Development and analysis of two-dimensional point-ahead angle mechanism for space gravitational-wave detection.

To detect low-frequency gravitational waves, it is necessary to eliminate the interference of geo-noise and build a laser interference gravitational-wave detection device in space. Space gravitational-wave detection missions, namely Taiji, LISA, and Tianqin, have been planning to achieve picometer sensitivity on an interferometer arm of several million kilometers to meet the gravitational-wave detection requirements. Because of the orbit evolution and the time delay in interferometer arms, the direction of the transmitted laser beam changes; consequently, a remote telescope cannot receive the laser beam to complete the inter-satellite laser interference. In this study, a two-dimensional point-ahead angle mechanism (2DPAAM) is designed and demonstrated to solve the aforementioned problem. Based on the design concept of aligning the rotation center with the mirror surface center, the 2DPAAM employs a four-link flexible-hinge structure, length expanding and contracting piezoelectric stack actuators, and closed-loop control of capacitive sensors to realize two-dimensional picometer-stable, high-precision rotation. A static model is established to analyze the rotational characteristics, and finite element analysis is performed to study the mechanical properties and to verify the rotational characteristics. The yaw and pitch stiffness errors are ∼0.93% and 5.9%, respectively, when the theoretical results are compared with the simulation results. A series of experiments are conducted on the developed 2DPAAM, and the results show that the rotary ranges of yaw and pitch motions attain ±270 and ±268 µrad, respectively. The rotational accuracies of both yaw and pitch motions attain ∼0.35 µrad, and the optical path difference is less than 10pm/Hz when the frequency is between 1 mHz and 1 Hz, by analogy.

[Study of the degree in white matter structural networks in the glioma based on diffusion tensor tractography].

At present, an effective detecting method for brain function impairment for the patients with the glioma is urgently needed in clinic, because it may help us understand its pathogenesis. This paper proposes a method of combining diffusion tensor tracing technology and 'small world' network. It utilizes the degree of brain function network to study complex network topological properties of the patients with the glioma in temporal lobe area. The experimental results showed that the brain networks of the patients with the glioma of different grades were destroyed compared with those of the normal persons, but the destruction degree is independent of the tumor grades. The distribution of functional connections is index truncated power-law accompanied by significant heterogeneity. Meanwhile, the stronger functional areas of information in the glioma have transferred and there exists lack of language function area and sensory function area.