Evans function analysis of the stability of non-adiabatic flames

2003 ◽  
Vol 7 (3) ◽  
pp. 545-561 ◽  
Author(s):  
Peter L Simon ◽  
Serafim Kalliadasis ◽  
John H Merkin ◽  
Stephen K Scott
Keyword(s):  
Function Analysis ◽  
Evans Function ◽  
The Stability

scholarly journals CSIG-22. CANCER-ASSOCIATED MISSENSE SINGLE NUCLEOTIDE VARIANTS REGULATE THE STABILITY AND SUBCELLULAR LOCALIZATION OF NF2/MERLIN

2020 ◽  
Vol 22 (Supplement_2) ◽  
pp. ii32-ii32
Author(s):  
Charlotte Eaton ◽  
Paola Bisignano ◽  
David Raleigh
Keyword(s):  
Tumor Suppressor ◽  
Subcellular Localization ◽  
Function Analysis ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Ferm Domain ◽  
Binding Partners ◽  
Subcellular Compartments ◽  
The Stability ◽  
The Impact

Abstract BACKGROUND Alterations in the NF2 tumor suppressor gene lead to meningiomas and schwannomas, but the tumor suppressor functions of the NF2 gene product, Merlin, are incompletely understood. To address this problem, we performed a structure-function analysis of Merlin by expressing cancer-associated missense single-nucleotide variants (mSNVs) in primary cancer cells for biochemical and cell biology experiments. METHODS All NF2 mSNVs were assembled from cBioPortal and COSMIC, and modelled on the FERM, a-helical, and C-terminal domains of Merlin (PDB 4ZRJ) using comparative structure prediction on the Robetta server and visually inspected using Pymol. mSNV hotspots were defined from sliding windows with at least 10 mutations within 5 residues in either direction. mSNVs from hotspots in meningiomas, schwannomas, or both, were selected for in vitro mechanistic analyses using immunofluorescence and immunoblotting of whole cell, plasma membrane, cytoskeletal, cytoplasmic, nuclear, and chromatin subcellular fractions from M10G meningioma cells and HEI-193 schwannoma cells. RESULTS We identified the following cancer-associated hotspot mSNVs in NF2, which were over-expressed for mechanistic studies: L46R, S156N, W191R, A211D, V219M, R418C and R462K. Endogenous Merlin was detected in all subcellular compartments, but was enriched in the nucleus. L46R and A211D mapped to hydrophobic pockets in the FERM domain, destabilized Merlin, and excluded Merlin from all subcellular compartments except the cytoskeleton. S156N, W191R and V219M also mapped to the FERM domain, but did not affect Merlin stability, and V219M attenuated chromatin localization, suggesting this motif may be involved in binding events that regulate subcellular localization. R418C and R463K mapped to the a-helical domain, but only R418C destabilized Merlin. CONCLUSION Our results suggest that cancer-associated mSNVs inactive the tumor suppressor functions of NF2 by altering the stability, subcellular localization, or binding partners of Merlin. Further work is required to identify and understand the impact of binding partners and subcellular localization on Merlin function.

Stability Behavior of Model Reference Adaptive Control Methods in Presence of Aircraft Structural Damage

2007 ◽  
Author(s):  
Pascal Nespeca ◽  
Nesrin Sarigul-Klijn
Keyword(s):  
Adaptive Control ◽  
Numerical Study ◽  
Function Analysis ◽  
Model Reference Adaptive Control ◽  
Approximation Technique ◽  
Control Methods ◽  
Model Reference ◽  
Stability Behavior ◽  
The Stability ◽  
Model Reference Adaptive

