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This study aimed to examine beliefs in repressed memory and dissociative amnesia from a cross-cultural perspective.

Chinese (n = 123) and Belgian student participants (n = 270) received several statements tapping into various dimensions of repressed memory and dissociative amnesia. Participants provided belief ratings for each of these statements. Because the field of psychoanalysis is less well developed in China, it was expected that Chinese participants would believe less in repressed memory and dissociative amnesia than their Belgian counterparts.

Overall, beliefs in repressed memory and dissociative amnesia were high among all participants. Although confirmatory analyses revealed that most belief ratings concerning statements did not statistically significantly differ between the two samples, Chinese participants did statistically believe less that therapy can recover lost traumatic memories than Belgian participants. Also, exploratory analyses showed that Chinese participants were more critical towards the idea that traumatic memories can be unconsciously repressed and that these memories can be accurately retrieved in therapy than Belgian participants. Many participants also confused repressed memory with plausible memory mechanisms such as ordinary forgetting.

The current study extends previous surveys on repressed memory and dissociative amnesia by comparing their beliefs in different cultures.

The purpose of this paper is to understand the natural wind field characteristics of the tunnel entrance section and analyzing the aerodynamic performance of high-speed railway trains (HSRTs) under natural winds.

Three typical tunnel entrance section sites, namely, tunnel–bridge in a dry canyon (TBDC), tunnel–bridge in a river canyon (TBRC) and tunnel–flat ground (TF), are selected to conduct a continuous wind field measurement. Based on the measured wind characteristics, the natural winds of the TBDC and TF sites are reconstituted and imported into the two corresponding full-scale computational fluid dynamics models. The aerodynamic loads of the HSRT running on TBDC and TF with reconstituted winds are simply analyzed.

The von Kármán spectrum can be used to describe the wind field at the tunnel entrance section. In the reconstituted natural wind condition, a time-varying feature of wind speed distribution and leeward side vortex around the HSRT caused by the wind speed fluctuation is found. The fluctuating amplitude of aerodynamic loads at the TBDC infrastructure is up to 97.9% larger than that at the TF infrastructure.

The natural wind characteristics at tunnel entrance sections on the high-speed railway are first measured and analyzed. A numerical reconstitution scheme considering the temporal and spatial variation of natural wind speed is proposed and verified based on field measurement results. The aerodynamic performance of an HSRT under reconstituted natural winds is first investigated.

This paper aims to present a simplified method to predict the pressure of the recess, no matter whether the tilt center coincides with the geometric center of the hydrostatic journal bearings.

To validate the effectiveness of the presented model, computational fluid dynamics (CFD) method and experimental method are performed in this study.

By comparing the CFD results and the experimental results, the pressure of the recess is related to the tilt direction, the tilt center, the width of the land and the circumferential angle of the land.

The mathematic model requires equivalent resistance of land edge – tilt position, tilt direction, tilt angle and the thickness of oil film instead of any digital iteration. Furthermore, a novel experimental apparatus including a circular hydrostatic bearing called ball bearing is designed to study the tilt effect produced by manufacturing error and offset load force on the pressure of the recess.

The paper aims to provide an adaptive neural network controller for permanent magnet synchronous motor (PMSM) under direct torque control (DTC) algorithm to minimize the torque ripple and EMI noise.

The design methodology is based on vector control used for electrical machines. MATLAB simulations supported with experimental study under C++ are used.

The simulated and experimental results show that considerable torque ripple as well as current ripple and EMI noise reduction can be achieved by utilizing adaptive neural switching algorithm to fire the inverter supplying the PMSM.

This research is limited to PMSM, however the research can be extended to include other AC motors as well. In addition, the following points can be studied: the effects of harmonics in control signals on the torque ripple can be analyzed; the actual mathematical relation between the torque and flux ripple can be studied to set the flux and torque bands width in reasonable value; different neural network algorithms can be applied to the system to solve the similar problems.

Based on existing DTC control system, it is only required to change the software switching algorithm, to provide smooth torque, given that the switching frequency of the inverter module is more than or equal to 15 MHz and the system is supplied with timers. In addition a relatively higher DC voltage may be required to achieve higher speed compared with the traditional DTC.

In this paper, the stator flux position, and errors due to deviations from reference values of the torque and stator flux are used to select two active vectors while at the same time the absolute value of the torque error and the stator flux position are used neural network structure to adapt the switching of the inverter in order to control the applied average voltage level in such a way as to minimize the torque ripple, so instead of fixed time table structure, a neural network controller is used to calculate the switching time for the selected vectors and no PI controller is used as the case in the traditional space vector modulation. This work is directed to motor drive system designers who seek highly smooth torque performance with EMI noise reduction.