Search

Peroxynitrite (ONOO−) is an important reactive oxygen species, and excess ONOO− in the body can lead to a range of diseases. Addressing the need for sensitive detection ONOO−, in this work, a highly sensitivity and selectivity long-wavelength fluorescent probe (named CIS) was designed for tracking ONOO− in biological cells. Probe CIS featured carbazole as the fluorophore and the C C double bond with two electron withdrawing –CN groups as the recognition site. The probe CIS exhibited the typical aggregation-induced emission (AIE) and intramolecular charge transfer (ICT) characteristics with the bright red fluorescent emission in high water fraction (f w ≥ 50 %) and negligible emission in low water fraction. The fluorescence emission wavelength of probe CIS is 631 nm, with a large Stokes shift (151 nm), which can sensitively detect ONOO− in DMSO: H 2 O (7:3, v/v) environment. Notably, the probe CIS exhibited a wide pH detection range (pH = 3–10), a low detection limit of 36.66 nM, high selectivity and minimal interference. Furthermore, probe CIS demonstrated excellent biocompatibility and low cytotoxicity, and can be used for the detection of exogenous ONOO− in 4T1 cells (Mouse breast cancer cells). These research results indicate that probe CIS has potential application prospects in the biological aspects. [Display omitted] • A long-wavelength (λ em = 631 nm) fluorescent probe CIS with AIE characteristics and a large Stokes shift (151 nm) was designed and synthesized for the identification of ONOO−. • Probe CIS has a wide pH range (3−10), low detection limit (36.66 nM) and strong anti-interference for the identification of ONOO−. • Probe CIS has been successfully applied to the dual-channel detection of ONOO− in 4T1 cells. [ABSTRACT FROM AUTHOR]

A novel dual emissive fluorescent probe SFQ was designed and synthesized by linking dicyanisophorone and thiophene aldehyde units to carbazole groups. The probe SFQ has high selectivity and sensitivity toward ClO−. Upon addition of ClO− to the solution of probe SFQ resulted in a noticeable color changed from orange to pink under natural light. Meanwhile, SFQ could make a ratiometric fluorescence response to ClO− at two different excitation wavelengths, with the change of color from orange-red fluorescence to cyan fluorescence under the 365 nm UV lamp. The detection limit was 1.4 × 10−7 mol/L under ratiometric conditions. The study on the reaction mechanism showed that when SFQ reacted with ClO−, the cyano group disappeared and the cyclic ketone SFQ -O came into being. Furthermore, probe SFQ was successfully used to monitor ClO− in HepG2 cells and detect ClO− in actual environmental water samples. [Display omitted] • A novel probe SFQ for colorimetric and ratiometric identification of ClO− was prepared. • SFQ can respond instantly to ClO− (<5 s) and has a large Stokes shift (145 nm). • SFQ was successfully used to monitor ClO− in HepG2 cells and detect ClO− in actual environmental water samples. [ABSTRACT FROM AUTHOR]

Community mining for complex social networks with link and attribute information plays an important role according to different application needs. In this paper, based on our proposed general non-negative matrix factorization (GNMF) algorithm without dimension matching constraints in our previous work, we propose the joint GNMF with graph Laplacian (LJGNMF) to implement community mining of complex social networks with link and attribute information according to different application needs. Theoretical derivation result shows that the proposed LJGNMF is fully compatible with previous methods of integrating traditional NMF and symmetric NMF. In addition, experimental results show that the proposed LJGNMF can meet the needs of different community minings by adjusting its parameters, and the effect is better than traditional NMF in the community vertices attributes entropy. [ABSTRACT FROM AUTHOR]

Abstract: Proportional delay is a kind of unbounded time-varying delay, which is different from unbounded distributed delays. In this paper, asymptotic stability of the equilibrium point of cellular neural networks with multiple proportional delays is presented. Sufficient conditions for delay-dependent global asymptotic stability and delay-independent uniform asymptotic stability of the system are obtained by employing matrix theory and constructing Lyapunov functional. Two examples are given to illustrate the effectiveness of the obtained results and less conservative than previously existing results. [Copyright &y& Elsevier]

Abstract: This paper presents an improved impossible differential cryptanalysis of SAFER ciphers, which uses the miss-in-the-middle technique developed by Biham et al. We analyze 3.75-round SAFER SK-64, [1] (In this paper, the number in the name of the ciphers indicates the key length). 1 using chosen plaintexts, bytes memory and half round computations. Furthermore, the new impossible differential attack on 3.75-round SAFER+/128 uses chosen plaintexts, half round computations and bytes memory. And attack on 3.75-round SAFER++/128 uses data, time, and memory. [Copyright &y& Elsevier]

