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1.
Peng Chen Pranjal Swarup Wojciech Michal Matkowski Adams Wai Kin Kong Su Han Zhihe Zhang Hou Rong 《Ecology and evolution》2020,10(7):3561-3573
- As a highly endangered species, the giant panda (panda) has attracted significant attention in the past decades. Considerable efforts have been put on panda conservation and reproduction, offering the promising outcome of maintaining the population size of pandas. To evaluate the effectiveness of conservation and management strategies, recognizing individual pandas is critical. However, it remains a challenging task because the existing methods, such as traditional tracking method, discrimination method based on footprint identification, and molecular biology method, are invasive, inaccurate, expensive, or challenging to perform. The advances of imaging technologies have led to the wide applications of digital images and videos in panda conservation and management, which makes it possible for individual panda recognition in a noninvasive manner by using image‐based panda face recognition method.
- In recent years, deep learning has achieved great success in the field of computer vision and pattern recognition. For panda face recognition, a fully automatic deep learning algorithm which consists of a sequence of deep neural networks (DNNs) used for panda face detection, segmentation, alignment, and identity prediction is developed in this study. To develop and evaluate the algorithm, the largest panda image dataset containing 6,441 images from 218 different pandas, which is 39.78% of captive pandas in the world, is established.
- The algorithm achieved 96.27% accuracy in panda recognition and 100% accuracy in detection.
- This study shows that panda faces can be used for panda recognition. It enables the use of the cameras installed in their habitat for monitoring their population and behavior. This noninvasive approach is much more cost‐effective than the approaches used in the previous panda surveys.
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The mechanism of mass collaboration in risk management was studied during the Sichuan earthquake under a Web-based “PeopleFinder” project, where information is contributed and shared among mass contributors. The case study is provided by a great earthquake that happened in Wenchuan County, Sichuan Province, of southwestern China at 2:28 p.m. on May 12, 2008. We witnessed and experienced the rescue and relief efforts for the great earthquake. In this article, two fundamental frameworks are developed to study the mechanism of mass collaboration. Mass collaboration is proven to be effective in a big public crisis such as the Sichuan earthquake. 相似文献
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After observing specimens of Calligonum pumilum Losinsk. and C. juochiangense Y. X. Liou in both the field and in herbarium collections, it was found that the morphological characters of these two species are quite different, especially with respect of the twisted direction of fruit ribs, number of bristle rows along each rib, rigidity and degree of interweaving of bristles, as well as their geographic distribution. Therefore, it is concluded that C. pumilum and C. juochiangense should be accepted as two independent species. 相似文献
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用金桔茎段为外植体,培养在附加1.0毫克/升BA和0.l毫克/升IBA的MS培养基上,诱导愈伤组织和芽形成。观察了愈伤组织和芽形成过程中的组织细胞学变化。培养一周后,在茎组织切口两端开始膨大,细胞增大和开始分裂。培养两周后,开始形成瘤状愈伤组织。在愈伤组织中有形成层状分生组织、维管组织结节和分生细胞团。培养四周后,表层的分生细胞团分化形成大量芽原基,同时愈伤组织深层也出现分生细胞团。带节茎段可从切口两端的愈伤组织分化形成芽,亦可从叶腋的潜伏芽直接形成芽。 相似文献
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酸性水和投加铝、钙对鲢鱼早期发育和鳃超微结构的影响 总被引:4,自引:1,他引:3
在实验室条件下,研究了酸性水和投加铝、钙对鲢鱼胚胎孵化和鱼苗存活以及幼鱼鳃超微结构的影响。pH4.0引起所有胚胎在24小时内死亡,暴露于pH4.5—6.0的胚胎孵化率和暴露于pH4.0—6.0的5—15日龄鱼苗存活率随pH值上升而增高。投加0.5mg Al~(3+)/L使在酸性pH暴露条件下的胚胎孵化率和鱼苗存活率进一步降低。投加3.0mg Ca~(2+)/L可显著提高暴露于pH4.5和5.0的胚胎孵化率;投加2.0mg Ca~(2+)/L可在一定程度上提高暴露于pH4.5和5.0的鱼苗存活率。幼苗经pH4.5暴露8小时后出现严重的鳃超微结构损害;投加1.0mg Al~(3+)/L使鳃结构损害加剧;投加5.0mg Ca~(2+)/L可明显缓解酸性水对鳃的损害。 相似文献
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