About this Journal Submit a Manuscript Table of Contents
Abstract and Applied Analysis
Volume 2013 (2013), Article ID 901014, 10 pages
http://dx.doi.org/10.1155/2013/901014
Research Article

The Time Delays’ Effects on the Qualitative Behavior of an Economic Growth Model

1Dipartimento di Scienze Matematiche, Politecnico, Corso Duca degli Abruzzi 24, 10129 Torino, Italy
2Department of Law and Economics, University Mediterranea of Reggio Calabria and CRIOS University Bocconi of Milan, Via dei Bianchi 2, 89127 Reggio Calabria, Italy
3Department of Management, Polytechnic University of Marche, 60121 Ancona, Italy

Received 14 August 2013; Accepted 1 November 2013

Academic Editor: Constantin Udriste

Copyright © 2013 Carlo Bianca et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

A further generalization of an economic growth model is the main topic of this paper. The paper specifically analyzes the effects on the asymptotic dynamics of the Solow model when two time delays are inserted: the time employed in order that the capital is used for production and the necessary time so that the capital is depreciated. The existence of a unique nontrivial positive steady state of the generalized model is proved and sufficient conditions for the asymptotic stability are established. Moreover, the existence of a Hopf bifurcation is proved and, by using the normal form theory and center manifold argument, the explicit formulas which determine the stability, direction, and period of bifurcating periodic solutions are obtained. Finally, numerical simulations are performed for supporting the analytical results.

1. Introduction

Most of the phenomena occurring in real-world complex systems, especially in the economics systems, have not an immediate effect but appear with some delay. Therefore time delays have been inserted into mathematical models and in particular in models of the applied sciences based on ordinary differential equations; see the recent book [1]. Differential equations specifically with time delays have been proposed in population dynamics [2] for biological systems such as immune system response [36] and tumor growth [712], in models of social sciences [13], and in economics systems; see, among others, [1421].

The introduction of a time delay into an ordinary differential equation could change the stability of the equilibrium (stable equilibrium becomes unstable) and could cause fluctuations, and Hopf bifurcation can occur. Indeed global existence of Hopf bifurcations has been proved in many delay mathematical models; see papers [2224] and references cited therein.

If on one hand, the stability and bifurcation analysis of ordinary differential equations with a single time delay is well outlined in the pertinent literature [25, 26], on the other hand the analysis of the dynamics of ordinary differential equations with multiple time delays is a difficult task [2729] and the related literature is much limited. In this context, for several classes of ordinary differential equation models with multiple time delays, sufficient and necessary conditions have been established and a complete description of the stability region has been reached; see, among others, [30, 31] and references cited therein.

The present paper is concerned with a further generalization of the Solow model [32]. The generalized model is governed by a delay differential equation with two time delays. Specifically the two time delays refer, respectively, to the time employed in order that the capital is used for production and the necessary time so that the capital is depreciated. The asymptotic analysis performed in this paper shows the existence of a unique nontrivial positive steady state, and sufficient conditions for the asymptotic stability are established. Moreover, the existence of a Hopf bifurcation is proved and, by using the normal form theory and center manifold argument, the explicit formulas which determine the stability, direction, and period of bifurcating periodic solutions are obtained. Finally, some numerical simulations to support the analytical conclusions are carried out.

The rest of the paper is organized into four more sections which follow this introduction. Specifically, Section 2 discusses the derivation of the generalized Solow model with two time delays. Section 3 deals with the analysis of the existence of Hopf bifurcation and stability of the positive equilibrium for the model proposed in Section 1. Section 4 is concerned with the direction and the stability of the Hopf bifurcation. Some numerical simulations are performed in Section 5 with the aim of supporting the analytic results. Finally Section 6 completes the paper with conclusions and some future research perspectives.

2. The Mathematical Model

Recently, Zak has proposed in [15] the following delay ordinary differential equation to describe the dynamics of the Solow model [32] in which a production technology has a constant finite period linked to the time needed for the installation of capital. Here, denotes capital at time , is a neoclassical production function, namely a function which is continuous, increasing, and strictly concave in capital, and is the constant savings rate. Population is assumed to be constant and normalized to unity. During production a proportion of the capital stock, , depreciates at the same gestation period .

The assumption that the growth of the amount of capital at time is a function of the total output of capital at time has been showed in [15] to be the source of cyclic behaviour in the economic system (1). Generalizing this idea, we proposed the following delay ordinary differential equation: that is, the generalized Solow model with two delays.

