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TTAGO-COUPLED-MULTIPLEX-DIGITAL-RPA-CRISPR/CAS12A FOR EGFR MUTATIONS DETECTION 26

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TTAGO-COUPLED-MULTIPLEX-DIGITAL-RPA-CRISPR/CAS12A FOR EGFR M...

26th International Conference on Miniaturized systems for Chemistry and Life Sciences, MicroTAS 2022

作者： Zhuang, Jianjian Xia, Liping Zou, Zheyu Yin, Juxin Mu, Ying Department of Clinical Pharmacology Key Laboratory of Clinical Cancer Pharmacology and Toxicology Research of Zhejiang Province Affiliated Hangzhou First People's Hospital Cancer Center Zhejiang University School of Medicine Hangzhou310006 China School of information and Electrical Engineering Zhejiang University City College Hangzhou China Research Centre for Analytical Instrumentation Institute of Cyber-Systems and Control State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou China

ISBN: (纸本)9781733419048

Herein, Ttago-Coupled-Multiplex-digital-RPA-CRISPR/Cas12a (TCMDC) was proposed for the enrichment and multiplex detection of EGFR mutations. TCMDC realizes the fast enrichment of mutant nucleic acid templates by using Ttago to cut the wild-type template efficiently. The RPA-dual-crRNA Cas12a without need of PAM sequence realizes the universal one-tube RPA-Cas12a detection. Moreover, a multiplex digital PCR chip was developed and TCMDC was used to achieve absolute quantitative detection of multiplex EGFR mutations. As a mutation detection method, TCMDC not only has extremely high sensitivity (0.001%) and specificity, but also is very fast (1h), simple and convenient, which has versatility in point-of-care cancer diagnosis and precision medicine. © 2022 MicroTAS 2022 - 26th International Conference on Miniaturized systems for Chemistry and Life Sciences. All rights reserved.

关键词： Diagnosis

Indirect Adaptive Robust Trajectory Tracking control of Hard Rock TBM with Load Variation of Tunneling Face

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Chinese Journal of Mechanical Engineering 2019年第2期32卷 168-179页

作者： Chengjun Shao Jianfeng Liao Zhitao Liu Hongye Su State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University State Key Laboratory of Fluid Power Transmission and Control Zhejiang University

Posture adjustment of open-type hard rock tunnel boring machine(TBM) can be achieved by properly adjusting the hydraulic pressure of gripper cylinder and torque cylinders. However, the time-varying inhomogeneous load acting on tunneling face of TBM and complex stratum working condition can cause the trajectory deviation. In this paper,the position and posture rectification kinematics and dynamics models of TBM have been established in order to track the trajectory. Moreover, there are uncertain parameters and uncertain loads from complex working conditions in the dynamic model. An indirect adaptive robust control strategy is applied to achieve precise position and posture trajectory tracking control. Simulation results show when the position deviation only occurs in Y-axis and the current orientation is parallel with the designed axis, the deviation can be corrected by controlling the pressure of gripper cylinder and the actual trajectory meets the designed axis when TBM is pushed forward 0.14 m in X-axis. If the deviation only occurs in Z-axis, then the deviation can be corrected by controlling torque cylinders. If the position deviation occurs both in Y-axis and Z-axis at the same time, the pressure of gripper cylinder and torque cylinders should be controlled at the same time to rectify the deviation. Simulation results are shown to illustrate the e ectiveness and robustness of the proposed controller. This research proposes an indirect adaptive robust controller that can track the planned tracking trajectory smoothly and rapidly.

关键词： Open type hard rock TBM Inhomogeneous load Position and posture rectification Indirect adaptive robust control

Attitude Estimation from Vector Measurements: Necessary and Sufficient Conditions and Convergent Observer Design

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arXiv 2022年

作者： Yi, Bowen Wang, Lei Manchester, Ian R. The Australian Centre for Field Robotics Sydney Institute for Robotics and Intelligent Systems The University of Sydney SydneyNSW2006 Australia State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou310027 China

The paper addresses the problem of attitude estimation for rigid bodies using (possibly time-varying) vector measurements, for which we provide a necessary and sufficient condition of distinguishability. Such a condition is shown to be strictly weaker than those previously used for attitude observer design. Thereafter, we show that even for the single vector case the resulting condition is sufficient to design almost globally convergent attitude observers, and two explicit designs are obtained. To overcome the weak excitation issue, the first design employs to make full use of historical information, whereas the second scheme dynamically generates a virtual reference vector, which remains non-collinear to the given vector measurement. Simulation results illustrate the accurate estimation despite noisy measurements. © 2022, CC BY.

