3,722 research outputs found
Quantifying sudden changes in dynamical systems using symbolic networks
We characterise the evolution of a dynamical system by combining two
well-known complex systems' tools, namely, symbolic ordinal analysis and
networks. From the ordinal representation of a time-series we construct a
network in which every node weights represents the probability of an ordinal
patterns (OPs) to appear in the symbolic sequence and each edges weight
represents the probability of transitions between two consecutive OPs. Several
network-based diagnostics are then proposed to characterize the dynamics of
different systems: logistic, tent and circle maps. We show that these
diagnostics are able to capture changes produced in the dynamics as a control
parameter is varied. We also apply our new measures to empirical data from
semiconductor lasers and show that they are able to anticipate the polarization
switchings, thus providing early warning signals of abrupt transitions.Comment: 18 pages, 9 figures, to appear in New Journal of Physic
Detection of Side Chain Rearrangements Mediating the Motions of Transmembrane Helices in Molecular Dynamics Simulations of G Protein-Coupled Receptors.
Structure and dynamics are essential elements of protein function. Protein structure is constantly fluctuating and undergoing conformational changes, which are captured by molecular dynamics (MD) simulations. We introduce a computational framework that provides a compact representation of the dynamic conformational space of biomolecular simulations. This method presents a systematic approach designed to reduce the large MD simulation spatiotemporal datasets into a manageable set in order to guide our understanding of how protein mechanics emerge from side chain organization and dynamic reorganization. We focus on the detection of side chain interactions that undergo rearrangements mediating global domain motions and vice versa. Side chain rearrangements are extracted from side chain interactions that undergo well-defined abrupt and persistent changes in distance time series using Gaussian mixture models, whereas global domain motions are detected using dynamic cross-correlation. Both side chain rearrangements and global domain motions represent the dynamic components of the protein MD simulation, and are both mapped into a network where they are connected based on their degree of coupling. This method allows for the study of allosteric communication in proteins by mapping out the protein dynamics into an intramolecular network to reduce the large simulation data into a manageable set of communities composed of coupled side chain rearrangements and global domain motions. This computational framework is suitable for the study of tightly packed proteins, such as G protein-coupled receptors, and we present an application on a seven microseconds MD trajectory of CC chemokine receptor 7 (CCR7) bound to its ligand CCL21
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
Statistical Mechanics and Information-Theoretic Perspectives on Complexity in the Earth System
Peer reviewedPublisher PD
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