It is worth stressing that for , we recover the Solow model equation [32]. In this model, the positive equilibrium is asymptotically stable in the absence of delay. For , (2) reduces to the delayed Solow model proposed by Zak in [15].

3. Local Stability and Hopf Bifurcation

The mathematical model (2) has exactly the same equilibrium points of the corresponding system with zero delays. Hence, there exists a unique positive equilibrium , where . To determine the stability of this equilibrium and Hopf bifurcation, we linearize (2) around . The result is a linear delay differential equation of the form where It is well known that the stability of the equilibrium is determined by the spectrum of the eigenvalues of the linearization, which can be found as the roots of the characteristic equation We recall that an equilibrium point of an equation is stable if all eigenvalues of its linearization have negative real part. It changes its stability type when eigenvalues cross the imaginary axis of the complex plane. We first note that is not a root of (5) because this would imply , contradicting the fact that . Next, the distribution of the roots of (5) should be investigated. However, the analysis of the sign of the real parts of eigenvalues is very complicated because of the presence of two different delays, and , in (5). Therefore, we will use a method consisting of determining the stability of the equilibrium when one delay is equal to zero, and, using similar analytic arguments as in the work by Ruan and Wei [33], we will deduce conditions for the stability of the equilibrium when both time delays are nonzero.

3.1. Case 1: and

The characteristic equation (5) reduces to If , (6) has the unique root . Thus, the equilibrium is locally asymptotically stable. Consequently, when increases, the stability of the steady state can only be lost if pure imaginary roots appear. Hence we look for purely imaginary roots , , of (6). Let be a purely imaginary root of (6). Then, separating real and imaginary parts, satisfies It follows that Hence, (6) has no positive root. Then, we can conclude the following result about the asymptotic stability of the equilibrium of (2).

Proposition 1. Let . Then the positive equilibrium of (2) is locally asymptotically stable.

3.2. Case 2: and

The characteristic equation (5) becomes

Setting , we know that the equilibrium is locally asymptotically stable. Let , , be a root of (9). Separating real and imaginary parts, we have the following two equations: Adding the squares of both hand sides of (10), it follows that must be a root of the following equation: Hence, (11) admits only the positive root Define from (10) and Then, it is immediate to check that is a simple root of (9) when .

Lemma 2. Let be the complex root of (9) near satisfying and . Then the transversal condition is satisfied.

Proof. Differentiating the characteristic equation (9) with respect to , we obtain This gives Hence, we have This completes the proof.

Bearing the above analysis in mind and the Hopf bifurcation theorem for functional differential equations due to Hale and Verduyn Lunel (see p. 246, Theorem 1.1 of the book [34]), we have the following result.

Theorem 3. Let . Then the positive equilibrium of (2) is locally asymptotically stable when and unstable when . Furthermore, (2) undergoes a Hopf bifurcation at the positive equilibrium when , , where is defined as in (14).

3.3. Case 3: and

Equation (5) has purely imaginary roots , where , if the following equations are satisfied. Consider Squaring and adding up both equations in (19) yield where

Lemma 4. For every arbitrary , (20) has a finite number of positive solutions for .

Proof. The inequality and imply . The function has the properties , , , and A graphical inspection on the intersections of the functions and gives the statement.

Remark 5. If , (20) has only one positive solution.

For any , (20) has a finite number of positive zeros , . It is clear that for every arbitrary chosen and for each we have an infinite number of such that . For all , we define In addition, we set and denote for such that . Next, we check the condition which guarantees that the purely imaginary roots pass through the imaginary axis at . Let be the root of (5) near such that and . By direct computation we have and obtain Hence, it follows that If for given both and are positive (resp., negative), then and the purely imaginary roots of (5) move to the right (resp., left) half plane when the bifurcation parameter increases. So, we have the following transversality condition.

Proposition 6. Let and .(1)If , then .(2)If , then .

Lemma 7. are simple roots of (5) when .

Proof. If is a repeated root for (5), then holds true. Using (5), this leads to and . Thus, we must have . If , this means , while if , this identity does not hold. The conclusion is immediate.

From the discussion above, and recalling that for any and all roots of (5) have strictly negative real parts, the following theorem about stability and Hopf bifurcation of (2) is immediately obtained.

Theorem 8. Let and , be defined as in Proposition 6. Then(1)equation (2) undergoes a Hopf bifurcation at when ,(2)if , then the nontrivial equilibrium to (2) is locally asymptotically stable for and unstable for ,(3)if , then the nontrivial equilibrium to (2) is locally asymptotically stable for .

