Microneedles are small-scale devices that may be used for drug delivery and biosensing. In this study, the forces required for mechanical failure, the modes of mechanical failure, as well as the mechanisms for microneedle penetration into porcine skin were examined. Microneedles produced from the acrylate-based polymer e-Shell 200 using an indirect rapid prototyping approach involving two-photon polymerization and poly(dimethylsiloxane) micromolding were found to possess sufficient strength for penetration of porcine skin. The failure forces were an order of magnitude greater than the forces necessary for full insertion into the skin. Bending was the most common form of failure; an increasing aspect ratio and a decreasing tip diameter were associated with lower failure forces. Video captured during skin penetration revealed that microneedle penetration into the skin occurred by means of a series of insertions and not by means of a single insertion event. Images obtained during and after skin penetration confirmed microneedle penetration of skin as well as transdermal delivery of lucifer yellow dye. These findings shed insight into the mechanisms of microneedle penetration and failure, facilitating design improvements for polymer microneedles.

Spaceborne LiDAR has been widely used to obtain forest canopy heights over large areas, but it is still a challenge to obtain spatio-continuous forest canopy heights with this technology. In order to make up for this deficiency and take advantage of the complementary for multi-source remote sensing data in forest canopy height mapping, a new method to estimate forest canopy height was proposed by synergizing the spaceborne LiDAR (ICESat-2) data, Synthetic Aperture Radar (SAR) data, multi-spectral images, and topographic data considering forest types. In this study, National Geographical Condition Monitoring (NGCM) data was used to extract the distributions of coniferous forest (CF), broadleaf forest (BF), and mixed forest (MF) in Hua’ nan forest area in Heilongjiang Province, China. Accordingly, the forest canopy height estimation models for whole forest (all forests together without distinguishing types, WF), CF, BF, and MF were established, respectively, by Radom Forest (RF) and Gradient Boosting Decision Tree (GBDT). The accuracy for established models and the forest canopy height obtained based on estimation models were validated consequently. The results showed that the forest canopy height estimation models considering forest types had better performance than the model grouping all types of forest together. Compared with GBDT, RF with optimal variables had better performance in forest canopy height estimation with Pearson’s correlation coefficient (R) and the root-mean-squared error (RMSE) values for CF, BF, and MF of 0.72, 0.59, 0.62, and 3.15, 3.37, 3.26 m, respectively. It has been validated that a synergy of ICESat-2 with other remote sensing data can make a crucial contribution to spatio-continuous forest canopy height mapping, especially for areas covered by different types of forest.

Wood nondestructive testing (NDT) is one of the high efficient methods in utilizing wood. This paper explained the principle of log defect testing by using stress wave, and analyzed the effects of sensor quantity on defect testing results by using stress wave in terms of image fitting degree and error rate. The results showed that for logs with diameter ranging from 20 to 40 cm, at least 12 sensors were needed to meet the requirement which ensure a high testing accuracy of roughly 90% of fitness with 0.1 of error rate. And 10 sensors were recommended to judge the possible locations of defects and 6 sensors were sufficient to decide whether there were defects or not.

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