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.

     

Reconstitution of the fusogenic activity of vesicular stomatitis virus.

Enveloped virus glycoproteins exhibit membrane fusion activity. We have analysed whether the G protein of vesicular stomatitis virus, reconstituted into liposomes, is able to fuse nucleated cells in a pH-dependent fashion. Proteoliposomes produced by octylglucoside dialysis did not exhibit cell fusion activity of the G protein. However, by making use of n-dodecyl octaethylene monoether (C12E8) as the solubilizing agent and by removal of the detergent in two steps, we were able to produce fusogenic G protein liposomes. These G protein liposomes fuse to the BHK-21 cell surface at pH 5.7-6.0 with an efficiency of fusion comparable with that of the parent virus. Physical and chemical analysis revealed that the fusogenic liposomes exhibited a protein to lipid weight ratio of 0.67 and showed an average diameter of 130 nm.     

Putative candidate genes for blood pressure control in the SHR.BN-RNO8 congenic substrains

The SHR-Lx congenic strain carrying a differential segment of chromosome 8 of BN and PD origin was recently shown to exhibit a significant decrease in blood pressure as compared to the SHR strain. There were two positional candidate genes for blood pressure control mapped to the differential segment: the rat kidney epithelial potassium channel gene (Kcnj1) and brain dopamine receptor 2 gene (Drd2). Bot these genes were separated into SHR.BN-RNO8 congenic substrains. In this communication, we are presenting the assignment of two further putative candidate genes, which might be involved in blood pressure control to the BN/PD differential segment of the SHR-Lx congenic strain. These are: the gene coding for smooth muscle cell specific protein 22 (Sm22) defined by the D8Mcw1 marker and neuronal nicotinic acetylcholine receptor gene cluster, defined by the D8Bord1 marker. Moreover, the glutamate receptor gene Grik4 which also maps to the differential segment of the SHR-Lx should be taken into account. The genetic separation of all these putative candidate genes of blood pressure control is being performed by recombinations and subsequent selection using (SHR×SHR-Lx) intercross population.     

A new approach to polarized fluorescence using phase and modulation fluorometry

In the preceding paper, an alternative method is described for obtaining information about the reorientational behavior of a fluorophore in a membrane system from frequency domain measurements. To demonstrate this new analysis procedure, we present data for the probe-molecule 1,6-diphenyl-1,3,5-hexatriene (DPH) in l--dimyristoyl- and l--dipalmitoylphosphatidylcholine (DMPC and DPPC) obtained with two different phase fluorometers: the SLM 4800A Subnanosecond Spectrofluorometer which has only three fixed frequencies available (6, 18 and 30 MHz) and the recently constructed continuously variable multifrequency phasefluorometer (Gratton and Limkeman 1983).It will be shown that reasonable information about the anisotropy behavior of a fluorophore can be obtained even if only three frequencies are used. The phase modulation technique was also used to check the new expression for the anisotropy, r(t), called the general model and introduced by Van der Meer et al. (1984). The parameters P ₂, P ₄ and D, obtained from the nonlinear least squares fit (Bevington 1969) for this general model, confirm the results from the pulse technique of Ameloot and coworkers (Ameloot et al. 1984; Pottel et al. 1986).