4. Direction and Stability of the Hopf Bifurcation

In this section, we study the direction of bifurcations and the stability of bifurcating periodic solutions of (2) at by using the method based on the normal form theory and center manifold theory introduced by Hassard et al. [35].

For notational convenience, let , . Then is the Hopf bifurcation point for (2). First, we transform (2) into a functional differential equation in , which is the Banach space of continuous real-valued functions that map into , and endowed with the norm Set . Then, rewriting (2) in terms of and considering its Taylor expansion at the trivial equilibrium up to the third order, we get For , define the linear operator and the nonlinear operator By the Riesz representation theorem, there exists a bounded variation function with such that with where is the Dirac delta function. For , define Then (30) is equivalent to where for . For , define the operator as and the bilinear inner product where the over bar denotes complex conjugation. Then and are adjoint operators. By the discussion in the previous section, we know that are eigenvalues of . Thus, they are also eigenvalues of . We need to compute the eigenvector of and corresponding to and , respectively. A direct computation shows that their eigenvectors are respectively. We have . In order to ensure , we choose as Next, we compute the coordinates to describe the center manifold at . Let be the solution of (36) when . Define On the center manifold , we have , with where and are local coordinates for in the direction of and . For any , since , we find with We rewrite (43) as where It follows from (36) and (43) that where Expanding the above series and comparing the coefficients, we get Now implies Noticing that , we derive Then substituting this into (50) and comparing the coefficients with (46), the following hold: In order to compute , we need to know and . For , we have Comparing the coefficients with those in (48) yields From (49) Solving , we have and, similarly for , Here and are constants to be determined by setting in . A direct computation shows Then all have been obtained, and thus we can compute the quantities which determine the properties of bifurcating periodic solutions at the critical value . From the discussion above, we have the following result.

Theorem 9. Let be the unique positive equilibrium of the model (2). Then one has the following. (1) determines the direction of the Hopf bifurcation when : if (resp., ), then the Hopf bifurcation is supercritical (resp., subcritical) and the bifurcating periodic solution exists for (resp., ) in a sufficiently small -neighbourhood.(2) determines the stability of the bifurcating periodic solution: if (resp., ) the bifurcating periodic solution is locally asymptotically stable (resp., unstable).(3) determines the period of the bifurcating periodic solution: if (resp., ) the period increases (resp., decreases).

5. Numerical Simulations

This section is concerned with some numerical simulations of the mathematical model (2) with the aim of exploring the analytical results. The model is characterized by four nonnegative parameters (, , , ) and the function . In what follows we restrict our attention to the Cobb-Douglas function; this function reads with and .

The first set of simulations refers to the following case: where . Figure 1(a) shows that the function reaches the stationary state (the equilibrium ). This equilibrium is stable; see Figure 1(b), where the evolution of versus is depicted for .

fig1
Figure 1: The time evolution of the function for , , , , , and (a). The versus , for (b).

The dynamics depicted by Figure 1 does not change from the qualitative viewpoint when . Indeed when the parameter varies in the interval the time necessary for reaching the stationary state increases but the behavior is that of Figure 1. When the time evolution of is shown in Figure 2. In this simulation the time length has been increased in order to better visualize the evolution. As Figure 2(b) shows, the equilibrium is now instable.

fig2
Figure 2: The time evolution of the function for , , , , , and (a). The versus , for (b).

The second set of simulations refers to the following case: These simulations take into account the case . As Figure 3 shows, oscillations occur for a long time (about ), with respect to the previous case, before reaching the equilibrium. In this case the equilibrium is stable but a very long time is necessary to reach it; see Figure 3(b). It is sufficient to increase for obtaining the stationary state rapidly. These simulations suggest that when the value of increases then the time necessary to reach the stationary state decreases. Moreover, if the difference increases, then the stability of the equilibrium is lost for all .

fig3
Figure 3: The time evolution of the function for , , , , , and (a). The versus , for (b).

Finally, we would show some numerical simulations related to the evolution of versus . Figure 4 shows the instability of the equilibrium for , , , , , , see Figure 4(a); it is worth stressing that the equilibrium is reached for . In this case, when we increase the magnitude of we are able to reach the equilibrium more rapidly, see Figure 4(b), which is obtained for and . The equilibrium is rapidly reached if we also decrease the magnitude of .

fig4
Figure 4: The time evolution of versus for , , , , , , and (a). The time evolution of versus for , , , , , , and (b).

