The double charm decays of BcB_c Meson in the Perturbative QCD Approach

We make a systematic investigation on the double charm decays of $B_c$ meson, by employing the perturbative QCD approach based on $k_T$ factorization. It is found that the non-factorizable emission diagrams are not negligible in these channels. We predict the branching ratios of these $B_c$ decays and also the transverse polarization fractions of $B_c\rightarrow D_{(s)}^{*+}\bar D^{*0}, D_{(s)}^{*+}D^{*0}$ decays, % where V denote the vector $D^*_{(s)}$ meson. We find that the magnitudes of the branching ratios of the decays $B_c\rightarrow D_s\bar{D}^0$ and $B_c\rightarrow D_sD^0$ are very close to each other, which are well suited to extract the Cabibbo-Kobayashi-Maskawa angle $\gamma$ through the amplitude relations. In addition, a large transverse polarization contribution that can reach $50$ is predicted in some of the $B_c$ meson decay to two vector charmed mesons.Comment: 22 pages, 5 tables, to appear at PRD. arXiv admin note: text overlap with arXiv:1112.125

Entropy Model of Dynamic Bus Dispatching Based on the Prediction of Back-Station Time

In the actual operation of a bus, due to the influences of the passenger flow, traffic conditions and other factors, the vehicle back-station time is often delayed, which brings difficulties in commuting according to a timetable that results in the discontinuity of the bus. This is also the main disadvantage of static bus scheduling. Therefore, the “Entropy model of dynamic bus dispatching based on the prediction of back-station time” is proposed, which can be used for decreasing the passive effect of discontinuity by extending the departure interval of an early bus in advance, and to realize fairness in adjustments of the departure interval by using entropy theory. Finally, the model is validated by two examples, and the results show that the model can match the distribution pattern of the bus departure interval before and after an adjustment and as far as possible, it can reduce bus breaks, balance the occupancy rate and improve the stability of bus operations

Entropy Model of Dynamic Bus Dispatching Based on the Prediction of Back-Station Time

In the actual operation of a bus, due to the influences of the passenger flow, traffic conditions and other factors, the vehicle back-station time is often delayed, which brings difficulties in commuting according to a timetable that results in the discontinuity of the bus. This is also the main disadvantage of static bus scheduling. Therefore, the “Entropy model of dynamic bus dispatching based on the prediction of back-station time” is proposed, which can be used for decreasing the passive effect of discontinuity by extending the departure interval of an early bus in advance, and to realize fairness in adjustments of the departure interval by using entropy theory. Finally, the model is validated by two examples, and the results show that the model can match the distribution pattern of the bus departure interval before and after an adjustment and as far as possible, it can reduce bus breaks, balance the occupancy rate and improve the stability of bus operations

An Evaluation of MEMS-IMU Performance on the Absolute Trajectory Error of Visual-Inertial Navigation System

Nowadays, accurate and robust localization is preliminary for achieving a high autonomy for robots and emerging applications. More and more, sensors are fused to guarantee these requirements. A lot of related work has been developed, such as visual-inertial odometry (VIO). In this research, benefiting from the complementary sensing capabilities of IMU and cameras, many problems have been solved. However, few of them pay attention to the impact of different performance IMU on the accuracy of sensor fusion. When faced with actual scenarios, especially in the case of massive hardware deployment, there is the question of how to choose an IMU appropriately? In this paper, we chose six representative IMUs with different performances from consumer-grade to tactical grade for exploring. According to the final performance of VIO based on different IMUs in different scenarios, we analyzed the absolute trajectory error of Visual-Inertial Systems (VINS_Fusion). The assistance of IMU can improve the accuracy of multi-sensor fusion, but the improvement of fusion accuracy with different grade MEMS-IMU is not very significant in the eight experimental scenarios; the consumer-grade IMU can also have an excellent result. In addition, the IMU with low noise is more versatile and stable in various scenarios. The results build the route for the development of Inertial Navigation System (INS) fusion with visual odometry and at the same time, provide a guideline for the selection of IMU