关键词： Vectors

DIDO: Deep Inertial Quadrotor Dynamical Odometry

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arXiv 2022年

作者： Zhang, Kunyi Jiang, Chenxing Li, Jinghang Yang, Sheng Ma, Teng Xu, Chao Gao, Fei State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou310027 China Huzhou Institute Zhejiang University Huzhou313000 China Alibaba DAMO Academy Autonomous Driving Lab Hangzhou311121 China

—In this work, we propose an interoceptive-only state estimation system for a quadrotor with deep neural network processing, where the quadrotor dynamics is considered as a perceptive supplement of the inertial kinematics. To improve the precision of multi-sensor fusion, we train cascaded networks on real-world quadrotor flight data to learn IMU kinematic properties, quadrotor dynamic characteristics, and motion states of the quadrotor along with their uncertainty information, respectively. This encoded information empowers us to address the issues of IMU bias stability, quadrotor dynamics, and multi-sensor calibration during sensor fusion. The above multisource information is fused into a two-stage Extended Kalman Filter (EKF) framework for better estimation. Experiments have demonstrated the advantages of our proposed work over several conventional and learning-based methods. © 2022, CC BY.

关键词： Extended Kalman filters

Matrix Completion over Finite Fields: Bounds and Belief Propagation Algorithms

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arXiv 2023年

作者： Soleymani, Mahdi Liu, Qiang Mahdavifar, Hessam Balzano, Laura Halıcıoglu Data Science Institute University of California San Diego United States The State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou310027 China The Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor United States

We consider the low rank matrix completion problem over finite fields. This problem has been extensively studied in the domain of real/complex numbers, however, to the best of authors' knowledge, there exists merely one efficient algorithm to tackle the problem in the binary field, due to Saunderson et al. [1]. In this paper, we improve upon the theoretical guarantees for the algorithm provided in [1]. Furthermore, we formulate a new graphical model for the matrix completion problem over the finite field of size q, Fq, and present a message passing (MP) based approach to solve this problem. The proposed algorithm is the first one for the considered matrix completion problem over finite fields of arbitrary size. Our proposed method has a significantly lower computational complexity, reducing it from O(n2r+3) in [1] down to O(n2) (where, the underlying matrix has dimension n × n and r denotes its rank), while also improving the performance. Copyright © 2023, The Authors. All rights reserved.

关键词： Message passing

CoNi-MPC: Cooperative Non-inertial Frame Based Model Predictive control

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arXiv 2023年

作者： Zhang, Baozhe Chen, Xinwei Li, Zhehan Beltrame, Giovanni Xu, Chao Gao, Fei Cao, Yanjun Huzhou Institute of Zhejiang University Huzhou313000 China State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou310027 China The Chinese University of Hong Kong Shenzhen518172 China Department of Computer Engineering and Software Engineering Poly-technique Montreal Canada

This paper presents a novel solution for UAV control in cooperative multi-robot systems, which can be used in various scenarios such as leader-following, landing on a moving base, or specific relative motion with a target. Unlike classical methods that tackle UAV control in the world frame, we directly control the UAV in the target coordinate frame, without making motion assumptions about the target. In detail, we formulate a nonlinear model predictive controller of a UAV, referred to as the agent, within a non-inertial frame (i.e., the target frame). The system requires the relative states (pose and velocity), the angular velocity and the accelerations of the target, which can be obtained by relative localization methods and ubiquitous MEMS IMU sensors, respectively. This framework eliminates dependencies that are vital in classical solutions, such as accurate state estimation for both the agent and target, prior knowledge of the target motion model, and continuous trajectory re-planning for some complex tasks. We have performed extensive simulations to investigate the control performance with varying motion characteristics of the target. Furthermore, we conducted real robot experiments, employing either simulated relative pose estimation from motion capture systems indoors or directly from our previous relative pose estimation devices outdoors, to validate the applicability and feasibility of the proposed approach. © 2023, CC BY.

