On controllability of neuronal networks with constraints on the average of control gains

Control gains play an important role in the control of a natural or a technical system since they reflect how much resource is required to optimize a certain control objective. This paper is concerned with the controllability of neuronal networks with constraints on the average value of the control gains injected in driver nodes, which are in accordance with engineering and biological backgrounds. In order to deal with the constraints on control gains, the controllability problem is transformed into a constrained optimization problem (COP). The introduction of the constraints on the control gains unavoidably leads to substantial difficulty in finding feasible as well as refining solutions. As such, a modified dynamic hybrid framework (MDyHF) is developed to solve this COP, based on an adaptive differential evolution and the concept of Pareto dominance. By comparing with statistical methods and several recently reported constrained optimization evolutionary algorithms (COEAs), we show that our proposed MDyHF is competitive and promising in studying the controllability of neuronal networks. Based on the MDyHF, we proceed to show the controlling regions under different levels of constraints. It is revealed that we should allocate the control gains economically when strong constraints are considered. In addition, it is found that as the constraints become more restrictive, the driver nodes are more likely to be selected from the nodes with a large degree. The results and methods presented in this paper will provide useful insights into developing new techniques to control a realistic complex network efficiently

BMB activity defines refractory and competent hair follicle populations during the propagation of regenerative waves

n/

Dispersion Relations for Thermally Excited Waves in Plasma Crystals

Thermally excited waves in a Plasma crystal were numerically simulated using a Box_Tree code. The code is a Barnes_Hut tree code proven effective in modeling systems composed of large numbers of particles. Interaction between individual particles was assumed to conform to a Yukawa potential. Particle charge, mass, density, Debye length and output data intervals are all adjustable parameters in the code. Employing a Fourier transform on the output data, dispersion relations for both longitudinal and transverse wave modes were determined. These were compared with the dispersion relations obtained from experiment as well as a theory based on a harmonic approximation to the potential. They were found to agree over a range of 0.9<k<5, where k is the shielding parameter, defined by the ratio between interparticle distance a and dust Debye length lD. This is an improvement over experimental data as current experiments can only verify the theory up to k = 1.5.Comment: 8 pages, Presented at COSPAR '0

Mechanical Dispersion of Nanoparticles and Its Effect on the Specific Heat Capacity of Impure Binary Nitrate Salt Mixtures

In this study, the effect of nanoparticle concentration was tested for both CuO and TiO2 in eutectic mixture of sodium and potassium nitrate. Results showed an enhancement in specific heat capacity (Cp) for both types of nanoparticles (+10.48% at 440 °C for 0.1 wt % CuO and +4.95% at 440 °C for 0.5 wt % TiO2) but the behavior toward a rise in concentration was different with CuO displaying its highest enhancement at the lowest concentration whilst TiO2 showed no concentration dependence for three of the four different concentrations tested. The production of cluster of nanoparticles was visible in CuO but not in TiO2. This formation of nanostructure in molten salt might promote the enhancement in Cp. However, the size and shape of these structures will most likely impact the energy density of the molten salt

Estimation of shell radiation efficiency using a FEM-SmEdA algorithm

The radiation efficiencies of cylindrical and conical shells were investigated by using the statistical modal energy distribution analysis (SmEdA) and integrated FEM-SmEdA approaches. In cylindrical shell, three analytical algorithms were carried out, including SmEdA and two conventional approaches, i.e. the wave approach and the statistical energy analysis (SEA), and the results were compared with a former experimental one. SmEdA showed closest results with the experimental one, owing to its precise estimation of the coupling loss factors (CLF) which were further used to calculate the radiation efficiency. Furthermore, based on the analytical SmEdA, an integrated FEM-SmEdA algorithm is proposed. This hybrid method provided similar shell radiation efficiency for cylindrical shell, indicating its applicability in the analysis of complicated structures