scholarly journals Phase Multistability of Dynamics Modes of the Ricker Model with Periodic Malthusian Parameter

2018 ◽  
Vol 13 (1) ◽  
pp. 68-83
Author(s):  
K.V. Shlufman ◽  
G.P. Neverova ◽  
E.Ya. Frisman
Keyword(s):  
Phase Shift ◽  
Dynamic Mode ◽  
Threshold Values ◽  
Attraction Basin ◽  
Malthusian Parameter ◽  
Ricker Model ◽  
Short Period ◽  
Tangent Bifurcation ◽  
Attraction Basins ◽  
Model Trajectory

The paper investigates the phase multistability of dynamical modes of the Ricker model with 2-year periodic Malthusian parameter. It is shown that both the variable perturbation and the phase shift of the Malthusian parameter can lead to a phase shift or a change in the dynamic mode observed. The possibility of switches between different dynamic modes is due to multistability, since the model has two different stable 2-cycles. The first stable 2-cycle is the result of transcritical bifurcation and is synchronous to the oscillations of the Malthusian parameter. The second stable 2-cycle arises as a result of the tangent bifurcation and is asynchronous to the oscillations of the Malthusian parameter. This indicates that two-year fluctuations in the population size can be both synchronous and asynchronous to the fluctuations in the environment. The phase shift of the Malthusian parameter causes a phase shift in the stable 4-cycle of the first bifurcation series to one or even three elements of the 4-cycle. The phase shift to two elements of this 4-cycle is possible due to a change in the half-amplitude of the Malthusian parameter oscillation or the variable perturbation. At the same time, the longer period of the cycle, the more phases with their attraction basins it has, and the smaller the threshold values above which shift from the attraction basin to another one occur. As a result, in the case of cycles with long period (for example, 8-cycle) perturbations, that stable cycles with short period are able to "absorb", can cause different phase transitions, which significantly complicates the dynamics of the model trajectory and, as a consequence, the identification of the dynamic mode observed.

scholarly journals Anatomy of the Attraction Basins: Breaking with the Intuition

2019 ◽  
Vol 27 (3) ◽  
pp. 435-466 ◽  
Author(s):  
Leticia Hernando ◽  
Alexander Mendiburu ◽  
Jose A. Lozano
Keyword(s):  
Combinatorial Optimization ◽  
Optimization Problems ◽  
Local Search Algorithms ◽  
Neighborhood Structure ◽  
Natural Landscape ◽  
Local Optima ◽  
Attraction Basin ◽  
Combinatorial Optimization Problems ◽  
New Findings ◽  
Attraction Basins

Solving combinatorial optimization problems efficiently requires the development of algorithms that consider the specific properties of the problems. In this sense, local search algorithms are designed over a neighborhood structure that partially accounts for these properties. Considering a neighborhood, the space is usually interpreted as a natural landscape, with valleys and mountains. Under this perception, it is commonly believed that, if maximizing, the solutions located in the slopes of the same mountain belong to the same attraction basin, with the peaks of the mountains being the local optima. Unfortunately, this is a widespread erroneous visualization of a combinatorial landscape. Thus, our aim is to clarify this aspect, providing a detailed analysis of, first, the existence of plateaus where the local optima are involved, and second, the properties that define the topology of the attraction basins, picturing a reliable visualization of the landscapes. Some of the features explored in this article have never been examined before. Hence, new findings about the structure of the attraction basins are shown. The study is focused on instances of permutation-based combinatorial optimization problems considering the 2-exchange and the insert neighborhoods. As a consequence of this work, we break away from the extended belief about the anatomy of attraction basins.

scholarly journals A Kaluza–Klein subtractor

2014 ◽  
Vol 29 (16) ◽  
pp. 1450079 ◽  
Author(s):  
Sanjib Jana ◽  
Chethan Krishnan
Keyword(s):  
Black Holes ◽  
Exact Solutions ◽  
Equations Of Motion ◽  
Specific Class ◽  
Attraction Basin ◽  
Rotating Black Holes ◽  
Klein Theory ◽  
Attraction Basins ◽  
Extremal Black Holes ◽  
Kaluza Klein

We generalize the results of arXiv:1212.1875 and arXiv:1212.6919 on attraction basins and their boundaries to the case of a specific class of rotating black holes, namely the ergo-free branch of extremal black holes in Kaluza–Klein theory. We find that exact solutions that span the attraction basin can be found even in the rotating case by appealing to certain symmetries of the equations of motion. They are characterized by two asymptotic parameters that generalize those of the non-rotating case, and the boundaries of the basin are spinning versions of the (generalized) subtractor geometry. We also give examples to illustrate that the shape of the attraction basin can drastically change depending on the theory.

scholarly journals Novel SH-SAW Biosensors for Ultra-Fast Recognition of Growth Factors

