Distribution patterns of plant communities and their associations with environmental soil factors on the eastern shore of Lake Taihu, China

Introduction: Plant communities and soil factors might interact with each other in different temporal and spatial scales, which can influence the patterns and processes of the wetland ecosystem. To get a better understanding of the distribution of plants in wetlands and analyze their associations with environmental soil factors, the structure and types of plant communities in the eastern shore area of Lake Taihu were analyzed by two-way indicator species analysis and canonical correspondence analysis (CCA) ordination. The spatial distribution patterns of vegetation and the main factors affecting the distributions were investigated.Outcomes: Sixty-six sampling sites were selected to obtain vegetation species and soil environmental factor data. Results showed that 22 species from the 66 sites could be divided into seven communities: I: Arundo donax; II: A. donax + Phragmites australis; III: Zizania latifolia + Typha orientalis; IV: P. australis + Alternanthera philoxeroides + Polygonum hydropiper; V: P. australis; VI: P. australis + Humulus scandens; and VII: Erigeron acer + Ipomoea batatas + Rumex acetosa. Plant species and soil factors in the CCA analysis showed that I. batatas, E. acer, Chenopodium album, Polygonum lapathifolium, and Acalypha australis were mainly affected by pH, whereas Echinochloa crus-galli, Setaria viridis, and H. scandens were mainly affected by soil total phosphorus. Mentha canadensis and A. donax were mainly affected by soil conductivity, A. philoxeroides was mainly affected by soil organic matter and, Z. latifolia, Metaplexis japonica and P. hydropiper were mainly affected by available phosphorus.Conclusion:These results indicated that different plants adapted to different soil environmental factors and provided basic information on the diversity of Lake Taihu wetland vegetation

Can China’s soybean production satisfy its demand in the future? The efficiency analysis of China’s soybean production

The paper reviews soybean production and its demand change in China. It proposes that the improvement in technical efficiency of soybean production is indispensable for the increase of soybean output and, in turn, to satisfy the domestic demand for soybean. The paper investigates the technical efficiency, scale efficiency, profit efficiency, and Malmquist index of China’s soybean productivity. According to the result of estimate, the paper proposes that the rapid improvement of China’s soybean production is difficult and China will continue to import soybeans including GM soybeans to satisfy its domestic demand in the future

Adaptive Smoothing Power Following Control Strategy Based on an Optimal Efficiency Map for a Hybrid Electric Tracked Vehicle

The series hybrid electric powertrain is the main architecture of the hybrid electric tracked vehicle. For a series tracked hybrid electric bulldozer (HEB), frequent fluctuations of the engine working points, deviation of the genset working points from the pre-set target trajectory due to an insufficient response, or interference of the hydraulic pump consumed torque, will all result in increased fuel consumption. To solve the three problems of fuel economy, an adaptive smooth power following (ASPF) control strategy based on an optimal efficiency map is proposed. The strategy combines a fuzzy adaptive filter algorithm with a genset’s optimal efficiency, which can adaptively smooth the working points of the genset and search the trajectory for the genset’s best efficiency when the hydraulic pump torque is involved. In this study, the proposed strategy was compared on the established HEB hardware in loop (HIL) platform with two other strategies: a power following strategy in a preliminarily practical application (PF1) and a typical power following strategy based on the engine minimum fuel consumption curve (PF2). The results of the comparison show that (1) the proposed approach can significantly reduce the fluctuation and pre-set trajectory deviation of the engine and generator working points; (2) the ASPF strategy achieves a 7.8% improvement in the equivalent fuel saving ratio (EFSR) over the PF1 strategy, and a 3.4% better ratio than the PF2 strategy; and (3) the ASPF strategy can be implemented online with a practical controller

Impacts of Integration of Wind Farms on Power System Transient Stability

To compensate for the ever-growing energy gap, renewable resources have undergone fast expansions worldwide in recent years, but they also result in some challenges for power system operation such as the static security and transient stability issues. In particular, as wind power generation accounts for a large share of these renewable energy and reduces the inertia of a power network, the transient stability of power systems with high-level wind generation is decreased and has attracted wide attention recently. Effectively analyzing and evaluating the impact of wind generation on power transient stability is indispensable to improve power system operation security level. In this paper, a Doubly Fed Induction Generator with a two-lumped mass wind turbine model is presented firstly to analyze impacts of wind power generation on power system transient stability. Although the influence of wind power generation on transient stability has been comprehensively studied, many other key factors such as the locations of wind farms and the wind speed driving the wind turbine are also investigated in detail. Furthermore, how to improve the transient stability by installing capacitors is also demonstrated in the paper. The IEEE 14-bus system is used to conduct these investigations by using the Power System Analysis Tool, and the time domain simulation results show that: (1) By increasing the capacity of wind farms, the system instability increases; (2) The wind farm location and wind speed can affect power system transient stability; (3) Installing capacitors will effectively improve system transient stability