6. Conclusions and Research Perspectives

In the present paper, a generalization of the Solow model by inserting two time delays has been considered. The delays, respectively, represent the time employed in order that the capital is used for production and the necessary time so that the capital is depreciated. Specifically, an asymptotic analysis has been performed referring to the stability analysis of the steady state and the conditions under which a Hopf bifurcation appears.

According to the analysis developed in this paper, the stability of the positive equilibrium changes as the time delays vary. Indeed if , the positive equilibrium is always locally asymptotically stable; if the positive equilibrium can be locally asymptotically stable or unstable and a Hopf bifurcation occurs; the dynamics is more complicated when the two time delays are both different from zero (see Theorem 8 where as the reader can see the investigation of stability switches becomes quite complicated). This shows that the time delays play an important role in the dynamics of the model. Then, based on the analysis of the existence of the Hopf bifurcation, by using the center manifold theory and the normal form method, an explicit algorithm for determining the direction of the Hopf bifurcation and the stability of the bifurcating periodic solutions has been derived. This means that one can obtain the important quantities which determine the properties of bifurcating periodic solutions at the critical value; see Theorem 9. According to our results, we can say that the model with two independent time delays has much more complicated dynamics than the model with only one time delay. That is why it seems to be more realistic.

The introduction of time delays can be also performed in the mathematical model developed in [36] for the mammary carcinoma. Indeed the stability analysis developed in the present paper can help to reach more results in the cancer-immune system competition. From a biological point of view, the Hopf bifurcation means that for small values of parameters the nontrivial stationary solution to the model in [36] is stable, and we do not observe radical changes in the competition. Otherwise, nontrivial stationary solution can oscillate and the amplitude of the oscillations about the stationary solution remains constant. This case simply corresponds to the situation when the competition oscillates in time.

The Hopf bifurcation analysis developed in this paper must be revised if the mathematical models are not based on ordinary differential equations. Recently an increasing number of partial differential equation models for tumor growth or therapy have been developed; see the references section of paper [12] and the references cited in the recent review paper [37].

Moreover thermostated integrodifferential equations have been proposed in papers [3843] for the modeling of biological systems, vehicular traffic, crowd and swarm dynamics, and economic systems subjected to external force fields. The introduction of the Gaussian isokinetic thermostat ensures the reaching of stationary states whose existence has been proved in [44]. The introduction of multiple time delays in thermostated equations, their stability, and bifurcation analysis is a future research perspective.

It is worth stressing that also the Boltzmann equation with the one-dimensional Bhatnagar-Gross-Krook relaxation type operator [45] and the Kac equation have been coupled with a Gaussian isokinetic thermostat; the existence of stationary solutions is ensured also within these frameworks; see papers [4648].

Conflict of Interests

The authors declare that there is no conflict of interests regarding the publication of this paper.

Acknowledgments

The first author acknowledges the support by the FIRB project RBID08PP3J-Metodi matematici e relativi strumenti per la modellizzazione e la simulazione della formazione di tumori, competizione con il sistema immunitario, e conseguenti suggerimenti terapeutici. The authors acknowledge the financial support of MEDAlics-Research Center for Mediterranean Relations.

