure is accompanied by an increase in eigenvector localization and
a drop in topological dimension. We propose these two novel indicators as
possible candidates to monitor a system in the approach to failure. As such,
they provide alternatives to monitoring changes in the precursory avalanche
activity, which is often invoked as a candidate for failure prediction in
materials which exhibit critical-like behavior at failure, but may not work in
the context of hierarchical materials which exhibit scale-free avalanche
statistics even very far from the critical load.Comment: 12 pages, 6 figure
Fractals in the Nervous System: conceptual Implications for Theoretical Neuroscience
This essay is presented with two principal objectives in mind: first, to
document the prevalence of fractals at all levels of the nervous system, giving
credence to the notion of their functional relevance; and second, to draw
attention to the as yet still unresolved issues of the detailed relationships
among power law scaling, self-similarity, and self-organized criticality. As
regards criticality, I will document that it has become a pivotal reference
point in Neurodynamics. Furthermore, I will emphasize the not yet fully
appreciated significance of allometric control processes. For dynamic fractals,
I will assemble reasons for attributing to them the capacity to adapt task
execution to contextual changes across a range of scales. The final Section
consists of general reflections on the implications of the reviewed data, and
identifies what appear to be issues of fundamental importance for future
research in the rapidly evolving topic of this review
Temporal Taylor's scaling of facial electromyography and electrodermal activity in the course of emotional stimulation
High frequency psychophysiological data create a challenge for quantitative
modeling based on Big Data tools since they reflect the complexity of processes
taking place in human body and its responses to external events. Here we
present studies of fluctuations in facial electromyography (fEMG) and
electrodermal activity (EDA) massive time series and changes of such signals in
the course of emotional stimulation. Zygomaticus major (ZYG, "smiling" muscle)
activity, corrugator supercilii (COR, "frowning"bmuscle) activity, and phasic
skin conductance (PHSC, sweating) levels of 65 participants were recorded
during experiments that involved exposure to emotional stimuli (i.e., IAPS
images, reading and writing messages on an artificial online discussion board).
Temporal Taylor's fluctuations scaling were found when signals for various
participants and during various types of emotional events were compared. Values
of scaling exponents were close to 1, suggesting an external origin of system
dynamics and/or strong interactions between system's basic elements (e.g.,
muscle fibres). Our statistical analysis shows that the scaling exponents
enable identification of high valence and arousal levels in ZYG and COR
signals
Dragon-kings: mechanisms, statistical methods and empirical evidence
This introductory article presents the special Discussion and Debate volume
"From black swans to dragon-kings, is there life beyond power laws?" published
in Eur. Phys. J. Special Topics in May 2012. We summarize and put in
perspective the contributions into three main themes: (i) mechanisms for
dragon-kings, (ii) detection of dragon-kings and statistical tests and (iii)
empirical evidence in a large variety of natural and social systems. Overall,
we are pleased to witness significant advances both in the introduction and
clarification of underlying mechanisms and in the development of novel
efficient tests that demonstrate clear evidence for the presence of
dragon-kings in many systems. However, this positive view should be balanced by
the fact that this remains a very delicate and difficult field, if only due to
the scarcity of data as well as the extraordinary important implications with
respect to hazard assessment, risk control and predictability.Comment: 20 page
Characterization and Modeling of weighted networks
We review the main tools which allow for the statistical characterization of
weighted networks. We then present two case studies, the airline connection
network and the scientific collaboration network, which are representative of
critical infrastructures and social systems, respectively. The main empirical
results are (i) the broad distributions of various quantities and (ii) the
existence of weight-topology correlations. These measurements show that weights
are relevant and that in general the modeling of complex networks must go
beyond topology. We review a model which provides an explanation for the
features observed in several real-world networks. This model of weighted
network formation relies on the dynamical coupling between topology and
weights, considering the rearrangement of weights when new links are introduced
in the system.Comment: Proceedings of the conference "Complex networks: structure, function
and processes", Kolkata (Satellite Meeting of STATPHYS 22), to be published
in Physica
Current challenges for preseismic electromagnetic emissions: shedding light from micro-scale plastic flow, granular packings, phase transitions and self-affinity notion of fracture process
Are there credible electromagnetic (EM) EQ precursors? This a question
debated in the scientific community and there may be legitimate reasons for the
critical views. The negative view concerning the existence of EM precursors is
enhanced by features that accompany their observation which are considered as
paradox ones, namely, these signals: (i) are not observed at the time of EQs
occurrence and during the aftershock period, (ii) are not accompanied by large
precursory strain changes, (iii) are not accompanied by simultaneous geodetic
or seismological precursors and (v) their traceability is considered
problematic. In this work, the detected candidate EM precursors are studied
through a shift in thinking towards the basic science findings relative to
granular packings, micron-scale plastic flow, interface depinning, fracture
size effects, concepts drawn from phase transitions, self-affine notion of
fracture and faulting process, universal features of fracture surfaces, recent
high quality laboratory studies, theoretical models and numerical simulations.
Strict criteria are established for the definition of an emerged EM anomaly as
a preseismic one, while, precursory EM features, which have been considered as
paradoxes, are explained. A three-stage model for EQ generation by means of
preseismic fracture-induced EM emissions is proposed. The claim that the
observed EM precursors may permit a real-time and step-by-step monitoring of
the EQ generation is tested
Influence of Behavioral Models on Multiuser Channel Capacity
In order to characterize the channel capacity of a wavelength channel in a
wavelength-division multiplexed (WDM) system, statistical models are needed for
the transmitted signals on the other wavelengths. For example, one could assume
that the transmitters for all wavelengths are configured independently of each
other, that they use the same signal power, or that they use the same
modulation format. In this paper, it is shown that these so-called behavioral
models have a profound impact on the single-wavelength achievable information
rate. This is demonstrated by establishing, for the first time, upper and lower
bounds on the maximum achievable rate under various behavioral models, for a
rudimentary WDM channel model
The Small World of Osteocytes: Connectomics of the Lacuno-Canalicular Network in Bone
Osteocytes and their cell processes reside in a large, interconnected network
of voids pervading the mineralized bone matrix of most vertebrates. This
osteocyte lacuno-canalicular network (OLCN) is believed to play important roles
in mechanosensing, mineral homeostasis, and for the mechanical properties of
bone. While the extracellular matrix structure of bone is extensively studied
on ultrastructural and macroscopic scales, there is a lack of quantitative
knowledge on how the cellular network is organized. Using a recently introduced
imaging and quantification approach, we analyze the OLCN in different bone
types from mouse and sheep that exhibit different degrees of structural
organization not only of the cell network but also of the fibrous matrix
deposited by the cells. We define a number of robust, quantitative measures
that are derived from the theory of complex networks. These measures enable us
to gain insights into how efficient the network is organized with regard to
intercellular transport and communication. Our analysis shows that the cell
network in regularly organized, slow-growing bone tissue from sheep is less
connected, but more efficiently organized compared to irregular and
fast-growing bone tissue from mice. On the level of statistical topological
properties (edges per node, edge length and degree distribution), both network
types are indistinguishable, highlighting that despite pronounced differences
at the tissue level, the topological architecture of the osteocyte canalicular
network at the subcellular level may be independent of species and bone type.
Our results suggest a universal mechanism underlying the self-organization of
individual cells into a large, interconnected network during bone formation and
mineralization
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