4,209 research outputs found
Optimal cellular mobility for synchronization arising from the gradual recovery of intercellular interactions
Cell movement and intercellular signaling occur simultaneously during the
development of tissues, but little is known about how movement affects
signaling. Previous theoretical studies have shown that faster moving cells
favor synchronization across a population of locally coupled genetic
oscillators. An important assumption in these studies is that cells can
immediately interact with their new neighbors after arriving at a new location.
However, intercellular interactions in cellular systems may need some time to
become fully established. How movement affects synchronization in this
situation has not been examined. Here we develop a coupled phase oscillator
model in which we consider cell movement and the gradual recovery of
intercellular coupling experienced by a cell after movement, characterized by a
moving rate and a coupling recovery rate respectively. We find (1) an optimal
moving rate for synchronization, and (2) a critical moving rate above which
achieving synchronization is not possible. These results indicate that the
extent to which movement enhances synchrony is limited by a gradual recovery of
coupling. These findings suggest that the ratio of time scales of movement and
signaling recovery is critical for information transfer between moving cells.Comment: 18 single column pages + 1 table + 5 figures + Supporting Informatio
Electrode current distributions in MGD CHANNELS
Current distribution to and electric field behavior of segmented electrodes in linear magnetogasdynamic generato
Sequential pattern formation governed by signaling gradients
Rhythmic and sequential segmentation of the embryonic body plan is a vital
developmental patterning process in all vertebrate species. However, a
theoretical framework capturing the emergence of dynamic patterns of gene
expression from the interplay of cell oscillations with tissue elongation and
shortening and with signaling gradients, is still missing. Here we show that a
set of coupled genetic oscillators in an elongating tissue that is regulated by
diffusing and advected signaling molecules can account for segmentation as a
self-organized patterning process. This system can form a finite number of
segments and the dynamics of segmentation and the total number of segments
formed depend strongly on kinetic parameters describing tissue elongation and
signaling molecules. The model accounts for existing experimental perturbations
to signaling gradients, and makes testable predictions about novel
perturbations. The variety of different patterns formed in our model can
account for the variability of segmentation between different animal species.Comment: 12 pages, 5 figure
The adequacy of the present practice in dynamic aggregated modelling of wind farm systems
Large offshore wind farms are usually composed of several hundred individual wind turbines, each turbine having its own complex set of dynamics. The analysis of the dynamic interaction between wind turbine generators (WTG), interconnecting ac cables, and voltage source converter (VSC) based High Voltage DC (HVDC) system is difficult because of the complexity and the scale of the entire system. The detailed modelling and modal analysis of a representative wind farm system reveal the presence of several critical resonant modes within the system. Several of these modes have frequencies close to harmonics of the power system frequency with poor damping. From a computational perspective the aggregation of the physical model is necessary in order to reduce the degree of complexity to a practical level. This paper focuses on the present practices of the aggregation of the WTGs and the collection system, and their influence on the damping and frequency characteristics of the critical oscillatory modes. The effect of aggregation on the critical modes are discussed using modal analysis and dynamic simulation. The adequacy of aggregation method is discussed
A framework for quantification and physical modeling of cell mixing applied to oscillator synchronization in vertebrate somitogenesis
In development and disease, cells move as they exchange signals. One example is found in vertebrate development, during which the timing of segment formation is set by a ‘segmentation clock’, in which oscillating gene expression is synchronized across a population of cells by Delta-Notch signaling. Delta-Notch signaling requires local cell-cell contact, but in the zebrafish embryonic tailbud, oscillating cells move rapidly, exchanging neighbors. Previous theoretical studies proposed that this relative movement or cell mixing might alter signaling and thereby enhance synchronization. However, it remains unclear whether the mixing timescale in the tissue is in the right range for this effect, because a framework to reliably measure the mixing timescale and compare it with signaling timescale is lacking. Here, we develop such a framework using a quantitative description of cell mixing without the need for an external reference frame and constructing a physical model of cell movement based on the data. Numerical simulations show that mixing with experimentally observed statistics enhances synchronization of coupled phase oscillators, suggesting that mixing in the tailbud is fast enough to affect the coherence of rhythmic gene expression. Our approach will find general application in analyzing the relative movements of communicating cells during development and disease.Fil: Uriu, Koichiro. Kanazawa University; JapónFil: Bhavna, Rajasekaran. Max Planck Institute of Molecular Cell Biology and Genetics; Alemania. Max Planck Institute for the Physics of Complex Systems; AlemaniaFil: Oates, Andrew C.. Francis Crick Institute; Reino Unido. University College London; Reino UnidoFil: Morelli, Luis Guillermo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigación en Biomedicina de Buenos Aires - Instituto Partner de la Sociedad Max Planck; Argentina. Max Planck Institute for Molecular Physiology; Alemania. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; Argentin
Nonlinearity arising from noncooperative transcription factor binding enhances negative feedback and promotes genetic oscillations
We study the effects of multiple binding sites in the promoter of a genetic
oscillator. We evaluate the regulatory function of a promoter with multiple
binding sites in the absence of cooperative binding, and consider different
hypotheses for how the number of bound repressors affects transcription rate.
Effective Hill exponents of the resulting regulatory functions reveal an
increase in the nonlinearity of the feedback with the number of binding sites.
We identify optimal configurations that maximize the nonlinearity of the
feedback. We use a generic model of a biochemical oscillator to show that this
increased nonlinearity is reflected in enhanced oscillations, with larger
amplitudes over wider oscillatory ranges. Although the study is motivated by
genetic oscillations in the zebrafish segmentation clock, our findings may
reveal a general principle for gene regulation.Comment: 11 pages, 8 figure
Synchronization in the presence of distributed delays
We study systems of identical coupled oscillators introducing a distribution
of delay times in the coupling. For arbitrary network topologies, we show that
the frequency and stability of the fully synchronized states depend only on the
mean of the delay distribution. However, synchronization dynamics is sensitive
to the shape of the distribution. In the presence of coupling delays, the
synchronization rate can be maximal for a specific value of the coupling
strength.Comment: 6 pages, 3 figure
GRB Flares: UV/Optical Flaring (Paper I)
We present a new algorithm for the detection of flares in gamma-ray burst
(GRB) light curves and use this algorithm to detect flares in the UV/optical.
The algorithm makes use of the Bayesian Information Criterion (BIC) to analyze
the residuals of the fitted light curve, removing all major features, and to
determine the statistically best fit to the data by iteratively adding
additional `breaks' to the light curve. These additional breaks represent the
individual components of the detected flares: T_start, T_stop, and T_peak. We
present the detection of 119 unique flaring periods detected by applying this
algorithm to light curves taken from the Second Swift Ultraviolet/Optical
Telescope (UVOT) GRB Afterglow Catalog. We analyzed 201 UVOT GRB light curves
and found episodes of flaring in 68 of the light curves. For those light curves
with flares, we find an average number of ~2 flares per GRB. Flaring is
generally restricted to the first 1000 seconds of the afterglow, but can be
observed and detected beyond 10^5 seconds. More than 80% of the flares detected
are short in duration with Delta t/t of < 0.5. Flares were observed with flux
ratios relative to the underlying light curve of between 0.04 to 55.42. Many of
the strongest flares were also seen at greater than 1000 seconds after the
burst.Comment: Submitted to ApJ. 20 pages (including 8 figures and 1 table
Indenture, Marshall County, 12 December 1850
https://egrove.olemiss.edu/aldrichcorr_b/1268/thumbnail.jp
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