scholarly journals Real-time dynamics of typical and untypical states in nonintegrable systems

2018 ◽  
Vol 97 (17) ◽  
Author(s):  
Jonas Richter ◽  
Fengping Jin ◽  
Hans De Raedt ◽  
Kristel Michielsen ◽  
Jochen Gemmer ◽  
...  
Keyword(s):  
Real Time ◽  
Time Dynamics ◽  
Nonintegrable Systems

scholarly journals Real-time dynamics in the one-dimensional Hubbard model

2014 ◽  
Vol 90 (24) ◽  
Author(s):  
Luis Seabra ◽  
Fabian H. L. Essler ◽  
Frank Pollmann ◽  
Imke Schneider ◽  
Thomas Veness
Keyword(s):  
Hubbard Model ◽  
Real Time ◽  
One Dimensional ◽  
Time Dynamics ◽  
The One

scholarly journals Computer Algebra for Real-Time Dynamics of Robots with Large Numbers of Joints

2004 ◽  
pp. 278-285 ◽  
Author(s):  
Ramutis Bansevicius ◽  
Algimantas Cepulkauskas ◽  
Regina Kulvietiene ◽  
Genadijus Kulvietis
Keyword(s):  
Real Time ◽  
Computer Algebra ◽  
Time Dynamics ◽  
Large Numbers

scholarly journals Infrared Spectroscopy Coupled with a Dispersion Model for Quantifying the Real-Time Dynamics of Kanamycin Resistance in Artificial Microbiota

2017 ◽  
Vol 89 (18) ◽  
pp. 9814-9821 ◽  
Author(s):  
Naifu Jin ◽  
Maria Paraskevaidi ◽  
Kirk T. Semple ◽  
Francis L. Martin ◽  
Dayi Zhang
Keyword(s):  
Infrared Spectroscopy ◽  
Real Time ◽  
Dispersion Model ◽  
Kanamycin Resistance ◽  
The Real ◽  
Time Dynamics

scholarly journals Real‐Time Dynamics of Translation

2012 ◽  
Vol 26 (S1) ◽  
Author(s):  
Joseph Daniel Puglisi ◽  
Jin Chen ◽  
Guy Kornberg ◽  
Sean O'Leary ◽  
Alexey Petrov ◽  
...  
Keyword(s):  
Real Time ◽  
Time Dynamics

scholarly journals Learning In Spike Trains: Estimating Within-Session Changes In Firing Rate Using Weighted Interpolation

2016 ◽  
Author(s):  
Greg Jensen ◽  
Fabian Muñoz ◽  
Vincent P. Ferrera
Keyword(s):  
Real Time ◽  
Electrophysiological Study ◽  
Monte Carlo Algorithm ◽  
Small Samples ◽  
Weighted Interpolation ◽  
Time Dynamics ◽  
Firing Rates ◽  
The Past ◽  
Time Estimates ◽  
Quantitative Procedure

AbstractThe electrophysiological study of learning is hampered by modern procedures for estimating firing rates: Such procedures usually require large datasets, and also require that included trials be functionally identical. Unless a method can track the real-time dynamics of how firing rates evolve, learning can only be examined in the past tense. We propose a quantitative procedure, called ARRIS, that can uncover trial-by-trial firing dynamics. ARRIS provides reliable estimates of firing rates based on small samples using the reversible-jump Markov chain Monte Carlo algorithm. Using weighted interpolation, ARRIS can also provide estimates that evolve over time. As a result, both real-time estimates of changing activity, and of task-dependent tuning, can be obtained during the initial stages of learning.

scholarly journals Real-time dynamics of mutagenesis reveal the chronology of DNA repair and damage tolerance responses in single cells

2018 ◽  
Vol 115 (28) ◽  
pp. E6516-E6525 ◽  
Author(s):  
Stephan Uphoff
Keyword(s):  
Dna Repair ◽  
Real Time ◽  
Molecular Mechanisms ◽  
Damage Tolerance ◽  
Single Cells ◽  
Dna Alkylation ◽  
Alkylation Damage ◽  
Time Dynamics ◽  
Dna Mismatches ◽  
The Creation

Evolutionary processes are driven by diverse molecular mechanisms that act in the creation and prevention of mutations. It remains unclear how these mechanisms are regulated because limitations of existing mutation assays have precluded measuring how mutation rates vary over time in single cells. Toward this goal, I detected nascent DNA mismatches as a proxy for mutagenesis and simultaneously followed gene expression dynamics in single Escherichia coli cells using microfluidics. This general microscopy-based approach revealed the real-time dynamics of mutagenesis in response to DNA alkylation damage and antibiotic treatments. It also enabled relating the creation of DNA mismatches to the chronology of the underlying molecular processes. By avoiding population averaging, I discovered cell-to-cell variation in mutagenesis that correlated with heterogeneity in the expression of alternative responses to DNA damage. Pulses of mutagenesis are shown to arise from transient DNA repair deficiency. Constitutive expression of DNA repair pathways and induction of damage tolerance by the SOS response compensate for delays in the activation of inducible DNA repair mechanisms, together providing robustness against the toxic and mutagenic effects of DNA alkylation damage.

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