Nanjing University

About: Nanjing University is a education organization based out in Nanjing, China. It is known for research contribution in the topics: Catalysis & Population. The organization has 85961 authors who have published 105504 publications receiving 2289036 citations. The organization is also known as: NJU & Nanking University.

Ultra-sparse metasurface for high reflection of low-frequency sound based on artificial Mie resonances

Abstract: Acoustic metamaterials offer great flexibility for manipulating sound waves and promise unprecedented functionality, ranging from transformation acoustics, super-resolution imaging to acoustic cloaking However, the design of acoustic metamaterials with exciting functionality remains challenging with traditional approaches using classic acoustic elements such as Helmholtz resonators and membranes Here we demonstrate an ultraslow-fluid-like particle with intense artificial Mie resonances for low-frequency airborne sound Eigenstate analysis and effective parameter retrieval show two individual negative bands in the single-size unit cell, one of which exhibits a negative bulk modulus supported by the monopolar Mie resonance, whereas the other exhibits a negative mass density induced by the dipolar Mie resonance The unique single-negative nature is used to develop an ultra-sparse subwavelength metasurface with high reflectance for low-frequency sound We demonstrate a 015λ-thick, 15%-filling ratio metasurface with an insertion loss over 934% The designed Mie resonators provide diverse routes to construct novel acoustic devices with versatile applications

Adaptive Fault-Tolerant Tracking Control of Near-Space Vehicle Using Takagi–Sugeno Fuzzy Models

Abstract: Based on the adaptive-control technique, this paper deals with the problem of fault-tolerant tracking control for near-space-vehicle (NSV) attitude dynamics. First, Takagi-Sugeno (T-S) fuzzy models are used to describe the NSV attitude dynamics; then, an actuator-fault model is developed. Next, an adaptive fault-tolerant tracking-control scheme is proposed based on the online estimation of actuator faults, in which a compensation control term is introduced in order to reduce the effect of actuator faults. Compared with some existing results of fault-tolerant control (FTC) in nonlinear systems, the technique presented in this paper is not dependent on fault detection and isolation (FDI) mechanism and is easy to implement in aerospace-engineering applications. Finally, simulation results are given to illustrate the effectiveness and potential of the proposed FTC scheme.

Functional DNA Regulated CRISPR-Cas12a Sensors for Point-of-Care Diagnostics of Non-Nucleic-Acid Targets.

Abstract: Beyond its extraordinary genome editing ability, the CRISPR-Cas systems have opened a new era of biosensing applications due to its high base resolution and isothermal signal amplification. However, the reported CRISPR-Cas sensors are largely only used for the detection of nucleic acids with limited application for non-nucleic-acid targets. To realize the full potential of the CRISPR-Cas sensors and broaden their applications for detection and quantitation of non-nucleic-acid targets, we herein report CRISPR-Cas12a sensors that are regulated by functional DNA (fDNA) molecules such as aptamers and DNAzymes that are selective for small organic molecule and metal ion detection. The sensors are based on the Cas12a-dependent reporter system consisting of Cas12a, CRISPR RNA (crRNA), and its single-stranded DNA substrate labeled with a fluorophore and quencher at each end (ssDNA-FQ), and fDNA molecules that can lock a DNA activator for Cas12a-crRNA, preventing the ssDNA cleavage function of Cas12a in the absence of the fDNA targets. The presence of fDNA targets can trigger the unlocking of the DNA activator, which can then activate the cleavage of ssDNA-FQ by Cas12a, resulting in an increase of the fluorescent signal detectable by commercially available portable fluorimeters. Using this method, ATP and Na+ have been detected quantitatively under ambient temperature (25 °C) using a simple and fast detection workflow (two steps and <15 min), making the fDNA-regulated CRISPR system suitable for field tests or point-of-care diagnostics. Since fDNAs can be obtained to recognize a wide range of targets, the methods demonstrated here can expand this powerful CRISPR-Cas sensor system significantly to many other targets and thus provide a new toolbox to significantly expand the CRISPR-Cas system into many areas of bioanalytical and biomedical applications.

Multilabel dimensionality reduction via dependence maximization

Abstract: Multilabel learning deals with data associated with multiple labels simultaneously. Like other data mining and machine learning tasks, multilabel learning also suffers from the curse of dimensionality. Dimensionality reduction has been studied for many years, however, multilabel dimensionality reduction remains almost untouched. In this article, we propose a multilabel dimensionality reduction method, MDDM, with two kinds of projection strategies, attempting to project the original data into a lower-dimensional feature space maximizing the dependence between the original feature description and the associated class labels. Based on the Hilbert-Schmidt Independence Criterion, we derive a eigen-decomposition problem which enables the dimensionality reduction process to be efficient. Experiments validate the performance of MDDM.