In this work, we propose a new solution for 3D human pose estimation in videos. Instead of directly regressing the 3D joint locations, we draw inspiration from the human skeleton anatomy and decompose the task into bone direction prediction and bone length prediction, from which the 3D joint locations can be completely derived. Our motivation is the fact that the bone lengths of a human skeleton remain consistent across time. This promotes us to develop effective techniques to utilize global information across all the frames in a video for high-accuracy bone length prediction. Moreover, for the bone direction prediction network, we propose a fully-convolutional propagating architecture with long skip connections. Essentially, it predicts the directions of different bones hierarchically without using any time-consuming memory units (e.g. LSTM). A novel joint shift loss is further introduced to bridge the training of the bone length and bone direction prediction networks. Finally, we employ an implicit attention mechanism to feed the 2D keypoint visibility scores into the model as extra guidance, which significantly mitigates the depth ambiguity in many challenging poses. Our full model outperforms the previous best results on Human3.6M and MPI-INF-3DHP datasets, where comprehensive evaluation validates the effectiveness of our model. Code is available at https://github.com/sunnychencool/Anatomy3D.

A new approach is developed for the rapid and cost-effective detection of human genetic polymorphisms based on matrix-assisted laser description/ionization mass spectrometric (MALDI MS) detection using a nitrocellulose film substrate. This method employs polymerase chain reaction (PCR) amplification using DNA extracted from buccal cells as templates, followed by direct digestion with restriction enzymes and subsequent analysis by MALDI MS. The extraction of DNA from buccal cells provides a rapid and convenient means for sampling PCR-based diagnostic analysis. The amount of DNA was sufficient as the template for both normal PCR amplifications, and amplifications involving the use of mismatched primers and multiple primers. The MALDI MS methodology has been successfully used for the analysis of such PCR products where restriction fragments generated directly in PCR reactions have been used for detection of carbonic anhydrase and cystic fibrosis transmembrane conductance regulator as model genes. The detection of genetic polymorphisms following routine biological and clinical procedures with the MALDI MS method is demonstrated. The results from MALDI MS analysis are shown to be comparable to those obtained from gel electrophoresis but the MALDI MS method is several orders of magnitude faster than gel electrophoretic techniques. The method described herein should also be readily extended to other areas involving DNA screening and testing.

Despite the great progress in human motion prediction, it remains a challenging task due to the complicated structural dynamics of human behaviors. In this paper, we address this problem in three aspects. First, to capture the long-range spatial correlations and temporal dependencies, we apply a transformer-based architecture with the global attention mechanism. Specifically, we feed the network with the sequential joints encoded with the temporal information for spatial and temporal explorations. Second, to further exploit the inherent kinematic chains for better 3D structures, we apply a progressive-decoding strategy, which performs in a central-to-peripheral extension according to the structural connectivity. Last, in order to incorporate a general motion space for high-quality prediction, we build a memory-based dictionary, which aims to preserve the global motion patterns in training data to guide the predictions. We evaluate the proposed method on two challenging benchmark datasets (Human3.6M and CMU-Mocap). Experimental results show our superior performance compared with the state-of-the-art approaches.

Blue phosphorene (blue-P), an allotrope of black phosphorene, is prone to oxidize under ambient conditions, which significantly hinders its incorporation in anode for Li/Na ion batteries (LIBs/NIBs). Combining blue-P and hexagonal boron nitride (h-BN) together to construct h-BN/blue-P heterostructure (BN/P) can break the limitation of the restricted properties of blue-P. By means of first-principles computations, we explored the potential of using BN/P as anode material for LIBs/NIBs. Our computations show that the adsorption energies of Li/Na in BN/P are stronger than those in blue-P. Interestingly, although Li has similar chemical properties to Na, their the most energetically favorable sites on BN/P are different. Li prefers to insert into the interlayer of BN/P while Na prefers to absorb on the blue-P surface of BN/P. Furthermore, BN/P can achieve high theoretical specific capacities 801 and 541 mAh/g and low diffusion barriers 0.08 and 0.07 eV for LIBs and NIBs, respectively. All these characteristics suggest that the BN/P could be an ideal candidate used as promising anode material for high-performance LIBs/NIBs.

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