关键词： Unmanned aerial vehicles (UAV)

PEBO-SLAM: Observer Design for Visual Inertial SLAM with Convergence Guarantees

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arXiv 2023年

作者： Yi, Bowen Jin, Chi Wang, Lei Shi, Guodong Ila, Viorela Manchester, Ian R. The Australian Centre for Robotics School of Aerospace Mechanical and Mechatronic Engineering The University of Sydney SydneyNSW2006 Australia The TuSimple Inc. Liangmaqiao Road Beijing China State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou310027 China

This paper introduces a new linear parameterization to the problem of visual inertial simultaneous localization and mapping (VI-SLAM)—without any approximation—for the case only using information from a single monocular camera and an inertial measurement unit. In this problem set, the system state evolves on the nonlinear manifold SE(3)×3n, on which we design dynamic extensions carefully to generate invariant foliations, such that the problem can be reformulated into online constant parameter identification, then interestingly with linear regression models obtained. It demonstrates that VI-SLAM can be translated into a linear least squares problem, in the deterministic sense, globally and exactly. Based on this observation, we propose a novel SLAM observer, following the recently established parameter estimation-based observer (PEBO) methodology. A notable merit is that the proposed observer enjoys almost global asymptotic stability, requiring neither persistency of excitation nor uniform complete observability, which, however, are widely adopted in most existing works with provable stability but can hardly be assured in many practical scenarios. © 2023, CC BY.

关键词： Parameter estimation

Improved Backward Scenario Reduction Method for Generation Planning Considering Extreme Scenarios 7

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Improved Backward Scenario Reduction Method for Generation P...

7th IEEE Conference on Energy Internet and Energy System Integration, EI2 2023

作者： Xie, Yigong Huo, Ziyu Wu, Chen Yao, Wenfeng Wang, Jiayang Qiao, Ying Power Dispatch Control Center Yunnan Power Grid Guangzhou China Tsinghua University State Key Lab of Power Systems Dept. of Electrical Engineering Beijing China Planning and Construction Research Center Yunnan Power Grid Kunming China China Southern Power Grid Research Institute State Key Laboratory of Current Transmission Technology Guangzhou China

ISBN: (纸本)9798350345094

Renewable energy sources exhibit significant variability and uncertainty, showing numerous distinct scenarios. In the context of generation planning, it's imperative to employ scenario reduction techniques to select representative scenarios that capture the characteristics of renewable energy outputs. However, traditional scenario reduction methods often fail to adequately preserve the extreme output scenarios of these renewables. This paper improves the simultaneous backward reduction method (SBR), enhancing its capability to effectively capture the extreme output scenarios of renewable sources. As a result, the generation planning becomes more economically viable and more reliable. The efficacy of the improved SBR method is demonstrated using data from the Qinhuangdao region in China. © 2023 IEEE.

关键词： Renewable energy

Neural motion prediction for in-flight uneven object catching

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arXiv 2021年

作者： Yu, Hongxiang Guo, Dashun Yin, Huan Chen, Anzhe Xu, Kechun Wang, Yue Xiong, Rong State Key Laboratory of Industrial Control and Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou310058 China

In-flight objects capture is extremely challenging. The robot is required to complete trajectory prediction, interception position calculation and motion planning in sequence within tens of milliseconds. As in-flight uneven objects are affected by various kinds of forces, motion prediction is difficult for a time-varying acceleration. In order to compensate the system’s non-linearity, we introduce the Neural Acceleration Estimator (NAE) that estimates the varying acceleration by observing a small fragment of previous deflected trajectory. Moreover, end-to-end training with Differantiable Filter (NAE-DF) gives a supervision for measurement uncertainty and further improves the prediction accuracy. Experimental results show that motion prediction with NAE and NAE-DF is superior to other methods and has a good generalization performance on unseen objects. We test our methods on a robot, performing velocity control in real world and respectively achieve 83.3% and 86.7% success rate on a ploy urethane banana and a gourd. We also release an object in-flight dataset containing 1,500 trajectorys for uneven objects. © 2021, CC BY.

关键词： Motion estimation