This study investigated the anaerobic digestion capability of five plants and the effects of copper (Cu) and S,S'-ethylenediaminedisuccinic acid (EDDS, a chelator widely used in chelant-assisted phytoremediation) on biogas production to determine a feasible disposal method for plants used in remediation. The results showed that in addition to Phytolacca americana L., plants such as Zea mays L., Brassica napus L., Elsholtzia splendens Nakai ex F. Maekawa, and Oenothera biennis L. performed well in biogas production. Among these, O. biennis required the shortest period to finish anaerobic digestion. Compared to normal plants with low Cu content, the plants used in remediation with increased Cu levels (100 mg kg(-1)) not only promoted anaerobic digestion and required a shorter anaerobic digestion time, but also increased the methane content in biogas. When the Cu content in plants increased to 500, 1000, and 5000 mg kg(-1), the cumulative biogas production decreased by 12.3%, 14.6%, and 41.2%, respectively. Studies also found that EDDS conspicuously restrained biogas production from anaerobic digestion. The results suggest that anaerobic digestion has great potential for the disposal of contaminated plants and may provide a solution for the resource utilization of plants used in remediation.

The precise information of initial rotor position is very important to high performance Interior Permanent Magnet Synchronous Machine (IPMSM) adopting incremental encoder, which can normally be obtained by the high-frequency (HF) rotating or pulsating voltage injection methods. However, the demodulation procedure may confront with the challenge of constrained stability and limited accuracy. For improving estimation accuracy, an improved impulse injection method with merits of simple and fast is proposed. It is carried out by generating a series of phase-axial injections to calculate the probable rotor position, then injecting two reciprocal voltage pulses to obtain the rotor polarity, and finally injecting iterative voltage vectors to obtain the real position rapidly. During the estimation process, the filters to extract the high frequency current signals are not needed. The method effectiveness is validated by the measured results of IPMSM test platform. In the same time, its application limitation is deduced by comparison with the measured results between IPMSM and surface-mounted PMSM (SPMSM). It is shown that the estimation algorithm is compatible with motor parameter differences and can reduce the influence of inductance saturation and nonlinear voltage error. Therefore, the proposed method not only improves the accuracy and robustness of the PMSM sensorless startup control, but also ensures the fast response.

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Monocular vision-based pose estimation for known uncooperative space targets plays an increasingly important role in on-orbit operations. The existing state-of-the-art methods of space target pose estimation build the 2D-3D correspondences to recover the space target pose, where space target landmark regression is a key component of the methods. The 2D heatmap representation is the dominant descriptor in landmark regression. However, its quantization error grows dramatically under low-resolution input conditions, and extra post-processing is usually needed to compute the accurate 2D pixel coordinates of landmarks from heatmaps. To overcome the aforementioned problems, we propose a novel 1D landmark representation that encodes the horizontal and vertical pixel coordinates of a landmark as two independent 1D vectors. Furthermore, we also propose a space target landmark regression network to regress the locations of landmarks in the image using 1D landmark representations. Comprehensive experiments conducted on the SPEED dataset show that the proposed 1D landmark representation helps the proposed space target landmark regression network outperform existing state-of-the-art methods at various input resolutions, especially at low resolutions. Based on the 2D landmarks predicted by the proposed space target landmark regression network, the error of space target pose estimation is also smaller than existing state-of-the-art methods under all input resolution conditions.