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SERS-encoded nanocomposites for dual pathogen bioassay

Journal of Materials Science & Technology 2020年第8期36卷 161-167页

作者： Yaqi Shan Mingliang Wang Zengliang Shi Milan Lei Xiaoxuan Wang Fu-Gen Wu Huan-Huan Ran Gowri Manohari Arumugam Qiannan Cui Chunxiang Xu State Key Laboratory of Bioelectronics School of Chemistry and Chemical EngineeringSoutheast UniversityNanjing 211189China

Surface-enhanced Raman spectroscopy(SERS)has been successfully applied to detect various biomolecules,but it is still in challenge to assay living cells or bacteria sensitively,selectively and quantitatively in complex *** this paper,4-ATP and DTNB are assembled on Ag nanoparticle(NP)-decorated poly(styrene-co-acrylic acid)(PSA)nanospheres and then sealed by silica shells to form sensitive SERS labels based on the localized surface plasmon resonance of Ag NPs and large light scattering cross-sections of PSA *** are further developed as encoding tags for dual detection of *** and *** after assembling corresponding aptamers,which demonstrate ultralow detection limits of 8 cell L-1 for *** and 2 cell L-1 for *** a bioassay indicates a point-of-care strategy of ultrasensitively biomedical detections by encoding specific SERS tags.

关键词： SERS Pathogens Dual detection Encoded nanocomposites complex environments

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A resilient adjustment method to weigh pseudorange observation in precise point positioning

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Satellite Navigation 2022年第3期3卷 125-139,I0004页

作者： Qieqie Zhang Long Zhao Jianhua Zhou College of Automation Engineering Nanjing University of Aeronautics and AstronauticsNanjing211106China Digital Navigation Center School of Automation Science and Electrical EngineeringBeihang UniversityBeijing100191China Beijing Satellite Navigation Center Beijing100094China

The accurate weighting of pseudorange observations is important to improve the convergence time and positioning quality of Precise Point Positioning(PPP).Currently,the weight of a pseudorange observation is mainly determined with empirical stochastic ***,in a complex environment,due to the inability to adapt for the dynamic changes of the user environment,the empirical stochastic models usually cannot reflect the real error level of pseudorange *** address this problem,a resilient adjustment method to weigh pseudorange observations is proposed,which constructs the real-time estimation and inflation model for the variance of pseudorange multipath error and measurement noise to replace the empirical stochastic model to determine the weights of pseudorange observations.A set of static and dynamic Global Positioning System(GPS)test data are used to verify the effectiveness of the proposed *** test results indicate that the proposed real-time estimation model can provide a better representation of the pseudorange accuracy,and the positioning performance of PPP using the real-time estimation model is better than that with the empirical stochastic *** with the optimal empirical stochastic model,the positioning accuracy of PPP with the real-time estimation model is improved by at least 20%,and the convergence time is reduced by at least 50%.

关键词： Precise point positioning Stochastic model Resilient adjustment complex environments

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Method for the fruit tree recognition and navigation in complex environment of an agricultural robot

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International Journal of Agricultural and Biological Engineering 2024年第2期17卷 221-229页

作者： Xiaolin Xie Yuchao Li Lijun Zhao Xin Jin Shengsheng Wang Xiaobing Han College of Agricultural Equipment Engineering Henan University of Science and TechnologyLuoyang 471003HenanChina Collaborative Innovation Center of Machinery Equipment Advanced Manufacturing of Henan Province Luoyang 471003HenanChina Longmen Laboratory Luoyang 471003HenanChina College of Intelligent and Manufacturing Engineering Chongqing University of Arts and SciencesChongqing 402160China