Any classical control design starts by first satisfying stability and then looking towards satisfying transient requirements. Similarly, a Model Reference Adaptive Control (MRAC) Method should start with a stability analysis. Lyapunov function analysis is first used to justify the stability of the adaptive scheme. Next, a numerical study is conducted to predict the stability behavior of three different MRAC methods in the presence of large unanticipated changes in the dynamics of an aircraft. The Model reference adaptive control methods studied are: Method:1, an adaptive gain method; Method:2, a Neural Network (NN) approximation technique; and, Method:3, a linear approximation technique. For comparison purposes, the aircraft is assumed to have Linear Time Invariant, LTI dynamics. Each algorithm is given full state feedback, an inaccurate reference model and a poor Linear Quadratic Regulator, LQR design for the true plant. It is seen that when the LQR stabilizes the true plant, the three algorithms all achieve the same steady state error to a step command. Numerical results predict the different types of stability behavior that the algorithms provide. It is seen that the Methods: 2 and 3 can only provide a bounded stability, whereas Method: 1 can provide an asymptotic stability. A robust static controller can satisfy stability, but a robust static controller that accommodates variations in plant dynamics might not always be able to match transient requirements as expected. Although there may be no analytical guarantee from adaptive controllers of transient performance, one might look at anecdotal performances.

A stability index for travelling waves in activator-inhibitor systems

2019 ◽  
Vol 150 (1) ◽  
pp. 517-548
Author(s):  
Paul Cornwell ◽  
Christopher K. R. T. Jones
Keyword(s):  
Eigenvalue Problem ◽  
Symplectic Form ◽  
Travelling Waves ◽  
Stability Index ◽  
Maslov Index ◽  
Evans Function ◽  
Conjugate Points ◽  
Spatial Evolution ◽  
The Stability ◽  
Activator Inhibitor

AbstractWe consider the stability of nonlinear travelling waves in a class of activator-inhibitor systems. The eigenvalue equation arising from linearizing about the wave is seen to preserve the manifold of Lagrangian planes for a nonstandard symplectic form. This allows us to define a Maslov index for the wave corresponding to the spatial evolution of the unstable bundle. We formulate the Evans function for the eigenvalue problem and show that the parity of the Maslov index determines the sign of the derivative of the Evans function at the origin. The connection between the Evans function and the Maslov index is established by a ‘detection form,’ which identifies conjugate points for the curve of Lagrangian planes.

Structure - function analysis of photosystem II subunit S (PsbS) in vivo

2002 ◽  
Vol 29 (10) ◽  
pp. 1131 ◽  
Author(s):  
Xiao-Ping Li ◽  
Alba Phippard ◽  
Jae Pasari ◽  
Krishna K. Niyogi
Keyword(s):  
Amino Acid ◽  
Photosystem Ii ◽  
Function Analysis ◽  
Amino Acid Sequences ◽  
Forward Genetics ◽  
Photochemical Quenching ◽  
Amino Acid Residues ◽  
The Stability ◽  
Psbs Gene

In land plants, photosystem II subunit S (PsbS) plays a key role in xanthophyll- and pH-dependent non-photochemical quenching (qE) of excess absorbed light energy. Arabidopsis thaliana (L.) Heynh. npq4 mutants are defective in the psbS gene and have impaired qE. Exactly how the PsbS protein is involved in qE is unclear, but it has been proposed that PsbS binds H+ and/or de-epoxidized xanthophylls in excess light as part of the qE mechanism. To identify amino acid residues that are important for PsbS function, we sequenced the psbS gene from eight npq4 point mutant alleles isolated by forward genetics screening, including two new alleles. In the four transmembrane helices of PsbS, several amino acid residues were found to affect the stability and/or function of the protein. By comparing the predicted amino acid sequences of PsbS from several plant species and studying the proposed topological structure of PsbS, eight possible H+-binding amino acid residues on the lumenal side of the protein were identified and then altered by site-directed mutagenesis in vitro. The mutant psbS genes were transformed into npq4-1, a psbS deletion mutant, to test the stability and function of the mutant PsbS proteins in�vivo. The results demonstrate that two conserved, protonatable amino acids, E122 and E226, are especially critical for the function of PsbS.

scholarly journals Reconstitution of the Jasmonate Signaling Pathway in Plant Protoplasts

