[In Vitro Fatigue Test of Lung Volume Reduction Loop].

Lung volume reduction loop uses bronchoscopic lung volume reduction(BLVR) technology to compress and collapse the necrotic emphysema tissue and exhaust the internal gas to achieve the purpose of lung volume reduction to treat emphysema. After the lung volume reduction loop is implanted into the human body, the compressed part of the lung tissue tends to expand with breathing, which makes the lung volume reduction loop expand into a linear trend periodically. Fatigue resistance is one of the most important performance indexes of the lung volume reduction loop. In the paper, Z-direction vibration fatigue machine was used to simulate the changes of human respiratory cycle movement to test the fatigue performance of lung volume reduction loop, which can provide some reference for the test method of in vitro fatigue performance of lung volume reduction related products in the future.

[Purity measurement of hybrid rice seed Yixiang 725 with visible-near infrared reflectance spectra].

A rapid and non-invasive method was put forward to measure the purity of hybrid rice seed by visible-near infrared reflectance spectra. Ninety hybrid rice seed samples (Yixiang 725) with the purity of 90%-99% were collected using a FieldSpec 3 visible-near infrared spectometer. All samples were divided randomly into two groups, one group with 75 samples used as calibrated set, and the other with 15 samples used as validated set. Based on the spectra in the range of 380-2 400 nm, the regression model was established using the PLS (partial least square), and different spectra pretreatment methods were compared. The study showed that spectra information can be extracted thoroughly by the pretreatment method of first derivative combined with standard normal variate, with the SEC (standard error of calibration) of 0.002 5, SEP (standard error of prediction) of 0.006 6, and determination coefficients of 0.988 4 (calibration set) and 0.922 7 (validation set) respectively. The spectra, which were pretreated with the method of first derivative combined standard normal variate, were analyzed by principal component analysis (PCA). The top 20 principal components, which were computed by PCA and accounted for 86.09% variation of the original spectral information, were used to build BP-ANN model for measuring the purity of hybrid rice seed as the new variables. The study showed that the SEC and SEP of BP-ANN model were 0.001 7 and 0.006 1, and the determination coefficients of that were 0.995 2 (calibration set) and 0.936 9 (validation set) respectively. Therefore, the predictive power of BP-ANN model was better than that of PLS model. Results indicated that it was feasible to measure the purity of the hybrid rice seed by visible-near reflectance spectra as a rapid and non-contact way, and PCA combined with BP-ANN was a preferred method.