To realize the visual navigation of agricultural robots in the complex environment of orchards,this study proposed a method for fruit tree recognition and navigation based on *** YOLOv5s model was selected and trained to identify the trunks of the left and right rows of fruit trees;the quadratic curve was fitted to the bottom center of the fruit tree recognition box,and the identified fruit trees were divided into left and right columns by using the extreme value point of the quadratic curve to obtain the left and right rows of fruit trees;the straight-line equation of the left and right fruit tree rows was further solved,the median line of the two straight lines was taken as the expected navigation path of the robot,and the path tracing navigation experiment was carried out by using the improved LQR control *** experimental results show that under the guidance of the machine vision system and guided by the improved LQR control algorithm,the lateral error and heading error can converge quickly to the desired navigation path in the four initial states of[0 m,−0.34 rad],[0.10 m,0.34 rad],[0.15 m,0 rad]and[0.20 m,−0.34 rad].When the initial speed was 0.5 m/s,the average lateral error was 0.059 m and the average heading error was 0.2787 rad for the navigation trials in the four different initial *** average driving was 5.3 m into the steady state,the average value of steady state lateral error was 0.0102 m,the average value of steady state heading error was 0.0253 rad,and the average relative error of the robot driving along the desired navigation path was 4.6%.The results indicate that the navigation algorithm proposed in this study has good robustness,meets the operational requirements of robot autonomous navigation in orchard environment,and improves the reliability of robot driving in orchard.

关键词： fruit tree recognition visual navigation YOLOv5 complex environments orchards

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The Moderating Effect of Team Orientation Over the Relationship Between TMT Strategic Decision Speed and Firm Performance

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Chinese Business Review 2011年第9期10卷 790-795页

作者： Claudia Ramos-Garza Olivia Villalba-Moreno Leticia Ramos-Garza EGADE Business School Monterrey Tecnologico de Monterrey Mexico School of Business Social Science and Humanities Tecnologico de Monterrey Mexico

Due to the fast changing competitive environment faced by organizations, companies are forced to find ways to quickly adapt to technological innovations, changing demands of customers, and strategic actions taken by competitors. The purpose of the paper is to further the relationship between top management team （TMT） strategic decision speed and firm performance, considering the team processes when making strategic decisions in the face of complex environments. Measures of TMT strategic decision speed, firm performance, team orientation, and environmental complexity were collected from 29 top management teams of Mexican companies, which represented a total of 118 questionnaires. Pearson correlations among the variables and moderated regression analyses were performed, to test the hypotheses included in the study. Results show a positive relation between environmental complexity and TMT strategic decision speed and between team orientation and speed. Furthermore, results show that there is a positive relation between TMT strategic decision speed and firm performance in the presence of team orientation. In other words, team orientation moderates the relationship between TMT strategic speed and firm performance. Among the implications for managers is that they must ensure effective team processes （e.g., building consensus, active participation, and trust among team members） when making strategic decisions in order for the firm to perform better.

关键词： strategic decision speed team orientation TMT firm performance complex environments

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State Estimation Method for GNSS/INS/Visual Multi-sensor Fusion Based on Factor Graph Optimization for Unmanned System

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Transactions of Nanjing University of Aeronautics and Astronautics 2024年第S1期41卷 43-51页

作者： ZHU Zekun YANG Zhong XUE Bayang ZHANG Chi YANG Xin College of Automation Engineering Nanjing University of Aeronautics and AstronauticsNanjing 211106P.R.China

With the development of unmanned driving technology,intelligent robots and drones,high-precision localization,navigation and state estimation technologies have also made great *** global navigation satellite system/inertial navigation system(GNSS/INS)integrated navigation systems can provide high-precision navigation information ***,when this system is applied to indoor or GNSS-denied environments,such as outdoor substations with strong electromagnetic interference and complex dense spaces,it is often unable to obtain high-precision GNSS positioning *** positioning and orientation errors will diverge and accumulate rapidly,which cannot meet the high-precision localization requirements in large-scale and long-distance navigation *** paper proposes a method of high-precision state estimation with fusion of GNSS/INS/Vision using a nonlinear optimizer factor graph optimization as the basis for multi-source *** the collected experimental data and simulation results,this system shows good performance in the indoor environment and the environment with partial GNSS signal loss.

关键词： state estimation multi-sensor fusion combined navigation factor graph optimization complex environments

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