Root growth, available soil water, and water-use efficiency of winter wheat under different irrigation regimes applied at different growth stages in North China

Field experiments were conducted at the Luancheng Agro-Ecosystem Experimental Station of the Chinese Academy of Sciences during the winter wheat growing seasons in 2006-2007 and 2007-2008. Experiments involving winter wheat with 1, 2, and 3 irrigation applications at jointing, heading, or milking were conducted, and the total irrigation water supplied was maintained at 120 mm. The results indicated that irrigation during the later part of the winter wheat growing season and increase in irrigation frequency decreased the available soil water; this result was mainly due to the changes in the vertical distribution of root length density. In 30-cm-deep soil profiles, 1 time irrigation at jointing resulted in the highest root length density. With regard to evapotranspiration (ET), there was no significant (LSD, P Root length density Available soil water Water-use efficiency Winter wheat Deficit irrigation

温度对坏鳃指环虫产卵、孵化和发育的影响

实验研究了离体条件下温度对坏鳃指环虫（Dactylogyrus vastator）产卵和孵化的影响,以及在20℃、在体条件下坏鳃指环虫的产卵和发育过程。在离体条件下,坏鳃指环虫的平均产卵量随着温度的升高而增加,在4、10、20、30和35℃时,其平均产卵量分别为0.25、5.9、9.1、9.2和13.4枚/虫;除4℃外,绝大多数虫卵是在离体后的前5h内产出;然而,在体条件下虫体的产卵是连续且稳定的,在20℃条件下平均产卵量为6.5枚/（虫·d）。虫卵的孵化时间和孵化持续的时间随着温度的升高而减少,在10、20、30和35℃条件下,孵化时间和孵化持续时间分别为19d、3d、2d、36h和24d、5d、5d、3d,而最高的孵化率（65.5%）却出现在30℃。在20℃条件下,纤毛幼虫在感染7d后90%的虫体都已成熟,因此,在此温度条件下坏鳃指环虫由虫卵发育到成虫大约需要8—10d。为了有效控制指环虫病的暴发,在第一次用药1周后要进行第二次用药

Theoretical and numerical investigation into brush seal hysteresis without pressure differential

Brush seal is a novel type contact seal, and it is well-known due to its excellent performance. However, there are many intrinsic drawbacks, such as hysteresis, which need to be solved. This article focused on modeling hysteresis in both numerical way and analytic way without pressure differential. The numerical simulation was solved by the finite element method. General contact method was used to model the inter-bristle contact, bristle-rotor contact, and bristle-backplate contact. Bristle deformation caused by both vertical and axial tip force was used to validate the numerical model together with reaction force. An analytic model in respect of the strain energy was created. The influence of structure parameters on the hysteresis ratio, with the emphasis on the derivation of hysteresis ratio formula for brush seals, was also presented. Both numerical model and analytic model presented that cant angle is the most influential factor. The aim of the article is to provide a useful theoretical and numerical method to analyze and predict the hysteresis. This work contributes the basis for future hysteresis investigation with pressure differential.open access</p

Dictionary Learning for Few-Shot Remote Sensing Scene Classification

With deep learning-based methods growing (even with scarce data in some fields), few-shot remote sensing scene classification (FSRSSC) has received a lot of attention. One mainstream approach uses base data to train a feature extractor (FE) in the pre-training phase and employs novel data to design the classifier and complete the classification task in the meta-test phase. Due to the scarcity of remote sensing data, obtaining a suitable feature extractor for remote sensing data and designing a robust classifier have become two major challenges. In this paper, we propose a novel dictionary learning (DL) algorithm for few-shot remote sensing scene classification to address these two difficulties. First, we use natural image datasets with sufficient data to obtain a pre-trained feature extractor. We fine-tune the parameters with the remote sensing dataset to make the feature extractor suitable for remote sensing data. Second, we design the kernel space classifier to map the features to a high-dimensional space and embed the label information into the dictionary learning to improve the discrimination of features for classification. Extensive experiments on four popular remote sensing scene classification datasets demonstrate the effectiveness of our proposed dictionary learning method