142 research outputs found

    Personnel recognition and gait classification based on multistatic micro-doppler signatures using deep convolutional neural networks

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    In this letter, we propose two methods for personnel recognition and gait classification using deep convolutional neural networks (DCNNs) based on multistatic radar micro-Doppler signatures. Previous DCNN-based schemes have mainly focused on monostatic scenarios, whereas directional diversity offered by multistatic radar is exploited in this letter to improve classification accuracy. We first propose the voted monostatic DCNN (VMo-DCNN) method, which trains DCNNs on each receiver node separately and fuses the results by binary voting. By merging the fusion step into the network architecture, we further propose the multistatic DCNN (Mul-DCNN) method, which performs slightly better than VMo-DCNN. These methods are validated on real data measured with a 2.4-GHz multistatic radar system. Experimental results show that the Mul-DCNN achieves over 99% accuracy in armed/unarmed gait classification using only 20% training data and similar performance in two-class personnel recognition using 50% training data, which are higher than the accuracy obtained by performing DCNN on a single radar node

    Dynamic Hand Gesture Classification Based on Multistatic Radar Micro-Doppler Signatures Using Convolutional Neural Network

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    We propose a novel convolutional neural network (CNN) for dynamic hand gesture classification based on multistatic radar micro-Doppler signatures. The timefrequency spectrograms of micro-Doppler signatures at all the receiver antennas are adopted as the input to CNN, where data fusion of different receivers is carried out at an adjustable position. The optimal fusion position that achieves the highest classification accuracy is determined by a series of experiments. Experimental results on measured data show that 1) the accuracy of classification using multistatic radar is significantly higher than monostatic radar, and that 2) fusion at the middle of CNN achieves the best classification accuracy

    Global Gene Expression Profiling in Whole-Blood Samples from Individuals Exposed to Metal Fumes

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    Accumulating evidence demonstrates that particulate air pollutants can cause both pulmonary and airway inflammation. However, few data show that particulates can induce systemic inflammatory responses. We conducted an exploratory study using microarray techniques to analyze whole-blood total RNA in boilermakers before and after occupational exposure to metal fumes. A self-controlled study design was used to overcome the problems of larger between-individual variation interferences with observations of relatively smaller changes caused by environmental exposure. Moreover, we incorporated the dichotomous data of absolute gene expression status in the microarray analyses. Compared with nonexposed controls, we observed that genes with altered expression in response to particulate exposure were clustered in biologic processes related to inflammatory response, oxidative stress, intracellular signal transduction, cell cycle, and programmed cell death. In particular, the preinflammatory cytokine interleukin 8 and one of its receptors, chemokine receptor 4, seemed to play important roles in early-stage response to heavy metal exposure and were down-regulated. Furthermore, most observed expression variations were from nonsmoking exposed individuals, suggesting that smoking profoundly affects whole-blood expression profiles. Our study is the first to demonstrate that with a paired sampling study design of pre- and postexposed individuals, small changes in gene expression profiling can be measured in whole-blood total RNA from a population-based study. This technique can be applied to evaluate the host response to other forms of environmental exposures

    Cloning and characterization of two subunits of calcineurin cDNA in naked carp (Gymnocypris przewalskii) from Lake Qinghai, China

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    The naked carp (Gymnocypris przewalskii), a native teleost, plays an important role in maintenance of the ecological balance in the system of Lake Qinghai (altitude, 3.2 km) on the Qinghai-Tibet Plateau in China. Calcineurin (CN) is the only member of the serine/threonine phosphatase family that can be activated by both Ca2+ and calmodulin (CaM) and involved in many important physiological processes such as salt tolerance/adaption. In this report, cDNAs of CN catalytic subunit paralogue isoforms: GpCAα (GenBank accession no.JQ407043), GpCAγ (GenBank accession no. JQ407043), and CN regulatory subunit (GpCB) (GenBank accession no. JQ410473), were isolated from Gymnocypris przewalskii and their expression patterns in embryos developmentwere characterized. Gene expression profile demonstrated that GpCA and GpCB mRNA was distributed ubiquitously in all embryonic stages and showed decline until final stage of development. Immunohistologicalanalysis revealed CN localization in different tissues including kidney, heart, brain, spermary, and gill. Collectively, these results provide molecular basis and clues to further understand the role of CN during embryos development and its function in tissues for the adaptation mechanism of naked carp
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