A study on giant panda recognition based on images of a large proportion of captive pandas

1. 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.
2. 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.
3. The algorithm achieved 96.27% accuracy in panda recognition and 100% accuracy in detection.
4. 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.

     

Mass Collaboration in Earthquake Risk Management

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.     

On the classification of Calligonum juochiangense and C. pumilum (Polygonaceae)

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.     

罗汉果组培苗的栽培研究

本文报道罗汉果组培苗的栽培研究结果,为罗汉果在生产上推广应用组培苗栽培,提供有效的技术措施。     

金桔组织培养中愈伤组织和芽形成的组织细胞学观察

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。     

Clotrimazole对菠菜叶绿体光合磷酸化和电子传递的抑制作用

10μmol/的clotrimazole不仅抑制光合磷酸化活力,而且抑制各种类型的电子传递,是一个典型的电子传递抑制剂。经过它对叶绿体放氧,荧光和毫秒延迟发光影响的比较研究表明:clotri—mazole在光合电子传递链上的作用部位在Q与PQ之间,即与DGMU的作用部位相同或相近。     

桑树叶肉原生质体培养再生植株

近年来,木本植物原生质作诱导再生植株的研究越来越受到国内外学者关注。但在林木树种中,迄今成功的种类仍然不多,在文     

泉种蝇属一新种(双翅目:花蝇科)

本文记述泉种蝇属Pegohylemyia一新种。新种模式标本采自位于黔北高原的宽阔水自然保护区,保存于作者所在单位。 诹访泉种蝇Pegohylemyia suwai新种 雄 体长7.0mm。眼具稀疏微毛。额约为头宽的1/19或触角第三节宽的2/3。间额前方橘红,向后渐黑;粉波银灰;间额交叉鬃发达,其前下方尚具一个小鬃。侧额狭,至