Skin depth and detection ability of magneto-optical imaging for weld defects in alternating magnetic field

To detect and evaluate weld defects, the skin depth and detection ability of magneto-optical imaging (MOI) for weld defects in alternating magnetic field were studied, and the application scope of MOI in alternating magnetic field was determined. A model of magnetic flux leakage testing (MFL) for weld defects is established by finite element method, and the reliability of the model is determined by law analysis and MOI experimental verification. Comparing MFL and eddy current detection with simulation method, the skin effect mechanism and rules of MOI for weld defects in alternating magnetic field are analyzed and obtained. Considering the effect of skin effect, different MFL detection models are established, and the detection ability of MOI for weld defects with different frequencies under corresponding models is studied and obtained. Finally, the MOI experiment is used to verify the results, which are consistent with the simulations. The skin effect rule and detection ability of MOI for weld defects obtained by simulation method can be used as the theoretical basis for practical experiments.     

融合前沿研究的液体电介质击穿教学研究

针对《高电压与绝缘技术》课程中液体电介质的教学难点，提出了融合前沿研究的液体电介质击穿教学方法。基于前沿的液体放电应用背景与先进的液体放电研究平台，形象地展示液体电介质的动态击穿过程，在教学内容、教学方法、考核方式等方面进行科教融合改进，实施“以学生为中心”理念的课程教学设计。该教学方式取得了较好的教学效果，能够为其它知识点的教学质量提升提供参考。     

High-roubustness keystroke recognition method based on acoustic spatial gradient

For the fluctuation of CFCC caused by environmental noise is the main reason for the low accuracy of keystroke detection,the spatial characteristics of adjacent between CFCC were studied,and the spatial gradient structure of CFCC based on points was established.On this basis,the effect of CFCC spatial gradient on keystroke content recognition and the selection of precise neighborhood points were studied on training and testing.Finally,a high-robustness keystroke recognition algorithm based on acoustic signals was constructed.Extensive experiments in different environments demonstrate that the proposed CFCC spatial gradient sound feature achieves great performance and the recognition accuracy is 96.15%.     

Fluoro-Photoacoustic Polymeric Renal Reporter for Real-Time Dual Imaging of Acute Kidney Injury

Photoacoustic (PA) imaging agents detect disease tissues and biomarkers with increased penetration depth and enhanced spatial resolution relative to traditional optical imaging, and thus hold great promise for clinical applications. However, existing PA imaging agents often encounter the issues of slow body excretion and low-signal specificity, which compromise their capability for in vivo detection. Herein, a fluoro-photoacoustic polymeric renal reporter (FPRR) is synthesized for real-time imaging of drug-induced acute kidney injury (AKI). FPRR simultaneously turns on both near-infrared fluorescence (NIRF) and PA signals in response to an AKI biomarker (γ-glutamyl transferase) with high sensitivity and specificity. In association with its high renal clearance efficiency (78% at 24 h post-injection), FPRR can detect cisplatin-induced AKI at 24 h post-drug treatment through both real-time imaging and optical urinalysis, which is 48 h earlier than serum biomarker elevation and histological changes. More importantly, the deep-tissue penetration capability of PA imaging results in a signal-to-background ratio that is 2.3-fold higher than NIRF imaging. Thus, the study not only demonstrates the first activatable PA probe for real-time sensitive imaging of kidney function at molecular level, but also highlights the polymeric probe structure with high renal clearance.     

Performance of near-infrared dyes as effective contrast agents for breast cancer detection through simulation of photoacoustic imaging

ABSTRACT

Targeted photoacoustic imaging using exogenous contrast agents can potentially improve early detection of breast cancer, even at significant depths inside the breast. In this study, computer simulations were performed to compare the photoacoustic performance of 11 different near-infrared (NIR) dyes for detecting tumours deep inside the breast tissue. It was observed that the three high performing NIR dyes produced at least two-fold contrast enhancement of a spherical breast tumour embedded at 4?cm depth inside the breast than those of the corresponding endogenous contrast agents. These three selected dyes were employed to visualize small blood vessels deep inside the breast tissue. Although methylene blue provided the best contrast in visualizing tumour blood vessels at depths beyond 3?cm, considering other factors such as availability of suitable targeting agent, indocyanine green at 800?nm may be preferred over all other dyes for deep breast imaging applications.     

