Adaptive Graphical Model Network for 2D Handpose Estimation

In this paper, we propose a new architecture called Adaptive Graphical Model Network (AGMN) to tackle the task of 2D hand pose estimation from a monocular RGB image. The AGMN consists of two branches of deep convolutional neural networks for calculating unary and pairwise potential functions, followed by a graphical model inference module for integrating unary and pairwise potentials. Unlike existing architectures proposed to combine DCNNs with graphical models, our AGMN is novel in that the parameters of its graphical model are conditioned on and fully adaptive to individual input images. Experiments show that our approach outperforms the state-of-the-art method used in 2D hand keypoints estimation by a notable margin on two public datasets.Comment: 30th British Machine Vision Conference (BMVC

Biotransformation of doxycycline by \u3ci\u3eBrevundimonas naejangsanensis\u3c/i\u3e and \u3ci\u3eSphingobacterium mizutaii\u3c/i\u3e strains

The fate of doxycycline (DC), a second generation tetracycline antibiotic, in the environment has drawn increasing attention in recent years due to its wide usage. Little is known about the biodegradability of DC in the environment. The objective of this study was to characterize the biotransformation of DC by pure bacterial strains with respect to reaction kinetics under different environmental conditions and biotransformation products. Two bacterial strains, Brevundimonas naejangsanensis DD1 and Sphingobacterium mizutaii DD2, were isolated from chicken litter and characterized for their biotransformation capability of DC. Results show both strains rely on cometabolism to biotransform DC with tryptone as primary growth substrate. DD2 had higher biotransformation kinetics than DD1. The two strains prefer similar pHs (7 and 8) and temperature (30 °C), however, they exhibited opposite responses to increasing background tryptone concentration. While hydrolysis converted DC to its isomer or epimer, the two bacterial strains converted DC to various biotransformation products through a series of demethylation, dehydration, decarbonylation and deamination. Findings from the study can be used to better predict the fate of DC in the environment

PPT: token-Pruned Pose Transformer for monocular and multi-view human pose estimation

Recently, the vision transformer and its variants have played an increasingly important role in both monocular and multi-view human pose estimation. Considering image patches as tokens, transformers can model the global dependencies within the entire image or across images from other views. However, global attention is computationally expensive. As a consequence, it is difficult to scale up these transformer-based methods to high-resolution features and many views. In this paper, we propose the token-Pruned Pose Transformer (PPT) for 2D human pose estimation, which can locate a rough human mask and performs self-attention only within selected tokens. Furthermore, we extend our PPT to multi-view human pose estimation. Built upon PPT, we propose a new cross-view fusion strategy, called human area fusion, which considers all human foreground pixels as corresponding candidates. Experimental results on COCO and MPII demonstrate that our PPT can match the accuracy of previous pose transformer methods while reducing the computation. Moreover, experiments on Human 3.6M and Ski-Pose demonstrate that our Multi-view PPT can efficiently fuse cues from multiple views and achieve new state-of-the-art results.Comment: ECCV 2022. Code is available at https://github.com/HowieMa/PP

BRCAA1 monoclonal antibody conjugated fluorescent magnetic nanoparticles for in vivo targeted magnetofluorescent imaging of gastric cancer

<p>Abstract</p> <p>Background</p> <p>Gastric cancer is 2th most common cancer in China, and is still the second most common cause of cancer-related death in the world. How to recognize early gastric cancer cells is still a great challenge for early diagnosis and therapy of patients with gastric cancer. This study is aimed to develop one kind of multifunctional nanoprobes for <it>in vivo </it>targeted magnetofluorescent imaging of gastric cancer.</p> <p>Methods</p> <p>BRCAA1 monoclonal antibody was prepared, was used as first antibody to stain 50 pairs of specimens of gastric cancer and control normal gastric mucous tissues, and conjugated with fluorescent magnetic nanoparticles with 50 nm in diameter, the resultant BRCAA1-conjugated fluorescent magnetic nanoprobes were characterized by transmission electron microscopy and photoluminescence spectrometry, as-prepared nanoprobes were incubated with gastric cancer MGC803 cells, and were injected into mice model loaded with gastric cancer of 5 mm in diameter via tail vein, and then were imaged by fluorescence optical imaging and magnetic resonance imaging, their biodistribution was investigated. The tissue slices were observed by fluorescent microscopy, and the important organs such as heart, lung, kidney, brain and liver were analyzed by hematoxylin and eosin (HE) stain method.</p> <p>Results</p> <p>BRCAA1 monoclonal antibody was successfully prepared, BRCAA1 protein exhibited over-expression in 64% gastric cancer tissues, no expression in control normal gastric mucous tissues, there exists statistical difference between two groups (<it>P </it>< 0.01). The BRCAA1-conjugated fluorescent magnetic nanoprobes exhibit very low-toxicity, lower magnetic intensity and lower fluorescent intensity with peak-blue-shift than pure FMNPs, could be endocytosed by gastric cancer MGC803 cells, could target <it>in vivo </it>gastric cancer tissues loaded by mice, and could be used to image gastric cancer tissues by fluorescent imaging and magnetic resonance imaging, and mainly distributed in local gastric cancer tissues within 12 h post-injection. HE stain analysis showed that no obvious damages were observed in important organs.</p> <p>Conclusions</p> <p>The high-performance BRCAA1 monoclonal antibody-conjugated fluorescent magnetic nanoparticles can target <it>in vivo </it>gastric cancer cells, can be used for simultaneous magnetofluorescent imaging, and may have great potential in applications such as dual-model imaging and local thermal therapy of early gastric cancer in near future.</p

A Marr's Three‐Level Analytical Framework for Neuromorphic Electronic Systems

Neuromorphic electronics, an emerging field that aims for building electronic mimics of the biological brain, holds promise for reshaping the frontiers of information technology and enabling a more intelligent and efficient computing paradigm. As their biological brain counterpart, the neuromorphic electronic systems are complex, having multiple levels of organization. Inspired by David Marr's famous three-level analytical framework developed for neuroscience, the advances in neuromorphic electronic systems are selectively surveyed and given significance to these research endeavors as appropriate from the computational level, algorithmic level, or implementation level. Under this framework, the problem of how to build a neuromorphic electronic system is defined in a tractable way. In conclusion, the development of neuromorphic electronic systems confronts a similar challenge to the one neuroscience confronts, that is, the limited constructability of the low-level knowledge (implementations and algorithms) to achieve high-level brain-like (human-level) computational functions. An opportunity arises from the communication among different levels and their codesign. Neuroscience lab-on-neuromorphic chip platforms offer additional opportunity for mutual benefit between the two disciplines

Copper Selenide Nanosnakes: Bovine Serum Albumin-Assisted Room Temperature Controllable Synthesis and Characterization

Herein we firstly reported a simple, environment-friendly, controllable synthetic method of CuSe nanosnakes at room temperature using copper salts and sodium selenosulfate as the reactants, and bovine serum albumin (BSA) as foaming agent. As the amounts of selenide ions (Se2−) released from Na2SeSO3 in the solution increased, the cubic and snake-like CuSe nanostructures were formed gradually, the cubic nanostructures were captured by the CuSe nanosnakes, the CuSe nanosnakes grew wider and longer as the reaction time increased. Finally, the cubic CuSe nanostructures were completely replaced by BSA–CuSe nanosnakes. The prepared BSA–CuSe nanosnakes exhibited enhanced biocompatibility than the CuSe nanocrystals, which highly suggest that as-prepared BSA–CuSe nanosnakes have great potentials in applications such as biomedical engineering