Single-cell landscape of the ecosystem in early-relapse hepatocellular carcinoma

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Perspective Texture Synthesis Based on Improved Energy Optimization

Perspective texture synthesis has great significance in many fields like video editing, scene capturing etc., due to its ability to read and control global feature information. In this paper, we present a novel example-based, specifically energy optimization-based algorithm, to synthesize perspective textures. Energy optimization technique is a pixel-based approach, so it’s time-consuming. We improve it from two aspects with the purpose of achieving faster synthesis and high quality. Firstly, we change this pixel-based technique by replacing the pixel computation with a little patch. Secondly, we present a novel technique to accelerate searching nearest neighborhoods in energy optimization. Using k- means clustering technique to build a search tree to accelerate the search. Hence, we make use of principal component analysis (PCA) technique to reduce dimensions of input vectors. The high quality results prove that our approach is feasible. Besides, our proposed algorithm needs shorter time relative to other similar methods.     

Diversity of endophytic bacteria and fungi in seeds of Elymus nutans growing in four locations of Qinghai Tibet Plateau,China

Plant and Soil - Seeds are involved in the transmission of microorganisms from one plant generation to the next, acting as initial inoculum for the plant microbiome, therefore provide a key source...     

An antigenic HIV-1 peptide sequence engineered into the surface structure of transferrin does not elicit an antibody response.

One novel approach for the biological delivery of peptide drugs is to incorporate the sequence of the peptide into the structure of a natural transport protein such as human serum transferrin (HST). However, a potential drawback is that the HST may increase the immunoreactivity of the peptide, in the same way that carrier proteins can be used to generate highly immunogenic peptide hapten conjugates. In this study we have generated a recombinant HST carrier protein that contains a peptide substrate of HIV-1 protease (VSQNYPIVL). The protein retained native HST function, and the peptide was surface exposed since it was immunoreactive in native dot blots, and was cleaved by HIV-1 protease. Immunisation of rabbits with the recombinant protein elicited only a very poor anti-peptide immune response. In contrast, strong anti-peptide immune responses were raised against both the peptide alone, and a chemical conjugate of the peptide with HST. These data demonstrate that it is possible to attenuate the immune response normally directed against an immunogenic peptide sequence by engineering into a surface exposed loop of HST. These findings may have an important impact on the future design of peptide delivery systems.     

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.