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The migratory locust is one of the most notorious agricultural pests that undergo a well known reversible, density-dependent phase transition from the solitary to the gregarious. To demonstrate the underlying molecular mechanisms of the phase change, we generated 76,012 ESTs from the whole body and dissected organs in the two phases. Comparing 12,161 unigene clusters, we identified 532 genes as phase-related (P < 0.01). Comprehensive assessment of the phase-related expression revealed that, whereas most of the genes in various categories from hind legs and the midgut are down-regulated in the gregarious phase, several gene classes in the head are impressively up-regulated, including those with peptidase, receptor, and oxygen-binding activities and those related to development, cell growth, and responses to external stimuli. Among them, a superfamily of proteins, the JHPH super-family, which includes juvenile hormone-binding protein, hexamerins, prophenoloxidase, and hemocyanins, were highly expressed in the heads of the gregarious hoppers and hind legs of the solitary hoppers. Quantitative PCR experiments confirmed in part the EST results. These differentially regulated genes have strong functional implications that numerous molecular activities are involved in phase plasticity. This study provides ample molecular markers and genomic information on hemimetabolous insects and insights into the genetic and molecular mechanisms of phase changes in locusts. solitary phase | gregarious phase | EST | unigene

This paper deals with the problem for synchronization of a nonlinear time delayed complex spatio-temporal network (CSN), modelled by semi-linear parabolic partial differential-difference equations. A boundary controller relying to distributed measurement is designed. Multiple time-invariant delays are firstly considered. By employing Lyapunov's direct method and Wirtingers inequality, synchronization criteria of the CSN are presented in terms of LMIs. And then, multiple time-varying delays are respectively considered using the boundary controller and synchronization criteria are obtained. Finally, an example illustrates the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

An H ∞ congestion tracking control problem for nonlinear transmission control protocol/active queue management (TCP/AQM) network is proposed in this paper. Inspired by the existing network models, a modified TCP/AQM network model with external disturbance and modelling uncertainty is first introduced. And then, a novel function for the desired queue length is defined for the first time, which can simulate the changes in the queue length during a day. Next, a novel AQM scheme is presented to control network congestion by combining H ∞ theory and integral backstepping technique. The proposed method guarantees that the better tracking performance of the queue is achieved, and all the signals are asymptotically stable in the closed-loop system in probability. Finally, the effectiveness of the presented algorithm is tested by simulation results. [ABSTRACT FROM AUTHOR]

This paper concerns the problem of robust H∞ sliding mode control for a class of singular stochastic nonlinear systems. Integral sliding mode control is developed to deal with this problem. Based on the integral sliding surface of the design and linear matrix inequality, a sufficient condition which guarantees the sliding mode dynamics is asymptotically mean square admissible and has a prescribed H∞ performance for a class of singular stochastic nonlinear systems is proposed. Furthermore, a sliding mode control law is synthesized such that the singular stochastic nonlinear system can be driven to the sliding surface in finite time. Finally, a numerical example is proposed to illustrate the effectiveness of the given theoretical results. [ABSTRACT FROM AUTHOR]

The target of this article is to study almost periodic dynamical behaviors for complex-valued recurrent neural networks with discontinuous activation functions and time-varying delays. We construct an equivalent discontinuous right-hand equation by decomposing real and imaginary parts of complex-valued neural networks. Based on differential inclusions theory, diagonal dominant principle and nonsmooth analysis theory of generalized Lyapunov function method, we achieve the existence, uniqueness and global stability of almost periodic solution for the equivalent delayed differential network. In particular, we derive a series of results on the equivalent neural networks with discontinuous activation functions, constant coefficients as well as periodic coefficients, respectively. Finally, we give a numerical example to demonstrate the effectiveness and feasibility of the derived theoretical results. [ABSTRACT FROM AUTHOR]