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The exploitation of intersatellite links (ISLs) makes the LEO satellite constellation based Internet service widely favored due to its advantages of low-latency and high-speed communications. However, considering the time-varying network topology, limited on-board resources, and high node failure probability, the design of link assignment has become one of the key challenges for the future megaconstellation. To solve this problem, we adopt the idea of modified finite state automaton (FSA) to model the LEO satellite network and use nondominated sorting genetic algorithm (NSGA-II) to optimize the minimum residual capacity and the maximum transmission delay. The simulation results show that our method is more invulnerable and flexible, which is fit for megaconstellations. This work can provide comprehensive guidance on intersatellite link assignment for future megaconstellations.

The typical representative of pathological tremor is Parkinson's disease. One of the pathogenesis is that the synchronized neural oscillations within and between brain areas are affected. Inspired by this, this work proposes an algorithm based on neural oscillator to extract voluntary motion and estimate tremor motion in real time, which is named as RTBNO. This algorithm is composed of multiple adaptive modified Hopf oscillators linear combiner. The combiner is divided into two parts: one is used to estimate tremor motion and the other is applied to estimate voluntary motion. As it is updated iteratively in real time, this method has no phase delay. The performance of the proposed method was verified by the simulated action tremor and the actual experimental results of twenty Parkinson's disease patients. For the rest tremor signals of patients, the mean Root Mean Square Error (RMSE) values between the estimated signal and the actual signal was 0.0272±0.0077. The mean RMSE values between the estimated voluntary movement from action tremor and the actual voluntary movement were 0.0360±0.0097 (pick and put motion) and 0.0380±0.0083 (drawing motion). The execution time for the corresponding 10 seconds data was 0.0478s. The comparison results between the proposed method and the existing methods demonstrated the effectiveness of the proposed method.

Applying chaos theory for secure digital communications is promising and it is well acknowledged that in such applications the underlying chaotic systems should be carefully chosen. However, the requirements imposed on the chaotic systems are usually heuristic, without theoretic guarantee for the resultant communication scheme. Among all the primitives for secure communications, it is well-accepted that (pseudo) random numbers are most essential. Taking the well-studied two-dimensional coupled map lattice (2D CML) as an example, this paper performs a theoretical study towards pseudo-random number generation with the 2D CML. In so doing, an analytical expression of the Lyapunov exponent (LE) spectrum of the 2D CML is first derived. Using the LEs, one can configure system parameters to ensure the 2D CML only exhibits complex dynamic behavior, and then collect pseudo-random numbers from the system orbits. Moreover, based on the observation that least significant bit distributes more evenly in the (pseudo) random distribution, an extraction algorithm E is developed with the property that, when applied to the orbits of the 2D CML, it can squeeze uniform bits. In implementation, if fixed-point arithmetic is used in binary format with a precision of $z$ bits after the radix point, E can ensure that the deviation of the squeezed bits is bounded by $2^{-z}$ . Further simulation results demonstrate that the new method not only guide the 2D CML model to exhibit complex dynamic behavior, but also generate uniformly distributed independent bits. In particular, the squeezed pseudo random bits can pass both NIST 800-22 and TestU01 test suites in various settings. This study thereby provides a theoretical basis for effectively applying the 2D CML to secure communications., Comment: 10 pages, 11figures

Photoinduced carriers recombine almost twice slower and diffuse 20% faster in the disordered, β-phased samples than in the ordered, γ-phased ones.

A mixed-integer programming (MIP) problem contains both constraints and integer restrictions. Integer restrictions divide the feasible region defined by constraints into multiple discontinuous feasible parts. In particular, the number of discontinuous feasible parts will drastically increase with the increase of the number of integer decision variables and/or the size of the candidate set of each integer decision variable. Due to the fact that the optimal solution is located in one of the discontinuous feasible parts, it is a challenging task to solve a MIP problem. This article presents a cutting and repulsion-based evolutionary framework (called CaR) to solve MIP problems. CaR includes two main strategies: 1) the cutting strategy and 2) the repulsion strategy. In the cutting strategy, an additional constraint is constructed based on the objective function value of the best individual found so far, the aim of which is to continuously cut unpromising discontinuous feasible parts. As a result, the probability of the population entering a wrong discontinuous feasible part can be decreased. In addition, in the repulsion strategy, once it has been detected that the population has converged to a discontinuous feasible part, the population will be reinitialized. Moreover, a repulsion function is designed to repulse the previously explored discontinuous feasible parts. Overall, the cutting strategy can significantly reduce the number of discontinuous feasible parts and the repulsion strategy can probe the remaining discontinuous feasible parts. Sixteen test problems developed in this article and two real-world cases are used to verify the effectiveness of CaR. The results demonstrate that CaR performs well in solving MIP problems.

Navigation control of microrobots in vivo has great potential in precision medicine and has attracted considerable attention in recent years. The control performance of the existing methods is considerably affected by hysteresis nonlinearity. This article presents a robust control method that can overcome hysteresis influence in navigating a microrobot actuated by an electromagnetic coil system. A motion planner that combines the breadth-first search (BFS) method and genetic algorithm (GA) is used to plan a reliable and flexible trajectory for the microrobot navigation. To compensate for hysteresis nonlinearity existing in the system, the Prandtl-Ishlinskii (PI) model is introduced. A robust controller that integrates adaptive sliding mode control (ASMC) and nonlinear disturbance observer is designed to guarantee the stability and accuracy of the microrobot in motion. Experiments have been performed to demonstrate the effectiveness of the proposed approach. The success of this research will advance the microrobot navigation for in vivo applications.

In this paper, a millimeter-wave Y-shaped circulator based on magneto photonic crystals is demonstrated. The triangular lattice photonic crystal with Y-shaped line defect waveguide is constructed by Al2O3 ceramic posts. The magneto-optical cavity resonator in the junction of Y-shaped waveguide consists of two cylindrical ferrites and two triangular metal pedestals. The transmission characteristics of the circulator experimented under the external magnetic bias H0 = 300 Gs. In working frequency range 24∼28 GHz the isolation of circulator is better than 20 dB, and the best insertion loss is as low as 0.2 dB. The experimented results are well agreed with the simulation results.