Association of ALOX5AP with ischemic stroke in eastern Chinese

BACKGROUND：5-1ipoxygenase protein （ALOX5AP） has been recognized as a susceptibility gene for stroke and coronary artery diseases. The present study was to explore the role of this gene in the eastern Chinese patients with ischemic stroke.METHODS： Using a case-control design, we studied 658 patients with ischemic stroke and 704 unrelated population-based controls who were age- and sex-matched. The 658 patients were classified by the Trial of Org 10172 in Acute Stroke Treatment （TOAST）. Two single-nucleotide polymorphisms （SNPs） covering ALOX5AP were genotyped. RESULTS： The genotype frequencies of TG of the SNPs rs17222919 located in the promoter of the ALOX5AP gene were significantly higher in patients with ischemic stroke than in controls （OR＊=1.34, 95%C1＊=1.02-1.75）, especially in patients with ischemic stroke caused by small-artery occlusion （SAO） （OR＊=1.40, 95%C1＊=1.02-1.93）. Meanwhile, the genotype frequencies of TG and TG/ GG were higher in female patients than in the controls. After specification, the genotype frequencies of TG and TG/GG were higher in the patients than in controls with hypertension. The genotype frequencies of AG and AG/GG of the SNPs rs9579646 located in the intron of the ALOX5AP gene were higher in the controls than in the patients. After specification, the genotype frequencies of TG were higher in the controls than patients without hypertension. CONCLUSIONS： The present study suggests that sequence variants in the ALOX5AP gene are significantly associated with ischemic stroke.

An image encryption scheme based on three-dimensional Brownian motion and chaotic system

At present, many chaos-based image encryption algorithms have proved to be unsafe, few encryption schemes permute the plain images as three-dimensional（3D） bit matrices, and thus bits cannot move to any position, the movement range of bits are limited, and based on them, in this paper we present a novel image encryption algorithm based on 3D Brownian motion and chaotic systems. The architecture of confusion and diffusion is adopted. Firstly, the plain image is converted into a 3D bit matrix and split into sub blocks. Secondly, block confusion based on 3D Brownian motion（BCB3DBM）is proposed to permute the position of the bits within the sub blocks, and the direction of particle movement is generated by logistic-tent system（LTS）. Furthermore, block confusion based on position sequence group（BCBPSG） is introduced, a four-order memristive chaotic system is utilized to give random chaotic sequences, and the chaotic sequences are sorted and a position sequence group is chosen based on the plain image, then the sub blocks are confused. The proposed confusion strategy can change the positions of the bits and modify their weights, and effectively improve the statistical performance of the algorithm. Finally, a pixel level confusion is employed to enhance the encryption effect. The initial values and parameters of chaotic systems are produced by the SHA 256 hash function of the plain image. Simulation results and security analyses illustrate that our algorithm has excellent encryption performance in terms of security and speed.

Approximate Failures Semantics for Polynomial Labelled Transition Systems

Labelled transition systems(LTSs) are widely used to formally describe system behaviour.The labels of LTS are extended to offer a more satisfactory description of behaviour by refining the abstract labels into multivariate polynomials.These labels can be simplified by numerous numerical approximation methods.Those LTSs that can not apply failures semantics equivalence in description and verification may have a chance after using approximation on labels.The technique that combines approximation and failures semantics equivalence effectively alleviates the computational complexity and minimizes LTS.

Outlier detection by means of robust regression estimators for use in engineering science

This study compares the ability of different robust regression estimators to detect and classify outliers. Well-known estimators with high breakdown points were compared using simulated data. Mean success rates (MSR) were computed and used as comparison criteria. The results showed that the least median of squares (LMS) and least trimmed squares (LTS) were the most successful methods for data that included leverage points, masking and swamping effects or critical and concentrated outliers. We recommend using LMS and LTS as diagnostic tools to classify outliers, because they remain robust even when applied to models that are heavily contaminated or that have a complicated structure of outliers.

Behavioral Consistency Checking between Requirements and Implementations

Checking if the implementations conform to the requirement models is challenging. Most existing techniques for consistency checking either focus on requirement models（e.g., requirements consistency checking）, or on the implementations（e.g., code-based testing） only. In this paper we propose an approach to checking behavioral consistency of implementations against requirement models directly to overcome these limitations. Our approach extracts two behavioral models represented by Labelled Transition Systems（LTS） from requirement models and implementations respectively, and checks the behavioral consistency between these two models based on behavioral simulation relation of LTS. The checking results of our approach provide evidence for behavioral inconsistency as well as inconsistent localization. A research prototype called BCCH and a case study are presented to give initial validation of this approach.