Analysis of the Thermally Induced Packaging Effects on the Frequency Drift of Micro-Electromechanical System Resonant Accelerometer

Due to the working principle of MEMS resonant accelerometers, their thermally induced frequency drift is an inevitable practical issue for their extensive application. This paper is focused on reducing the thermally induced packaging effects on the frequency drift. A leadless ceramic chip carrier package with a stress-buffering layer was proposed for a MEMS resonant accelerometer, and the influences of packaging structure parameters on the frequency drift were investigated through finite element simulations and verified experimentally. Because of the thermal mismatch between dissimilar materials, the thermo-mechanical stress within the resonant beam leads to a change in the effective stiffness and causes the frequency drift to decrease linearly with increasing temperature. Furthermore, our investigations reveal that increasing the stress-buffering layer thickness and reducing the solder layer thickness can significantly minimize the thermo-mechanical stress within the resonant beam. As the neutral plane approaches the horizontal symmetry plane of the resonant beam when optimizing the packaging structure, the effects of the compressive and tensile stresses on the effective stiffness of the resonant beam will cancel each other out, which can dramatically reduce the frequency drift. These findings provide guidelines for packaging design through which to improve the temperature stability of MEMS resonant accelerometers

Enhancing Performance of Reservoir Computing System Based on Coupled MEMS Resonators

Reservoir computing (RC) is an attractive paradigm of a recurrent neural network (RNN) architecture, owning to the ease of training and existing neuromorphic implementation. Its simulated performance matches other digital algorithms on a series of benchmarking tasks, such as prediction tasks and classification tasks. In this article, we propose a novel RC structure based on the coupled MEMS resonators with the enhanced dynamic richness to optimize the performance of the RC system both on the system level and data set level. Moreover, we first put forward that the dynamic richness of RC comprises linear dynamic richness and nonlinear dynamic richness, which can be enhanced by adding delayed feedbacks and nonlinear nodes, respectively. In order to set forth this point, we compare three typical RC structures, a single-nonlinearity RC structure with single-feedback, a single-nonlinearity RC structure with double-feedbacks, and the couple-nonlinearity RC structure with double-feedbacks. Specifically, four different tasks are enumerated to verify the performance of the three RC structures, and the results show the enhanced dynamic richness by adding delayed feedbacks and nonlinear nodes. These results prove that coupled MEMS resonators offer an interesting platform to implement a complex computing paradigm leveraging their rich dynamical features

A decouple-decomposition noise analysis model for closed-loop mode-localized tilt sensors

Abstract The development of mode-localized sensors based on amplitude output metrics has attracted increasing attention in recent years due to the potential of such sensors for high sensitivity and resolution. Mode-localization phenomena leverage the interaction between multiple coupled resonant modes to achieve enhanced performance, providing a promising solution to overcome the limitations of traditional sensing technologies. Amplitude noise plays a key role in determining the resolution of mode-localized sensors, as the output metric is derived from the measured AR (amplitude ratio) within the weakly coupled resonator system. However, the amplitude noise originating from the weakly coupled resonator’s closed-loop circuit has not yet been fully investigated. This paper presents a decouple-decomposition (DD) noise analysis model, which is applied to achieve high resolution in a mode-localized tilt sensor based on a weakly coupled resonator closed-loop circuit. The DD noise model separates the weakly coupled resonators using the decoupling method considering the nonlinearity of the resonators. By integrating the decoupled weakly coupled resonators, the model decomposes the weakly coupled resonator’s closed-loop circuit into distinct paths for amplitude and phase noise analyses. The DD noise model reveals noise effects at various circuit nodes and models the system noise in the closed-loop circuit of the weakly coupled resonators. MATLAB/Simulink simulations verify the model’s accuracy when compared to theoretical analysis. At the optimal operating point, the mode-localized tilt sensor achieves an input-referred instability of 3.91 × 10-4° and an input-referred AR of PSD of 2.01 × 10-4°⁄√Hz using the closed-loop noise model. This model is also applicable to other varieties of mode-localized sensors