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.

     

The Thatcher illusion in humans and monkeys

Primates possess the remarkable ability to differentiate faces of group members and to extract relevant information about the individual directly from the face. Recognition of conspecific faces is achieved by means of holistic processing, i.e. the processing of the face as an unparsed, perceptual whole, rather than as the collection of independent features (part-based processing). The most striking example of holistic processing is the Thatcher illusion. Local changes in facial features are hardly noticeable when the whole face is inverted (rotated 180°), but strikingly grotesque when the face is upright. This effect can be explained by a lack of processing capabilities for locally rotated facial features when the face is turned upside down. Recently, a Thatcher illusion was described in the macaque monkey analogous to that known from human investigations. Using a habituation paradigm combined with eye tracking, we address the critical follow-up questions raised in the aforementioned study to show the Thatcher illusion as a function of the observer''s species (humans and macaques), the stimulus'' species (humans and macaques) and the level of perceptual expertise (novice, expert).     

反向虚拟筛选平台及应用

靶标确证是老药新用、药物毒副作用研究的关键。基于分子对接方法 Auto Dock Vina和内部构建的疾病靶标数据库,采用分布式架构,构建了反向虚拟筛选平台。应用该平台对药物吡斯的明进行靶标确证,最终成功找到其靶标乙酰胆碱酯酶,验证了平台的实用性和准确性。     

Freedom of religion,women's agency and banning the face veil: the role of feminist beliefs in shaping women's opinion

Several countries have imposed bans on the wearing of face veils, a controversial option considered in Bill 94 by the province of Quebec in 2010. This paper examines non-Muslim women's support for the acceptability of the niqab in public spaces. Analysing the 2010 Quebec Women's Political Participation Survey, we find that key feminist arguments – that wearing the niqab is a woman's free choice, a matter of freedom of religion and a visible symbol of women's oppression – are important drivers of opinion. Their role in shaping opinion, however, is complex and mirrors divisions among feminist groups in the province. Additional attitudinal drivers include generation, exposure to the practice and openness to immigration. Equally important, our findings suggest that being a member of a racial minority, feelings of cultural insecurity and religiosity are of little consequence for thinking on the issue.     

SNAIL- and SLUG-induced side population phenotype of HCT116 human colorectal cancer cells and its regulation by BET inhibitors

Epithelial-mesenchymal transition (EMT) is associated with cancer malignancies such as invasion, metastasis, and drug resistance. In this study, HCT116 human colorectal cancer cells were transduced with SLUG or SNAIL retroviruses, and EMT cells with mesenchymal morphology were established. The EMT cells showed a high invasive activity and resistance to several anticancer agents such as methotrexate, SN-38, and cisplatin. Furthermore, they contained about 1–10% side population (SP) cells that were not stained by Hoechst 33342. This SP phenotype was not stable; the isolated SP cells generated both SP and non-SP cells, suggesting a potential for differentiation. Gene expression analysis of SP cells suggested the alteration of genes that are involved in epigenetic changes. Therefore, we examined the effect of 74 epigenetic inhibitors, and found that two inhibitors, namely I-BET151 and bromosporine, targeting the bromodomain and extra-terminal motif (BET) proteins, decreased the ratio of SP cells to <50% compared with the control, without affecting the immediate efflux of Hoechst 33342 by transporters. In addition, compared with the parental cells, the EMT cells showed a higher sensitivity to I-BET151 and bromosporine. This study suggests that EMT development and SP phenotype can be independent events but both are regulated by BET inhibitors in SLUG- or SNAIL-transducted HCT116 cells.