Fig 1.
F-actin is enveloped by water molecules and counterions.
Fig 2.
A simplified circuit for the monomer shows current
flowing through inductance S and resistance
.
Fig 3.
Chart of the implemented analysis.
Fig 4.
Anti-kink soliton profile of from Eq (36) for positive wave speed using 3D plot.
Fig 5.
Anti-kink soliton profile of from Eq (36) for positive wave speed using 2D plot.
Fig 6.
Kink soliton profile of from Eq (36) for negative wave speed.
Fig 7.
Kink soliton profile of from Eq (36) for negative wave speed.
Fig 8.
Global phase portraits of the dynamical system (37) for positive and
, when
is absent.
Fig 9.
Global phase portraits of the dynamical system (37) for positive and
, when
is positive.
Fig 10.
Global phase portraits of the dynamical system (37) for positive and
, when
is negative.
Fig 11.
Global phase portraits of the dynamical system (37) for negative and
, when
is absent.
Fig 12.
Global phase portraits of the dynamical system (37) for negative and
, when
is positive.
Fig 13.
Global phase portraits of the dynamical system (37) for negative and
, when
is negative.
Fig 14.
Global phase portraits of the dynamical system (37) for and
, when
is absent.
Fig 15.
Global phase portraits of the dynamical system (37) for and
, when
is positive.
Fig 16.
Global phase portraits of the dynamical system (37) for and
, when
is negative.
Fig 17.
Global phase portraits of the dynamical system (37) for and
, when
is absent.
Fig 18.
Global phase portraits of the dynamical system (37) for and
, when
is positive.
Fig 19.
Global phase portraits of the dynamical system (37) for and
, when
is negative.
Table 1.
Conditions and parameter values corresponding to Global Phase Portraits.
Table 2.
Equilibrium points behaviors, and trajectory types of global phase portraits.
Fig 20.
Identification of quasi-periodic behaviour through 2D phase portrait analysis for dynamical system (45) at = 0.85,
= -0.45,
, and
.
Fig 21.
Identification of quasi-periodic behaviour through 2D phase portrait analysis for dynamical system (45) at = 0.85,
,
, and
.
Fig 22.
Identification of chaotic behaviour through 2D phase portrait analysis for dynamical system (45) at ,
= -0.45,
, and
.
Fig 23.
Identification of chaotic behaviour through 2D phase portrait analysis for dynamical system (45) at = 0.85,
= -0.45,
, and
.
Fig 24.
Identification of chaotic behaviour through 2D phase portrait analysis for dynamical system (45) at = 0.85,
= -0.45,
, and
.
Fig 25.
Identification of quasi-periodic and chaotic behaviour through 2D phase portrait analysis for dynamical system (45) at = 0.85,
= -0.45,
, and
.
Fig 26.
Chaotic behaviour in time analysis of system (45) for and
with
> 0,
> 0.
Fig 27.
Chaotic behaviour in time analysis of system (45) for and
with
< 0,
< 0.
Fig 28.
Identification of chaotic behaviour through poincaré map for dynamical system (45) at = 0.85,
,
= -0.45, and
.
Fig 29.
Identification of chaotic behaviour through poincaré map for dynamical system (45) at ,
,
, and
.
Fig 30.
Identification of chaotic behaviour through poincaré map for dynamical system (45) at ,
,
, and
.
Fig 31.
Identification of chaotic behaviour through poincaré map for dynamical system (45) at ,
,
, and
.
Fig 32.
Detection of chaotic behavior through the Lyapunov exponent for dynamical system (45) with ,
, and
.
Fig 33.
Detection of chaotic behavior through power spectrum for dynamical system (45) with ,
, and
.
Fig 34.
Detection of chaotic behavior through return map for dynamical system (45) with ,
, and
.
Fig 35.
Detection of chaotic behavior through fractal dimension for dynamical system (45) with ,
, and
.
Fig 36.
Analysis of sensitivity in the dynamical system (53) using (0.45,0.03) and (0.12,0.03).
Fig 37.
Analysis of sensitivity in the dynamical system (53) using (0.42,0.03) and (0.34,0.03).
Fig 38.
Analysis of sensitivity in the dynamical system (53) using using (0.35,0.03) and (0.24,0.03).