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Computational evidence of A-to-I RNA editing
in nucleus transcriptome of Arabidopsis thaliana
Pufeng DU, Yang CHEN, Yanda LI,
Front. Electr. Electron. Eng.. 2009, 4 (4): 349-361.
https://doi.org/10.1007/s11460-009-0053-7
RNA editing is a mechanism that can increase the complexity of the transcriptome via the insertion, deletion, or substitution of single or multiple nucleotides of mRNA sequences. In the last two decades, A-to-I RNA editing, which is catalyzed by the ADAR family enzymes, was discovered in many metazoans. C-to-U and U-to-C RNA editing were found in the mitochondria and plastids of plants. However, there is no report about RNA editing in plant nucleus transcriptome yet. Here, by integrating resources from public databases with computational methods, this paper proposes that A-to-I RNA editing mechanism may exist in the nucleus of Arabidopsis thaliana. Some characteristics of the potential A-to-I RNA editing sites in Arabidopsis thaliana are similar to those we have known in animals.
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Shared-p-cycles method for design of survivable
WDM networks
Zhenrong ZHANG, Lixin ZHU, Zhengbin LI, Anshi XU,
Front. Electr. Electron. Eng.. 2009, 4 (4): 362-370.
https://doi.org/10.1007/s11460-009-0057-3
In future high-capacity wavelength division multiplexed (WDM) optical networks, the failure of a network component such as a fiber link can lead to severe disruption in the networks’ traffic. Hence, it is imperatively important to provide fast and full protection in WDM optical networks. In this paper, we propose a new approach, called shared preconfigured protection cycles (shared-p-cycles), for the design of survivable WDM networks. We develop an integer linear program (ILP) formulation to solve the problem of shared-p-cycles design for WDM networks with and without wavelength conversion. Numerical results show that the shared-p-cycles design is more efficient in the use of spare capacity and requires much less spare capacity than the conventional p-cycles design.
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Convergence analysis of self-tuning Riccati equation
for systems with correlation noises
Chenjian RAN, Zili DENG, Guili TAO, Jinfang LIU,
Front. Electr. Electron. Eng.. 2009, 4 (4): 409-416.
https://doi.org/10.1007/s11460-009-0056-4
For linear discrete time-invariant stochastic system with correlated noises, and with unknown state transition matrix and unknown noise statistics, substituting the online consistent estimators of the state transition matrix and noise statistics into steady-state optimal Riccati equation, a new self-tuning Riccati equation is presented. A dynamic variance error system analysis (DVESA) method is presented, which transforms the convergence problem of self-tuning Riccati equation into the stability problem of a time-varying Lyapunov equation. Two decision criterions of the stability for the Lyapunov equation are presented. Using the DVESA method and Kalman filtering stability theory, it proves that with probability 1, the solution of self-tuning Riccati equation converges to the solution of the steady-state optimal Riccati equation or time-varying optimal Riccati equation. The proposed method can be applied to design a new self-tuning information fusion Kalman filter and will provide the theoretical basis for solving the convergence problem of self-tuning filters. A numerical simulation example shows the effectiveness of the proposed method.
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Controller design for 2-DOF underactuated mechanical
systems based on controlled Lagrangians and application to Acrobot
control
Maoqing LI,
Front. Electr. Electron. Eng.. 2009, 4 (4): 417-439.
https://doi.org/10.1007/s11460-009-0063-5
On the basis of controlled Lagrangians, a controller design is proposed for underactuated mechanical systems with two degrees of freedom. A new kinetic energy equation (K-equation) independent of the gyroscopic forces is found due to the use of their property. As a result, the necessary and sufficient matching condition comprises the new K-equation and the potential energy equation (P-equation) cascaded, the regular condition, and the explicit gyroscopic forces. Further, for two classes of input decoupled systems that cover the main benchmark examples, the new K-equation, respectively, degenerates from a quasilinear partial differential equation (PDE) into an ordinary differential equation (ODE) under some choice and into a homogeneous linear PDE with two kinds of explicit general solutions. Benefiting from one of the general solutions, the obtained smooth state feedback controller for the Acrobots is of a more general form. Specifically, a constant fixed in a related paper by the system parameters is converted into a controller parameter ranging over an open interval along with some new nonlinear terms involved. Unlike what is mentioned in the related paper, some categories of the Acrobots cannot be stabilized with the existing interconnection and damping assignment passivity based control (IDA-PBC) method. As a contribution, the system can be locally asymptotically stabilized by the selection of the new controller parameter except for only one special case.
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Plastic wastes recovery using electrostatic forces
A. TILMATINE, S. BENDIMERAD,
Front. Electr. Electron. Eng.. 2009, 4 (4): 446-450.
https://doi.org/10.1007/s11460-009-0062-6
Among the separation techniques used in industry, the triboelectric separation of insulating particles using rotary tube is an efficient technology employed in waste recovery and mineral industries. This process, also called free-fall triboelectric separation, is widely used for the sorting and the purification of granular materials resulting from industrial plastic wastes. This paper aims at the achievement of a comprehensive description of a laboratory triboelectric separator built up by the authors and its utilization for an experimental study carried out on granular samples containing particles of polyvinyl chloride (PVC) and polyethylene (PE). Thus, among the variable factors of the process, we analyzed the influence of the most important ones, i.e., the rotational speed of the cylinder n (rpm), the applied high voltage U (kV), the charging time of the particles t (s), the mass of the sample m (g), and the composition percentage of the sample Cp (%).
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