4,209 research outputs found

    Optimal cellular mobility for synchronization arising from the gradual recovery of intercellular interactions

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    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

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    Current distribution to and electric field behavior of segmented electrodes in linear magnetogasdynamic generato

    Sequential pattern formation governed by signaling gradients

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    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

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    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

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    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

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    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

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    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)

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    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

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    https://egrove.olemiss.edu/aldrichcorr_b/1268/thumbnail.jp
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