A Novel Hash Scheme Based on SNP-PLCM

AbstractBy combining the traditional iteration structure of Hash function with the dynamic S-boxes, a novel keyed Hash function is presented. The proposed approach can give a chaotic Hash value by means of the lookup table of functions and chaotic dynamic S-box. Compared with the existing chaotic Hash functions, this method improves computational performance of Hash system by using the chaotic S-box substitution. Theoretical and experimental results show that the proposed method has not only strong one way property, sensitivity to initial conditions and chaotic system's parameters, but also high speed

Preparation and Characterization of SO42-/TiO2-HBeta for Selective Conversion of 1-Methylnaphthalene

In this study, new types of SO42-/TiO2-HBeta (ST/Hβ) catalysts are synthesized and characterized by XRD, IR, N2 adsorption-desorption, ICP-OES, SEM, and NH3-TPD methods. Conversion of 1-methylnaphthalene is carried out in a fixed-bed system. Based on the study's results, the catalysts ST/Hβ showed uniform SO42-/TiO2 (ST) loading, high surface area, and sufficient mild acid sites. When ST content increased, the amount of strong acid sites and by-products decreased. Under atmospheric pressure, catalyst 15-ST/Hβ showed a catalytic performance of 74.1 % conversion and 97.4 % selectivity

A new hybrid method combining genetic algorithm and coordinate search method

This paper proposed a new hybrid method combining genetic algorithm(GA) and coordinate search method (CSM). Genetic algorithm is good at global exploration but bad at accuracy and local search. Whereas, coordinate search method is good at local exploitation, and its accuracy is reliable when searching in a local area. Thus we combine those two methods in this paper to design a hybrid method called genetic algorithm with coordinate search (GACS). Experimental tests shows that this method are good at both global search and local accuracy. © 2012 IEEE

Chaotic Behaviors of Symbolic Dynamics about Rule 58 in Cellular Automata

The complex dynamical behaviors of rule 58 in cellular automata are investigated from the viewpoint of symbolic dynamics. The rule is Bernoulli στ-shift rule, which is members of Wolfram’s class II, and it was said to be simple as periodic before. It is worthwhile to study dynamical behaviors of rule 58 and whether it possesses chaotic attractors or not. It is shown that there exist two Bernoulli-measure attractors of rule 58. The dynamical properties of topological entropy and topological mixing of rule 58 are exploited on these two subsystems. According to corresponding strongly connected graph of transition matrices of determinative block systems, we divide determinative block systems into two subsets. In addition, it is shown that rule 58 possesses rich and complicated dynamical behaviors in the space of bi-infinite sequences. Furthermore, we prove that four rules of global equivalence class ε43 of CA are topologically conjugate. We use diagrams to explain the attractors of rule 58, where characteristic function is used to describe that some points fall into Bernoulli-shift map after several times iterations, and we find that these attractors are not global attractors. The Lameray diagram is used to show clearly the iterative process of an attractor

Stabilization of switched neural networks with time-varying delay via bumpless transfer control

This paper investigates the stabilization of switched neural networks with time-varying delay. In order to overcome the drawback that the classical switching state feedback controller may generate the bumps at switching time, a new switching feedback controller which can smooth effectively the bumps is proposed. According to mode-dependent average dwell time, new exponential stabilization results are deduced for switched neural networks under the proposed feedback controller. Based on a simple corollary, the procedures which are used to calculate the feedback control gain matrices are also obtained. Two simple numerical examples are employed to demonstrate the effectiveness of the proposed results.Peer reviewe

Projective Lag Synchronization of Delayed Neural Networks Using Intermittent Linear State Feedback

The problem of projective lag synchronization of coupled neural networks with time delay is investigated. By means of the Lyapunov stability theory, an intermittent controller is designed for achieving projective lag synchronization between two delayed neural networks systems. Numerical simulations on coupled Lu neural systems illustrate the effectiveness of the results

Synchronization and Lag Synchronization of Hyperchaotic Memristor-Based Chua’s Circuits

A memristor-based five-dimensional (5D) hyperchaotic Chua’s circuit is proposed. Based on the Lyapunov stability theorem, the controllers are designed to realize the synchronization and lag synchronization between the hyperchaotic memristor-based Chua’s circuits under different initial values, respectively. Numerical simulations are also presented to show the effectiveness and feasibility of the theoretical results

TSPAN8 promotes cancer cell stemness via activation of sonic Hedgehog signaling

Cancer stem cells (CSCs) represent a major source of treatment resistance and tumor progression. However, regulation of CSCs stemness is not entirely understood. Here, we report that TSPAN8 expression is upregulated in breast CSCs, promotes the expression of the stemness gene NANOG, OCT4, and ALDHA1, and correlates with therapeutic resistance. Mechanistically, TSPAN8 interacts with PTCH1 and inhibits the degradation of the SHH/PTCH1 complex through recruitment of deubiquitinating enzyme ATXN3. This results in the translocation of SMO to cilia, downstream gene expression, resistance of CSCs to chemotherapeutic agents, and enhances tumor formation in mice. Accordingly, expression levels of TSPAN8, PTCH1, SHH, and ATXN3 are positively correlated in human breast cancer specimens, and high TSPAN8 and ATXN3 expression levels correlate with poor prognosis. These findings reveal a molecular basis of TSPAN8-enhanced Sonic Hedgehog signaling and highlight a role for TSPAN8 in promoting cancer stemness