Biosensors ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 17
Author(s):  
Daniel Matatagui ◽  
Ágatha Bastida ◽  
M. Carmen Horrillo
Keyword(s):  
Growth Factors ◽  
Growth Factor ◽  
Test Time ◽  
Dynamic Mode ◽  
Label Free ◽  
Fast Recognition ◽  
Short Period ◽  
Wide Range ◽  
Total Test Time ◽  
Total Test

In this study, we investigated a label-free time efficient biosensor to recognize growth factors (GF) in real time, which are of gran interesting in the regulation of cell division and tissue proliferation. The sensor is based on a system of shear horizontal surface acoustic wave (SH-SAW) immunosensor combined with a microfluidic chip, which detects GF samples in a dynamic mode. In order to prove this method, to our knowledge not previously used for this type of compounds, two different GFs were tested by two immunoreactions: neurotrophin-3 and fibroblast growth factor-2 using its polyclonal antibodies. GF detection was conducted via an enhanced sequential workflow to improve total test time of the immunoassay, which shows that this type of biosensor is a very promising method for ultra-fast recognition of these biomolecules due to its great advantages: portability, simplicity of use, reusability, low cost, and detection within a relatively short period of time. Finally, the biosensor is able to detect FGF-2 growth factor in a concentration wide range, from 1–25 µg/mL, for a total test time of ~15 min with a LOD of 130 ng/mL.

scholarly journals Two-cycles of the Ricker model with the periodic Malthusian parameter: stability and multistability

2016 ◽  
pp. 553-565 ◽  
Author(s):  
К.В. Шлюфман ◽  
◽  
Г.П. Неверова ◽  
Е.Я. Фрисман ◽  
◽  
...  
Keyword(s):  
Malthusian Parameter ◽  
Parameter Stability ◽  
Ricker Model

scholarly journals Dynamic modes of the Ricker model with periodic Malthusian parameter

2017 ◽  
Vol 13 (3) ◽  
pp. 363-380 ◽  
Author(s):  
К.В. Шлюфман ◽  
◽  
Г.П. Неверова ◽  
Е.Я. Фрисман ◽  
◽  
...  
Keyword(s):  
Malthusian Parameter ◽  
Ricker Model

scholarly journals ldpA Encodes an Iron-Sulfur Protein Involved in Light-Dependent Modulation of the Circadian Period in the Cyanobacterium Synechococcuselongatus PCC 7942

2003 ◽  
Vol 185 (4) ◽  
pp. 1415-1422 ◽  
Author(s):  
Mitsunori Katayama ◽  
Takao Kondo ◽  
Jin Xiong ◽  
Susan S. Golden
Keyword(s):  
Phase Shift ◽  
Circadian Clock ◽  
Binding Motif ◽  
Circadian Period ◽  
Wild Type ◽  
Reading Frame ◽  
Short Period ◽  
Screening Protocol ◽  
Dark Pulse ◽  
Pcc 7942

ABSTRACT We generated random transposon insertion mutants to identify genes involved in light input pathways to the circadian clock of the cyanobacterium Synechococcus elongatus PCC 7942. Two mutants, AMC408-M1 and AMC408-M2, were isolated that responded to a 5-h dark pulse differently from the wild-type strain. The two mutants carried independent transposon insertions in an open reading frame here named ldpA (for light-dependent period). Although the mutants were isolated by a phase shift screening protocol, the actual defect is a conditional alteration in the circadian period. The mutants retain the wild-type ability to phase shift the circadian gene expression (bioluminescent reporter) rhythm if the timing of administration of the dark pulse is corrected for a 1-h shortening of the circadian period in the mutant. Further analysis indicated that the conditional short-period mutant phenotype results from insensitivity to light gradients that normally modulate the circadian period in S. elongatus, lengthening the period at low light intensities. The ldpA gene encodes a polypeptide that predicts a 7Fe-8S cluster-binding motif expected to be involved in redox reactions. We suggest that the LdpA protein modulates the circadian clock as an indirect function of light intensity by sensing changes in cellular physiology.

scholarly journals Prediction of the Optimal Vortex in Synthetic Jets

Energies ◽  
2019 ◽  
Vol 12 (9) ◽  
pp. 1635 ◽  
Author(s):  
Soledad Le Clainche
Keyword(s):  
Stokes Equations ◽  
Flow Patterns ◽  
Synthetic Jet ◽  
Synthetic Jets ◽  
Dynamic Mode Decomposition ◽  
Computational Time ◽  
Dynamic Mode ◽  
Short Period ◽  
Speed Up ◽  
Low Order

