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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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在鉴定我囱青海省单蚤属(Monopsyllus Kolenati,1857)的跳蚤标本时,除检出别人已记述过的不等单蚤[Monopsyllus anisus(Rotnschild,1907)],新月单蚤(Monopsyllusscaloni Vovchinskaya,1950)和冯氏单蚤(Monopsyllus fengi Liu,Xie et Wang)(新种,待发表)外,尚发现两个在形态上都接近花鼠单蚤[Monopsyllus indages(Rothschild,1908)]的新种。由于两新种阳茎钩突特别,故分别命名为钩状单蚤Monopsyllus hamutus,新种和文状单蚤Monopsyllus forficus,新种。鉴别这三个蚤种的重要特征如表1所示。 相似文献
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大鼠隔—海马通路损伤对海马内递质含量及酶活力的影响 总被引:3,自引:0,他引:3
单侧切断大鼠海马缴和部分穹窿可使海马部分去神经。损伤后7d,海马内胆碱能系统中乙酰胆碱(ACh)含量下降72.5%,胆碱乙酰基转移酶(ChAT)活力下降45.7%,胆碱酯酶活力下降52.2%,在单胺能系统中,去甲肾上腺素(NA)含量下降16.3%,多巴胺(DA)含量下降31.3%,5-羟色胺含量下降30.3%。在损伤过程中,海马内氨基酸含量没有改变。实验结果表明,海马缴和穹窿是脑内胆碱能和单胺能传入神经到达海马靶区的部分共同通路。 相似文献
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家兔面神经后核内侧区在呼吸节律起源中的作用 总被引:36,自引:8,他引:28
从腹侧面暴露家兔延髓,脑内微量注射1%普鲁卡因阻滞面神经后核内侧区(mNRF),全部动物(n=20)一次注射(0.3—1.0μl)后即能可逆地消除呼吸节律。区域对照显示此区非常局限,范围约1.0×1.0×1.0mm。组织学检查表明为面神经后核内侧区。本文分析了 mNRF的呼吸相关神经元(RRNs)的放电形式。在 mNRF 有较多的呼气(E)神经元和呼气-吸气跨时相(E-IPS)神经元。在阻滞 mNRF 引起呼吸停止期间,观察到低位延髓背侧呼吸群(DRG)和腹侧呼吸群(VRG)尾端区 RRNs 放电的节律性消失,表现连续放电或停止放电。电刺激DRG,VRG 尾端区,只能诱发短串的膈神经放电,而不能产生节律性发放。说明这些区域的RRNs 无自动节律性活动的能力。结果表明,面神经后核内侧区与呼吸节律发生有关,它可能是呼吸节律发生器的一个重要的所在部位。 相似文献
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