Evaluation of feedforward and feedback contributions to hand stiffness and variability in multijoint arm control.

The purpose of this study is to validate a neuromechanical model of the virtual arm (VA) by comparing emerging behaviors of the model to those of experimental observations. Hand stiffness of the VA model was obtained by either theoretical computation or simulated perturbations. Variability in hand position of the VA was generated by adding signal dependent noise (SDN) to the motoneuron pools of muscles. Reflex circuits of Ia, Ib and Renshaw cells were included to regulate the motoneuron pool outputs. Evaluation of hand stiffness and variability was conducted in simulations with and without afferent feedback under different patterns of muscle activations during postural maintenance. The simulated hand stiffness and variability ellipses captured the experimentally observed features in shape, magnitude and orientation. Steady state afferent feedback contributed significantly to the increase in hand stiffness by 35.75±16.99% in area, 18.37±7.80% and 16.15±7.15% in major and minor axes; and to the reduction of hand variability by 49.41±21.19% in area, 36.89±12.78% and 18.87±23.32% in major and minor axes. The VA model reproduced the neuromechanical behaviors that were consistent with experimental data, and it could be a useful tool for study of neural control of posture and movement, as well as for application to rehabilitation.

Dynamic simulation of perturbation responses in a closed-loop virtual arm model.

A closed-loop virtual arm (VA) model has been developed in SIMULINK environment by adding spinal reflex circuits and propriospinal neural networks to the open-loop VA model developed in early study [1]. An improved virtual muscle model (VM4.0) is used to speed up simulation and to generate more precise recruitment of muscle force at low levels of muscle activation. Time delays in the reflex loops are determined by their synaptic connections and afferent transmission back to the spinal cord. Reflex gains are properly selected so that closed-loop responses are stable. With the closed-loop VA model, we are developing an approach to evaluate system behaviors by dynamic simulation of perturbation responses. Joint stiffness is calculated based on simulated perturbation responses by a least-squares algorithm in MATLAB. This method of dynamic simulation will be essential for further evaluation of feedforward and reflex control of arm movement and position.

[Effect of Ce3+ implantation on photoluminescence intensity of Si nanocrystals embedded in superlattices].

In the present paper, SiO/SiO2 superlattices samples were prepared on Si substrates by electron beam evaporation. The samples were annealed in nitrogen atmosphere at high temperature subsequently. And then, Ce3+ ions with a dose of 2.0 x 10(14) and 2.0 x 10(15) cm(-2) respectively were implanted into these samples with formed Si nanocrystals. The photoluminescence (PL) spectra showed that the PL intensities of samples with Ce3+ implanting dropped sharply compared with the samples without Ce3+ implanting. The PL intensity increased gradually with increasing re-annealing temperature, but dropped again when the temperature exceeded 600 degrees C. The PL intensity even could be higher than that of samples without Ce3+ implanting if only the dose of Ce3+ was 2.0 x 10(14) cm(-2). When the dose of Ce3+ was 2.0 x 10(15) cm(-2), the PL intensity couldn't exceed that of samples without Ce3+ implanting even when the re-annealing temperature was 600 degrees C. Further investigations showed that the varieties of the PL intensities were mainly dependent on the re-annealing temperature, which had the best point at 600 degrees C, and the dose of Ce3+ had the right value. Furthermore, the experiment results proved that there was energy transfer from Ce3+ to Si nanocrystals in this kind of structure.

[Deposition and structures analysis of amorphous SiNx films prepared by magnetron sputtering].

Amorphous SiNx films were deposited on p-type Si(100)substrates by magnetron sputtering technology. The samples were then detected by a Bruker Tennsor 27 Fourier transform spectrometer. One intense absorption band of the SiNx films (from 812 to 892 cm(-1)) which was assigned to the stretching vibration mode of Si--N--Si bond was detected by Fourier transform infrared (FTIR) spectroscopy. Obviously, it was showed that a red shift of the absorption peak occurred in the FTIR spectrum with the sputtering power increasing; nevertheless, a blue shift of the absorption peak occurred after annealing with the temperature increasing. In the present paper, the deposition process and inner structures of the SiNx films were studied according to RBM (random bonding model)and CFM (central force model). With the increase in the ratio of N(Si)to N(N), the angle of the Si--N--Si changed and the different structures were formed correspondingly. Therefore the Si--Ny--Si(4-y) (0 < or = y < or = 4) models were set up to explain the inner structure of the SiNx films. The investigation showed that Si--N4 tetrahedron, Si--N--Si3, Si--N2--Si2, Si--N3--Si and Si--Si modes were formed accordingly in the SiNx films with the sputtering power increasing. And five models in total were formed during the deposition process. Different stretching vibration modes of Si--N--Si bond were corresponding to the different inner structures of thin films prepared by different sputtering power. With the temperature increasing, the activity of atoms increased which would let the angle of the Si--N--Si go to identical. As a result, Si3N4 and Si nanocrystals were formed with the phase separation of SiNx films during the annealing process with higher temperature, which would result in a blue shift to 870 cm(-1) (the standard absorption peak of Si3N4).