This paper investigates an important problem concerning the complexity of three-layer binary neural networks (BNNs) with one hidden layer. The neuron in the studied BNNs employs a hard limiter activation function with only integer weights and an integer threshold. The studies are focused on implementations of arbitrary Boolean functions which map from {0,1}n into {0,1}. A deterministic algorithm called set covering algorithm (SCA) is proposed for the construction of a three-layer BNN to implement an arbitrary Boolean function. The SCA is based on a unit sphere covering (USC) of the Hamming space (HS) which is chosen in advance. It is proved that for the implementation of an arbitrary Boolean function of n-variables (n≥3) by using SCA, ⌊3L/2⌋ hidden neurons are necessary and sufficient, where L is the number of unit spheres contained in the chosen USC of the n-dimensional HS. It is shown that by using SCA, the number of hidden neurons required is much less than that by using a two-parallel hyperplane method. In order to indicate the potential ability of three-layer BNNs, a lower bound on the required number of hidden neurons which is derived by using the method of estimating the Vapnik-Chervonenkis (VC) dimension is also given. [Copyright &y& Elsevier]

In this paper, we derive a new fixed-time stability theorem based on definite integral, variable substitution and some inequality techniques. The fixed-time stability criterion and the upper bound estimate formula for the settling time are different from those in the existing fixed-time stability theorems. Based on the new fixed-time stability theorem, the fixed-time synchronization of neural networks is investigated by designing feedback controller, and sufficient conditions are derived to guarantee the fixed-time synchronization of neural networks. To show the usability and superiority of the obtained theoretical results, we propose a secure communication scheme based on the fixed-time synchronization of neural networks. Numerical simulations illustrate that the new upper bound estimate formula for the settling time is much tighter than those in the existing fixed-time stability theorems. Moreover, the plaintext signals can be recovered according to the new fixed-time stability theorem, while the plaintext signals cannot be recovered according to the existing fixed-time stability theorems. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new fixed-time stability theorem. Numerical simulations show that our upper bound estimate for the settling time is much smaller than those in the existing fixed-time stability theorems. Based on the new fixed-time stability theorem, we investigate the fixed-time synchronization of memristive neural networks (MNNs) by adopting a delay-dependent feedback controller. Numerical simulations are provided to demonstrate the correctness of our theoretical results and the superiority of the new fixed-time stability theorem. [ABSTRACT FROM AUTHOR]

Abstract This paper is concerned with the fixed-time synchronization control of inertial memristor-based neural networks with discrete delay. We design four different kinds of feedback controllers, under which the considered inertial memristor-based neural networks can realize fixed-time synchronization perfectly. Moreover, the obtained fixed-time synchronization criteria can be verified by algebraic operations. For any initial synchronization error, the settling time of fixed-time synchronization is bounded by a fixed constant, which can be calculated beforehand based on system parameters and controller parameters. Numerical simulations are given to illustrate the effectiveness of our theoretical results. [ABSTRACT FROM AUTHOR]

In this paper, we propose a General Non-negative Matrix Factorization based on the left Semi-Tensor Product (lGNMF) and the General Non-negative Matrix Factorization based on the right Semi-Tensor Product (rGNMF), which factorize an input non-negative matrix into two non-negative matrices of lower ranks based on gradient method. In particular, the proposed models are able to remove the dimension matching constraints required by conventional NMF models. Both theoretical derivation and experimental results show that the conventional NMF is a special case of the proposed lGNMF and rGNMF. We find the method for the best efficacy of the image restoration in lGNMF and rGNMF by experiments on baboon and lenna images. Moreover, inspired by the Incremental Non-negative Matrix Factorization (INMF), we propose the Incremental lGNMF (IlGNMF) and Incremental rGNMF (IrGNMF), We also conduct the experiments on JAFFE database and ORL database, and find that IlGNMF and IrGNMF realize saving storage space and reducing computation time in incremental facial training. [ABSTRACT FROM AUTHOR]

A particle swarm optimization algorithm with crossover operation (PSOCO) is proposed. In the proposed PSOCO, two different crossover operations are employed in order to breed promising exemplars. By performing crossover on the personal historical best position of each particle, the effective guiding exemplars are constructed and they maintain a good diversity. In turn, these high quality exemplars are used to guide the evolution of particles. PSOCO is two-layer particle swarm optimization with positive feedback mechanism. In order to test the performance of PSOCO, we use a set of widely used benchmark functions. The experimental results demonstrate that the proposed PSOCO is a competitive optimizer in terms of both solution quality and efficiency. [ABSTRACT FROM AUTHOR]