Cells ◽  
2019 ◽  
Vol 8 (12) ◽  
pp. 1532 ◽  
Author(s):  
Ning Li ◽  
Joachim F. Uhrig ◽  
Corinna Thurow ◽  
Li-Jun Huang ◽  
Christiane Gatz
Keyword(s):  
Signaling Pathway ◽  
Function Analysis ◽  
Luciferase Reporter ◽  
Luciferase Reporter Gene ◽  
Protein Levels ◽  
Activation Of Transcription ◽  
Subsequent Degradation ◽  
The Stability ◽  
F Box Protein ◽  
Ja Signaling

The phytohormone jasmonic acid (JA) plays an important role in various plant developmental processes and environmental adaptations. The JA signaling pathway has been well-elucidated in the reference plant Arabidopsis thaliana. It starts with the perception of the active JA derivative, jasmonoyl-isoleucine (JA-Ile), by the F-box protein COI1 which is part of the E3-ligase SCFCOI1. Binding of JA-Ile enables the interaction between COI1 and JAZ repressor proteins. Subsequent degradation of JAZ proteins leads to the activation of transcription factors like e.g., MYC2. Here we demonstrate that the pathway can be reconstituted in transiently transformed protoplasts. Analysis of the stability of a JAZ1-fLuc fusion protein as a function of COI1 transiently expressed in coi1 protoplasts allows structure function analysis of both JAZs and COI1. Using this system, we found that conserved cysteines in COI1 influence steady state COI1 protein levels. Using a luciferase reporter gene under the control of the JAZ1 promoter enable to address those features of JAZ1 that are required for MYC2 repression. Interestingly, the conserved TIFY-motif previously described to interact with NINJA to recruit the corepressor TOPLESS is not necessary for repression. This result is in favor of the alternative repression mode that proposes a direct competition between repressive JAZs and promotive MEDIATOR25 at MYC2. Finally, using protoplasts from the aos coi1 double mutant, which is deficient in JA synthesis and perception, we provide a system that has the potential to study the activity of different COI1 variants in the presence of different ligands.

Stability of a Proportional Valve Control System With Backlash and Saturation

2013 ◽  
Author(s):  
Nader Moustafa ◽  
Roger Fales
Keyword(s):  
Limit Cycle ◽  
Function Analysis ◽  
Linear Part ◽  
Open Loop ◽  
Function Technique ◽  
Main Stage ◽  
Describing Function ◽  
Nonlinear Part ◽  
The Stability ◽  
Limit Cycle Behavior

In this work, the describing function technique is used to study the stability of a nonlinear system. All of dynamic systems in industrial and fluid power systems are nonlinear and include uncertainties to some degree. Thus, unexpected changes in the stability can be exhibited and can lead these systems to become unstable or exhibit oscillatory behavior. Engineers have developed nonlinear mathematical models to be able to predict whether or not a designed system will be exposed to such an oscillation before considering building and implementing the system. The focus of this study is to predict the existence of nonlinear oscillation behavior in a dynamic system using a simplified approach. A nonlinear model validation of a solenoid operated proportional control valve was performed using open loop testes. The type of two-stage hydraulic valve considered in this research is used to control the velocity of hydraulic cylinders. The pilot valve, which is the focus of this research, is a pressure control 3-way valve. A number of 30 replications of this pilot spool valve were studied and tested experimentally along with a single main stage valve. The model consists of linear and nonlinear parts. The linear part of the model was developed by linearizing the nonlinear governing equations at nominal conditions. The nonlinear part was constructed by analyzing open loop experimental test data. The data showed that two major nonlinearities are found that are key to describing the behavior of the system: saturation of the current input and backlash hysteresis behavior. These nonlinearities were considered to be the cause of limit cycle behavior. Each one of these nonlinearities was represented by its describing function and limit cycles were predicted using the describing function analysis method. In using the describing function method, the complexities of working with the nonlinear physics based model to determine limit cycle behavior were avoided.

