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The Boussinesq equation can describe wave motions in media with damping mechanism, e.g., the propagation of long waves in shallow water and the oscillations of nonlinear elastic strings. To study the propagation of gravity waves on the surface of water, a second spatial variable (say, y) is weakly dependent, and an alternative form of generalized two-dimensional Boussinesq equation is investigated in this paper. Four families of lump solutions are derived by searching for positive quadratic function solutions to the associated bilinear equation. To guarantee the analyticity and rational localization of the lumps, some conditions are posed on both the lump parameters and the coefficients of the generalized two-dimensional Boussinesq equation. Localized structures and energy distribution of the lumps are analyzed as well. [ABSTRACT FROM AUTHOR]

Scale-invariant feature transform (SIFT) algorithm has been successfully applied to object recognition and to image feature extraction, which is a major application in the field of image processing. Nonetheless, the SIFT algorithm has not been solved effectively in practical applications that requires real-time performance, much calculation, and high storage capacity given the framework level and the iterative calculation process in the SIFT Gaussian blur operation. The extraction of image feature information is accelerated using the speeded-up robust features algorithm. However, this algorithm remains sensitive to complicated deformation. To address these problems, in this paper, we proposes a novel algorithmic framework based on bidimensional empirical mode decomposition (BEMD) and SIFT to extract self-adaptive features from images. First, the BEMD algorithm is used to decompose the self-adaptive features of the original image and to obtain multiple BIMF components. Second, the SIFT algorithm optimizes the extraction of parameters that reflect characteristic information on BIMF components. Related parameters are obtained through genetic algorithm optimization. Third, the method for extracting the characteristic information of the BIMF components involves synthesizing all of the accumulated characteristic information in the original image. Comparison results show that the method of calculating image feature extraction speed, accuracy, and reliability has a stronger effect than other methods. [ABSTRACT FROM AUTHOR]

Bidimensional empirical mode decomposition (BEMD) algorithm, with high adaptive ability, provides a suitable tool for the noisy image processing, and, however, the edge effect involved in its operation gives rise to a problem—how to obtain reliable decomposition results to effectively remove noises from the image. Accordingly, we propose an approach to deal with the edge effect caused by BEMD in the decomposition of an image signal and then to enhance its denoising performance. This approach includes two steps, in which the first one is an extrapolation operation through the regression model constructed by the support vector machine (SVM) method with high generalization ability, based on the information of the original signal, and the second is an expansion by the closed-end mirror expansion technique with respect to the extrema nearest to and beyond the edge of the data resulting from the first operation. Applications to remove the Gaussian white noise, salt and pepper noise, and random noise from the noisy images show that the edge effect of the BEMD can be improved effectively by the proposed approach to meet requirement of the reliable decomposition results. They also illustrate a good denoising effect of the BEMD by improving the edge effect on the basis of the proposed approach. Additionally, the denoised image preserves information details sufficiently and also enlarges the peak signal-to-noise ratio. [ABSTRACT FROM AUTHOR]

Delay tolerant networks ( DTN) often have intermittent connection, high delay, high bit error ratio and packet loss rate. Excellent and robust routing algorithm is an important factor for increasing message forwarding rate, reducing delay, improving communication capability in DTN. So the paper designed a kind of earliest deliver routing algorithm based on historical orderliness prediction. Simulation results show that EDHO improves effectively the reliability of message delivery in DTN. [ABSTRACT FROM AUTHOR]

Cervical cancer is a common public health issue with high morbidity worldwide. Paeonol (Pae) has been recognized as a traditional Chinese medicine used for the treatment of various cancer types. However, whether Pae could exert a protective effect on cervical cancer remains to be investigated. The aim of the present study was to explore the role of Pae in cervical cancer cells and identify the potential mechanism. Cell Counting Kit-8 and colony-formation assays were conducted to test the proliferation of HeLa cells. Additionally, wound healing and transwell assays were used to detect the migratory and invasive abilities of cells. The plasmid that overexpressed 5-lipoxygenase (5-LO) or control vector was constructed and transfected into the cells. Subsequently, flow cytometry was used to monitor the apoptotic rate of cells. The expression levels of apoptosis-associated proteins and 5-LO were detected using western blot analysis. Reverse transcription-quantitative PCR analysis detected the expression of 5-LO. Pae inhibited the proliferation, invasion and migration of HeLa cells, promoted cell apoptosis and downregulated the expression of 5-LO. Overexpression of 5-LO, however, attenuated these effects. Thus, Pae could inhibit the proliferation, migration and invasion, as well as promote apoptosis of HeLa cells by regulating the expression of 5-LO. [ABSTRACT FROM AUTHOR]

In the operation of bidimensional empirical mode decomposition, expansion with mirror-image signals is an effective approach to weaken the edge effect. To meet the basic requirement that mirrors should be placed at the extrema, however, there is a problem to make full use of the information involved in the original signal. To address this problem, we propose an approach with the expansion of both support-vector-regression (SVR) extrapolation and mirror-image signals, in which the extrema are captured from the data of SVR extrapolation. The SVR model is constructed with the support vector method (SVM) based on the original signal data. Its extrapolation results in the estimation of the signal data beyond the edge for capturing the extrema so that the information of the original signal can be fully used in locating the mirror. Once all of these extrema points are determined, the traditional mirror expansion method is used and finally edge effects of the BEMD are eliminated. Results from numerical experiments show that the proposed approach has a good capability of improving edge effects of the BEMD operation process, and the reconstruction image from the decomposed components of the intrinsic mode function (IMF) confirms its high coherency with the original one. [ABSTRACT FROM AUTHOR]