This paper is devoted to studying the fixed-time synchronization of memristor-based BAM neural networks (MBAMNNs) with discrete delay. Fixed-time synchronization means that synchronization can be achieved in a fixed time for any initial values of the considered systems. In the light of the double-layer structure of MBAMNNs, we design two similar feedback controllers. Based on Lyapunov stability theories, several criteria are established to guarantee that the drive and response MBAMNNs can realize synchronization in a fixed time. In particular, by changing the parameters of controllers, this fixed time can be adjusted to some desired value in advance, irrespective of the initial values of MBAMNNs. Numerical simulations are included to validate the derived results. [ABSTRACT FROM AUTHOR]

Network coding (NC) provides an elegant solution for improving capacity and robustness in computer networks. Different to traditional “store-and-forward” transmission paradigm, each intermediate node linearly combines received data packets, and the original files can be decoded at the sink nodes in NC settings. This brand-new paradigm is vulnerable to pollution attack, which means that some malicious nodes inject fake data packets into the network and this will lead to incorrect decoding. There are some information-theoretical solutions and cryptographic solutions for solving this security issue, and most existing schemes can thwart data pollution attacks. However, the privacy of the original files are vital to some application environments (e.g. military network). To the best of our knowledge, there is not a secure scheme which can thwart pollution attack and can protect the privacy of transmitted data simultaneously. In this paper, we present an efficient privacy-preserving scheme for secure network coding based on compressed sensing (CS), which has attracted considerable research interest in the signal processing community. Specifically, we embed CS into the general NC framework, i.e., the source node needs to compress each original data packet using the sensing matrix before creating the augmented vector and the sink nodes require to perform an additional CS reconstruction algorithm for reconstructing the original file. In addition, we construct a simple key distribution protocol and each intermediate node just needs two secret keys for verifying the integrity of received data packets. Such novel hybrid construction enables the privacy-preserving guarantee, and the performance comparison shows the high-efficiency of our scheme in terms of the computational complexity and communication overhead. [ABSTRACT FROM AUTHOR]

This paper is concerned with finite-time synchronization problem for multi-link complex networks with two kinds of discontinuous control approaches, e.g., the intermittent control and the impulsive control. Based on the above two discontinuous control methods, comparing with previous continuous control approaches, some less conservative criteria are derived for the finite-time synchronization of the multi-link complex networks. We consider the model of multi-link complex network, which is split into some sub-networks based on different time-delays and each sub-networks can be any network forms. Multi-link complex network with different sub-networks may present some interesting dynamical phenomena. Simple intermittent feedback controller and impulsive feedback controller are designed to achieve finite-time synchronization between the drive network and response network. Several novel and useful finite-time synchronization criteria are also derived based on finite-time stability theory, intermittent and impulsive control techniques. Finally, two numerical simulations are provided to illustrate the effectiveness of the theoretical analysis. [ABSTRACT FROM AUTHOR]

In this paper, we study the finite-time stability problem of neutral-type neural networks with various hybrid time-varying delays. These delays include general time-varying delays, finite distributed time-varying delays, neutral-type time-varying delays and infinite distributed time-varying delays. Based on the definition of finite-time stability instead of Lyapunov function method, with the aid of inequality techniques, some simple and novel sufficient conditions are derived to guarantee the finite-time stability of our proposed network model. The deduction process is simple and easy to understand. Finally, three simulation examples are given to show the effectiveness of our main results. [ABSTRACT FROM AUTHOR]

This paper deals with the finite time synchronization problem of memristor-based neural networks (MNNs) with mixed delays. By utilizing feedback controllers and constructing suitable Lyapunov functionals, several new sufficient conditions guaranteeing the finite time synchronization of MNNs with mixed delays are obtained based on different finite time synchronization analysis techniques. The obtained sufficient conditions are simple and easy to verify. Numerical simulations are given to illustrate the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]

This paper investigates issues of finite-time topological identification and stochastic synchronization for two complex networks with multiple time delays. In the paper, we propose two different approaches to identify the topological structure and guarantee stochastic synchronization for complex networks in finite time, which are achieved based on finite-time stability theory and properties of Wiener process. Several useful finite-time synchronization and identification criteria are obtained simultaneously based on adaptive feedback control method. In the final section, numerical examples are examined to illustrate the effectiveness of the analytical results. [ABSTRACT FROM AUTHOR]