This article presents three different low-order models to predict the main flow patterns in synthetic jets. The first model provides a simple theoretical approach based on experimental solutions explaining how to artificially generate the optimal vortex, which maximizes the production of thrust and system efficiency. The second model is a data-driven method that uses higher-order dynamic mode decomposition (HODMD). To construct this model, (i) Navier–Stokes equations are solved for a very short period of time providing a transient solution, (ii) a group of spatio-temporal data are collected containing the information of the transitory of the numerical simulations, and finally (iii) HODMD decomposes the solution as a Fourier-like expansion of modes that are extrapolated in time, providing accurate predictions of the large size structures describing the general flow dynamics, with a speed-up factor of 8 . 3 in the numerical solver. The third model is an extension of the second model, which combines HODMD with a low-rank approximation of the spatial domain, which is based on singular value decomposition (SVD). This novel approach reduces the memory requirements by 70% and reduces the computational time to generate the low-order model by 3, maintaining the speed-up factor to 8 . 3 . This technique is suitable to predict the temporal flow patterns in a synthetic jet, showing that the general dynamics is driven by small amplitude variations along the streamwise direction. This new and efficient tool could also be potentially used for data forecasting or flow pattern identification in any type of big database.

scholarly journals Graphical Structure of Attraction Basins of Hidden Chaotic Attractors: The Rabinovich–Fabrikant System

2019 ◽  
Vol 29 (01) ◽  
pp. 1930001 ◽  
Author(s):  
Marius-F. Danca ◽  
Paul Bourke ◽  
Nikolay Kuznetsov
Keyword(s):  
Computer Graphic ◽  
Initial Conditions ◽  
Three Dimensions ◽  
Hidden Attractors ◽  
Attraction Basin ◽  
Graphic Analysis ◽  
Stable Equilibria ◽  
Attraction Basins ◽  
Graphical Structure ◽  
Advanced Computer

The attraction basin of hidden attractors does not intersect with small neighborhoods of any equilibrium point. To the best of our knowledge this property has not been explored using realtime interactive three-dimensions graphics. Aided by advanced computer graphic analysis, in this paper, we explore this characteristic of a particular nonlinear system with very rich and unusual dynamics, the Rabinovich–Fabrikant system. It is shown that there exists a neighborhood of one of the unstable equilibria within which the initial conditions do not lead to the considered hidden chaotic attractor, but to one of the stable equilibria or are divergent. The trajectories starting from any neighborhood of the other unstable equilibria are attracted either by the stable equilibria, or are divergent.

scholarly journals Coherent demodulation of the two-level APSK signals with the symbol amplitude estimation

2021 ◽  
Vol 2094 (2) ◽  
pp. 022050
Author(s):  
O V Chernoyarov ◽  
A N Glushkov ◽  
V P Litvinenko ◽  
V A Mironov ◽  
A V Salnikova
Keyword(s):  
Phase Shift ◽  
Phase Detector ◽  
Threshold Values ◽  
Coherent Demodulation ◽  
Amplitude Estimation ◽  
Multi Level ◽  
Digital Demodulation ◽  
Phase Demodulation

Abstract The study focuses on the algorithms for the coherent demodulation of the two-level amplitude phase-shift keyed signals with an estimate of the received symbol amplitude carried out by its relative comparison with the preceding symbol amplitude. Determining calibrated values of the symbol amplitudes in order to compare them with the preset threshold values is considered unnecessary in this case. Phase demodulation is implemented based on the phase detector of the multi-level phase-shift keyed signals. Symbol amplitudes are determined by the quadrature channels responses. Both analog and digital demodulation algorithms are considered. Simulation of the demodulation algorithm is carried out.

scholarly journals Unsupervised and Generic Short-Term Anticipation of Human Body Motions

Sensors ◽  
2020 ◽  
Vol 20 (4) ◽  
pp. 976
Author(s):  
Kristina Enes ◽  
Hassan Errami ◽  
Moritz Wolter ◽  
Tim Krake ◽  
Bernhard Eberhardt ◽  
...  
Keyword(s):  
Neural Network ◽  
Human Body ◽  
Dynamic Mode Decomposition ◽  
Dynamic Mode ◽  
Short Term ◽  
Linear Combinations ◽  
Mode Decomposition ◽  
The Neural Network ◽  
Short Period ◽  
The One

Various neural network based methods are capable of anticipating human body motions from data for a short period of time. What these methods lack are the interpretability and explainability of the network and its results. We propose to use Dynamic Mode Decomposition with delays to represent and anticipate human body motions. Exploring the influence of the number of delays on the reconstruction and prediction of various motion classes, we show that the anticipation errors in our results are comparable to or even better for very short anticipation times (<0.4 s) than a recurrent neural network based method. We perceive our method as a first step towards the interpretability of the results by representing human body motions as linear combinations of previous states and delays. In addition, compared to the neural network based methods large training times are not needed. Actually, our methods do not even regress to any other motions than the one to be anticipated and hence it is of a generic nature.

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