References

  1. T. Erneux, Applied Delay Differential Equations, Springer, New York, NY, USA, 2009. View at MathSciNet
  2. P. J. Cunningham and W. J. Wangersky, Time Lag in Population Models, Yale, 1958.
  3. G. I. Marchuk, Mathematical Modelling of Immune Response in Infectious Diseases, Kluwer Academic, Dordrecht, Germany, 1997. View at MathSciNet
  4. U. Foryś, “Interleukin mathematical model of an immune system,” Journal of Biological Systems, vol. 3, pp. 889–902, 1995. View at Publisher · View at Google Scholar
  5. U. Foryś, “Global analysis of Marchuks model in case of strong immune system,” Journal of Biological Systems, vol. 8, pp. 331–346, 2000. View at Publisher · View at Google Scholar
  6. M. Bodnar and U. Foryś, “A model of immune system with time-dependent immune reactivity,” Nonlinear Analysis: Theory, Methods & Applications, vol. 70, no. 2, pp. 1049–1058, 2009. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
  7. U. Foryś and M. Bodnar, “Time delays in proliferation process for solid avascular tumour,” Mathematical and Computer Modelling, vol. 37, no. 11, pp. 1201–1209, 2003. View at Publisher · View at Google Scholar · View at Scopus
  8. H. M. Byrne, “The effect of time delays on the dynamics of avascular tumor growth,” Mathematical Biosciences, vol. 144, no. 2, pp. 83–117, 1997. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
  9. M. J. Piotrowska, “Hopf bifurcation in a solid avascular tumour growth model with two discrete delays,” Mathematical and Computer Modelling, vol. 47, no. 5-6, pp. 597–603, 2008. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
  10. M. Bodnar and U. Foryś, “Three types of simple DDE’s describing tumour growth,” Journal of Biological Systems, vol. 15, pp. 1–19, 2007.
  11. M. Bodnar and U. Foryś, “Global stability and the Hopf bifurcation for some class of delay differential equation,” Mathematical Methods in the Applied Sciences, vol. 31, no. 10, pp. 1197–1207, 2008. View at Publisher · View at Google Scholar · View at MathSciNet
  12. B. Shi, F. Zhang, and S. Xu, “Hopf bifurcation of a mathematical model for growth of tumors with an action of inhibitor and two time delays,” Abstract and Applied Analysis, vol. 2011, Article ID 980686, 10 pages, 2011. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
  13. N. Bielczyk, U. Foryś, and T. Platkowski, “Dynamical models of Dyadic interactions with delay,” The Journal of Mathematical Sociology, vol. 37, no. 4, 2013.
  14. S. Invernizzi and A. Medio, “On lags and chaos in economic dynamic models,” Journal of Mathematical Economics, vol. 20, no. 6, pp. 521–550, 1991. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
  15. P. J. Zak, “Kaleckian lags in general equilibrium,” Review of Political Economy, vol. 11, no. 3, pp. 321–330, 1999. View at Publisher · View at Google Scholar
  16. G. Dibeh, “Speculative dynamics in a time-delay model of asset prices,” Physica A, vol. 355, no. 1, pp. 199–208, 2005. View at Publisher · View at Google Scholar · View at MathSciNet
  17. M. Szydlowski, A. Krawiec, and J. Tobola, “Nonlinear oscillations in business cycle model with time lags,” Chaos, Solitons and Fractals, vol. 12, no. 3, pp. 505–517, 2001. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
  18. L. Zhou and Y. Li, “A dynamic IS-LM business cycle model with two time delays in capital accumulation equation,” Journal of Computational and Applied Mathematics, vol. 228, no. 1, pp. 182–187, 2009. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
  19. C. Bianca and L. Guerrini, “On the Dalgaard-Strulik model with logistic population growth rate and delayed-carrying capacity,” Acta Applicandae Mathematicae, vol. 128, pp. 39–48, 2013. View at Publisher · View at Google Scholar · View at MathSciNet
  20. C. Bianca, M. Ferrara, and L. Guerrini, “Hopf bifurcations in a delayed-energy-based model of capital accumulation,” Applied Mathematics & Information Sciences, vol. 7, no. 1, pp. 139–143, 2013. View at Publisher · View at Google Scholar · View at MathSciNet
  21. C. Bianca, M. Ferrara, and L. Guerrini, “The Cai model with time delay: existence of periodic solutions and asymptotic analysis,” Applied Mathematics & Information Sciences, vol. 7, no. 1, pp. 21–27, 2013. View at Publisher · View at Google Scholar · View at MathSciNet
  22. Y. Ma, “Global Hopf bifurcation in the Leslie-Gower predator-prey model with two delays,” Nonlinear Analysis: Real World Applications, vol. 13, no. 1, pp. 370–375, 2012. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
  23. Y. Song, J. Wei, and M. Han, “Local and global Hopf bifurcation in a delayed hematopoiesis model,” International Journal of Bifurcation and Chaos in Applied Sciences and Engineering, vol. 14, no. 11, pp. 3909–3919, 2004. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
  24. J. Wei, “Bifurcation analysis in a scalar delay differential equation,” Nonlinearity, vol. 20, no. 11, pp. 2483–2498, 2007. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
  25. E. Burger, “On the stability of certain economic systems,” Econometrica, vol. 24, pp. 488–493, 1956. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