Enhancing the resolving power of least‐squares inversion with active constraint balancing

Geophysics ◽  
2003 ◽  
Vol 68 (3) ◽  
pp. 931-941 ◽  
Author(s):  
Myeong‐Jong Yi ◽  
Jung‐Ho Kim ◽  
Seung‐Hwan Chung
Keyword(s):  
Least Squares ◽  
Function Analysis ◽  
Resolution Enhancement ◽  
Resolving Power ◽  
Stability And Convergence ◽  
Lagrangian Multiplier ◽  
Active Constraint ◽  
Data Set ◽  
Resistivity Tomography ◽  
The Stability

Most geophysical inverse problems are solved using least‐squares inversion schemes with damping or smoothness constraints to improve stability and convergence rate. Since the Lagrangian multiplier controls resolution and stability of the inverse problem, we always want to use the optimum multiplier, which is not easy to get and is usually obtained by experience or a time‐consuming optimization process. We present a new regularization approach, in which the Lagrangian multiplier is set as a spatial variable at each parameterized block and automatically determined via the parameter resolution matrix and spread function analysis. For highly resolvable parameters, a small value of the Lagrangian multiplier is assigned, and vice versa. This approach, named “active constraint balancing” (ACB), tries to balance the constraints of the least‐squares inversion according to sensitivity for a given problem so that it enhances the resolution as well as the stability of the inversion process. We demonstrate the performance of the ACB by applying it to a two‐dimensional resistivity tomography problem, which results in a remarkable enhancement of the spatial resolution. Enhancement of the resolution is also verified in the application of resistivity tomography to a field data set acquired at a tunnel construction site.

Characterization and Attenuation of Sandwiched Deadband Problem Using Describing Function Analysis and Application to Electrohydraulic Systems Controlled by Closed-Center Valves

2009 ◽  
Vol 131 (3) ◽  
Author(s):  
Song Liu ◽  
Bin Yao
Keyword(s):  
Closed Loop ◽  
Function Analysis ◽  
Closed Loop Control ◽  
Control Performance ◽  
Nonlinear Feedback ◽  
Describing Function ◽  
Loop Control ◽  
Actuator Dynamics ◽  
And Performance ◽  
The Stability

Unlike input deadband, the sandwiched deadband between actuator and plant dynamics is very difficult to be explicitly compensated for due to the proceeding actuator dynamics whose effect may not be negligible. The paper presents a practical way to overcome the design conservativeness of existing methods in dealing with sandwiched deadband. Specifically, a describing function based nonlinear analysis method is proposed to characterize the effect of the sandwiched deadband on the stability and performance of the overall closed-loop system. The analysis results can be used to determine the highest closed-loop bandwidth that can be achieved without inducing residual limit cycles and instability. Optimal controller parameters can then be found to maximize the achievable closed-loop control performance. The technique is applied to an electrohydraulic system controlled by closed-center valves and a nonlinear feedback controller. Simulation results showed severe oscillations as the feedback control gains are increased to the predicted threshold values. Comparative experimental results also showed the effectiveness of the proposed method in reducing the conservativeness of traditional design and the improved closed-loop control performance in implementation.

scholarly journals Evans function computation for the stability of travelling waves

2018 ◽  
Vol 376 (2117) ◽  
pp. 20170184 ◽  
Author(s):  
B. Barker ◽  
J. Humpherys ◽  
G. Lyng ◽  
J. Lytle
Keyword(s):  
Travelling Waves ◽  
Evans Function ◽  
Detonation Waves ◽  
Model Parameters ◽  
Theme Issue ◽  
Function Computation ◽  
Computational Aspects ◽  
The Stability ◽  
Linearized Operator

In recent years, the Evans function has become an important tool for the determination of stability of travelling waves. This function, a Wronskian of decaying solutions of the eigenvalue equation, is useful both analytically and computationally for the spectral analysis of the linearized operator about the wave. In particular, Evans-function computation allows one to locate any unstable eigenvalues of the linear operator (if they exist); this allows one to establish spectral stability of a given wave and identify bifurcation points (loss of stability) as model parameters vary. In this paper, we review computational aspects of the Evans function and apply it to multidimensional detonation waves. This article is part of the theme issue ‘Stability of nonlinear waves and patterns and related topics’.

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