A greedy reduced basis scheme for multifrequency solution of structural acoustic systems

The solution of frequency dependent linear systems arising from the discretization of vibro-acoustic problems requires a significant computational effort in the case of rapidly varying responses. In this paper, we review the use of a greedy reduced basis scheme for the efficient solution in a frequency range. The reduced basis is spanned by responses of the system at certain frequencies that are chosen iteratively based on the response that is currently worst approximated in each step. The approximations at intermediate frequencies as well as the a posteriori estimations of associated errors are computed using a least squares solver. The proposed scheme is applied to the solution of an interior acoustic problem with boundary element method (BEM) and to the solution of coupled structural acoustic problems with finite element method and BEM. The computational times are compared to those of a conventional frequencywise strategy. The results illustrate the efficiency of the method.     

Flexible Piezoelectric Acoustic Sensors and Machine Learning for Speech Processing

Flexible piezoelectric acoustic sensors have been developed to generate multiple sound signals with high sensitivity, shifting the paradigm of future voice technologies. Speech recognition based on advanced acoustic sensors and optimized machine learning software will play an innovative interface for artificial intelligence (AI) services. Collaboration and novel approaches between both smart sensors and speech algorithms should be attempted to realize a hyperconnected society, which can offer personalized services such as biometric authentication, AI secretaries, and home appliances. Here, representative developments in speech recognition are reviewed in terms of flexible piezoelectric materials, self-powered sensors, machine learning algorithms, and speaker recognition.     

基于声波测试的煤矿深井巷道围岩松动圈影响因素分析

声波测试是当前测试煤矿深井巷道围岩松动圈范围的一种比较准确的方式。随着深井巷道的推进,巷道附近一定范围内的围岩由于前期爆破和后期围岩内部应力调整,会产生较多的裂隙和形变。而围岩的岩性、裂隙发育程度、应力分布情况都会显著影响声波在围岩中的传播速度。通过监测迎头推进过程中的围岩波速变化情况,分析了迎头推进距离、岩性、巷道位置等对围岩松动圈的影响。     

A Survey of Underwater Multi-Robot Systems

As a cross-cutting field between ocean development and multi-robot system (MRS), the underwater multi-robot system (UMRS) has gained increasing attention from researchers and engineers in recent decades. In this paper, we present a comprehensive survey of cooperation issues, one of the key components of UMRS, from the perspective of the emergence of new functions. More specifically, we categorize the cooperation in terms of task-space, motion-space, measurement-space, as well as their combination. Further, we analyze the architecture of UMRS from three aspects, i.e., the performance of the individual underwater robot, the new functions of underwater robots, and the technical approaches of MRS. To conclude, we have discussed related promising directions for future research. This survey provides valuable insight into the reasonable utilization of UMRS to attain diverse underwater tasks in complex ocean application scenarios.      

ADVANCES IN HIGH-RESOLUTION MALDI MASS SPECTROMETRY FOR NEUROBIOLOGY

Research in the field of neurobiology and neurochemistry has seen a rapid expansion in the last several years due to advances in technologies and instrumentation, facilitating the detection of biomolecules critical to the complex signaling of neurons. Part of this growth has been due to the development and implementation of high-resolution Fourier transform (FT) mass spectrometry (MS), as is offered by FT ion cyclotron resonance (FTICR) and Orbitrap mass analyzers, which improves the accuracy of measurements and helps resolve the complex biological mixtures often analyzed in the nervous system. The coupling of matrix-assisted laser desorption/ionization (MALDI) with high-resolution MS has drastically expanded the information that can be obtained with these complex samples. This review discusses notable technical developments in MALDI-FTICR and MALDI-Orbitrap platforms and their applications toward molecules in the nervous system, including sequence elucidation and profiling with de novo sequencing, analysis of post-translational modifications, in situ analysis, key advances in sample preparation and handling, quantitation, and imaging. Notable novel applications are also discussed to highlight key developments critical to advancing our understanding of neurobiology and providing insight into the exciting future of this field. © 2020 John Wiley & Sons Ltd. Mass Spec Rev