  26. N. D. Hayes, “Roots of the transcendental equation associated with a certain difference-differential equation,” Journal of the London Mathematical Society, vol. 25, pp. 226–232, 1950. View at Zentralblatt MATH · View at MathSciNet
  27. J. K. Hale and W. Z. Huang, “Global geometry of the stable regions for two delay differential equations,” Journal of Mathematical Analysis and Applications, vol. 178, no. 2, pp. 344–362, 1993. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
  28. X. Li, S. Ruan, and J. Wei, “Stability and bifurcation in delay-differential equations with two delays,” Journal of Mathematical Analysis and Applications, vol. 236, no. 2, pp. 254–280, 1999. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
  29. J. Wei and Y. Yuan, “Synchronized Hopf bifurcation analysis in a neural network model with delays,” Journal of Mathematical Analysis and Applications, vol. 312, no. 1, pp. 205–229, 2005. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
  30. J. K. Hale and W. Z. Huang, “Global geometry of the stable regions for two delay differential equations,” Journal of Mathematical Analysis and Applications, vol. 178, no. 2, pp. 344–362, 1993. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
  31. M. J. Piotrowska, “A remark on the ODE with two discrete delays,” Journal of Mathematical Analysis and Applications, vol. 329, no. 1, pp. 664–676, 2007. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
  32. R. M. Solow, “A contribution to the theory of economic growth,” Quarterly Journal of Economics, vol. 70, pp. 65–94, 1956. View at Publisher · View at Google Scholar
  33. S. Ruan and J. Wei, “On the zeros of transcendental functions with applications to stability of delay differential equations with two delays,” Dynamics of Continuous, Discrete & Impulsive Systems A, vol. 10, no. 6, pp. 863–874, 2003. View at Zentralblatt MATH · View at MathSciNet
  34. J. K. Hale and S. M. Verduyn Lunel, Introduction to Functional-Differential Equations, Springer, New York, NY, USA, 1993. View at MathSciNet
  35. B. D. Hassard, N. D. Kazarinoff, and Y. H. Wan, Theory and Applications of Hopf Bifurcation, Cambridge University Press, 1981. View at MathSciNet
  36. C. Bianca and M. Pennisi, “The triplex vaccine effects in mammary carcinoma: a nonlinear model in tune with SimTriplex,” Nonlinear Analysis: Real World Applications, vol. 13, no. 4, pp. 1913–1940, 2012. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
  37. C. Bianca, “Thermostatted kinetic equations as models for complex systems in physicsand life sciences,” Physics of Life Reviews, vol. 9, pp. 359–399, 2012. View at Publisher · View at Google Scholar
  38. C. Bianca, “Kinetic theory for active particles modelling coupled to Gaussian thermostats,” Applied Mathematical Sciences, vol. 6, no. 13-16, pp. 651–660, 2012. View at Zentralblatt MATH · View at MathSciNet
  39. C. Bianca, “Modeling complex systems by functional subsystems representation and thermostatted-KTAP methods,” Applied Mathematics & Information Sciences, vol. 6, pp. 495–499, 2012.
  40. C. Bianca, “An existence and uniqueness theorem to the Cauchy problem for thermostatted-KTAP models,” International Journal of Mathematical Analysis, vol. 6, no. 17–20, pp. 813–824, 2012. View at Zentralblatt MATH · View at MathSciNet
  41. C. Bianca, M. Ferrara, and L. Guerrini, “High-order moments conservation in thermostatted kinetic models,” Journal of Global Optimization, 2013. View at Publisher · View at Google Scholar
  42. C. Bianca, “Onset of nonlinearity in thermostatted active particles models for complex systems,” Nonlinear Analysis: Real World Applications, vol. 13, no. 6, pp. 2593–2608, 2012. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
  43. C. Bianca, “Controllability in hybrid kinetic equations modeling nonequilibrium multicellular systems,” The Scientific World Journal, vol. 2013, Article ID 274719, 6 pages, 2013. View at Publisher · View at Google Scholar
  44. C. Bianca, “Existence of stationary solutions in kinetic models with Gaussian thermostats,” Mathematical Methods in the Applied Sciences, vol. 36, pp. 1768–1775, 2013. View at Publisher · View at Google Scholar · View at Zentralblatt MATH
  45. P. Degond and B. Wennberg, “Mass and energy balance laws derived from high-field limits of thermostatted Boltzmann equations,” Communications in Mathematical Sciences, vol. 5, no. 2, pp. 355–382, 2007. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
  46. V. Bagland, B. Wennberg, and Y. Wondmagegne, “Stationary states for the noncutoff Kac equation with a Gaussian thermostat,” Nonlinearity, vol. 20, no. 3, pp. 583–604, 2007. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
  47. B. Wennberg and Y. Wondmagegne, “Stationary states for the Kac equation with a Gaussian thermostat,” Nonlinearity, vol. 17, no. 2, pp. 633–648, 2004. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
  48. B. Wennberg and Y. Wondmagegne, “The Kac equation with a thermostatted force field,” Journal of Statistical Physics, vol. 124, no. 2–4, pp. 859–880, 2006. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet