Cardiac over-expression of microRNA-1 induces impairment of cognition in mice.

Large cohort studies have revealed a close relationship between cognitive impairment and cardiovascular diseases, although the mechanism underlying this relationship remains incompletely understood. In this study, using a transgenic (Tg) mouse model of cardiac-specific over-expression of microRNA-1-2 (miR-1-2), we observed that microRNA-1 (miR-1) levels were increased not only in the heart but also in the hippocampus and blood, whereas its levels did not change in the skeletal muscle of Tg mice compared with age-matched wild-type (WT) mice. Six-month-old Tg mice showed cognitive impairment compared with age-matched WT mice, as assessed using the Morris Water Maze test. The brain-derived neurotrophic factor (BDNF) level and cyclic AMP-responsive element-binding protein (CREB) phosphorylation were also significantly reduced in the hippocampi of the Tg mice, as evaluated by Western blot. Further examination showed that BDNF protein expression was down- or up-regulated by miR-1 over-expression or inhibition, respectively, and was unchanged by binding site mutations or miRNA-masks for the 3'UTR of Bdnf, indicating that this gene is a potential target of miR-1. Knockdown of miR-1 by hippocampal stereotaxic injection of an anti-miR-1 oligonucleotide fragment carried by a lentivirus vector (lenti-pre-AMO-miR-1) led to up-regulation of BDNF expression and prevented the reduction in cognitive performance in the Tg mice without affecting cardiac function. Our findings demonstrate that cardiac over-expression of miR-1 also induces behavioral abnormalities that may be associated, at least in part, with the down-regulation of BDNF expression in the hippocampus. This study definitely contributes to the understanding of the relationship between cardiovascular disease and cognitive impairment.

Eigenfunctions and self-imaging phenomena of the two-dimensional nonseparable linear canonical transform.

The two-dimensional (2D) nonseparable linear canonical transform (NSLCT) is a generalization of the fractional Fourier transform (FRFT) and the LCT. It is useful in signal analysis and optics. The eigenfunctions of both the FRFT and the LCT have been derived. In this paper, we extend the previous work and derive the eigenfunctions of the 2D NSLCT. Although the 2D NSLCT is very complicated and has 16 parameters, with the proposed methods, we can successfully find the eigenfunctions of the 2D NSLCT in all cases. Since many optical systems can be represented by the 2D NSLCT, our results are useful for analyzing the self-imaging phenomena of optical systems.

Using color histogram normalization for recovering chromatic illumination-changed images.

We propose a novel image-recovery method using the covariance matrix of the red-green-blue (R-G-B) color histogram and tensor theories. The image-recovery method is called the color histogram normalization algorithm. It is known that the color histograms of an image taken under varied illuminations are related by a general affine transformation of the R-G-B coordinates when the illumination is changed. We propose a simplified affine model for application with illumination variation. This simplified affine model considers the effects of only three basic forms of distortion: translation, scaling, and rotation. According to this principle, we can estimate the affine transformation matrix necessary to recover images whose color distributions are varied as a result of illumination changes. We compare the normalized color histogram of the standard image with that of the tested image. By performing some operations of simple linear algebra, we can estimate the matrix of the affine transformation between two images under different illuminations. To demonstrate the performance of the proposed algorithm, we divide the experiments into two parts: computer-simulated images and real images corresponding to illumination changes. Simulation results show that the proposed algorithm is effective for both types of images. We also explain the noise-sensitive skew-rotation estimation that exists in the general affine model and demonstrate that the proposed simplified affine model without the use of skew rotation is better than the general affine model for such applications.

Simplified fractional Fourier transforms.

The fractional Fourier transform (FRFT) has been used for many years, and it is useful in many applications. Most applications of the FRFT are based on the design of fractional filters (such as removal of chirp noise and the fractional Hilbert transform) or on fractional correlation (such as scaled space-variant pattern recognition). In this study we introduce several types of simplified fractional Fourier transform (SFRFT). Such transforms are all special cases of a linear canonical transform (an affine Fourier transform or an ABCD transform). They have the same capabilities as the original FRFT for design of fractional filters or for fractional correlation. But they are simpler than the original FRFT in terms of digital computation, optical implementation, implementation of gradient-index media, and implementation of radar systems. Our goal is to search for the simplest transform that has the same capabilities as the original FRFT. Thus we discuss not only the formulas and properties of the SFRFT's but also their implementation. Although these SFRFT's usually have no additivity properties, they are useful for the practical applications. They have great potential for replacing the original FRFT's in many applications.

A moment-based approach for deskewing rotationally symmetric shapes.

The covariance matrix of a pattern is composed by its second order central moments. For a rotationally symmetric shape, its covariance matrix is a scalar identity matrix. In this work, we apply this property to restore the skewed shape of rotational symmetry. The relations between the skew transformation matrix and the covariance matrices of original and skewed shapes are derived. By computing the covariance matrix of the skewed shape and letting the covariance matrix of the original shape be a scalar identity matrix, the skew transformation matrix can be solved. Then, the rotationally symmetric shape can be recovered by multiplying the inverse transformation matrix with the skewed shape. The method does not rely on continuous contours and is robust to noise, because only the second-order moments of the input shape are required. Experimental results are also presented.

Color image processing by using binary quaternion-moment-preserving thresholding technique.

This paper presents a new moment-preserving thresholding technique, called the binary quaternion-moment-preserving (BQMP) thresholding, for color image data. Based on representing color data by the quaternions, the statistical parameters of color data can be expressed through the definition of quaternion moments. Analytical formulas of the BQMP thresholding can thus be determined by using the algebra of the quaternions. The computation time for the BQMP thresholding is of order of the data size. By using the BQMP thresholding, quaternion-moment-based operators are designed for the application of color image processing, such as color image compression, multiclass clustering of color data, and subpixel color edge detection. The experimental results show that the proposed operator for color image compression can have output picture quality acceptable to human eyes. In addition, the proposed edge operator can detect the color edge at the subpixel level. Therefore, the proposed BQMP thresholding can be used as a tool for color image processing.

Improved discrete fractional Fourier transform.

The fractional Fourier transform is a useful mathematical operation that generalizes the well-known continuous Fourier transform. Several discrete fractional Fourier transforms (DFRFT's) have been developed, but their results do not match those of the continuous case. We propose a new DFRFT. This improved DFRFT provides transforms similar to those of the continuous fractional Fourier transform and also retains the rotation properties.

Motion-based grouping of optical flow fields: the extrapolation and subtraction technique.

The goal of three-dimensional (3-D) motion segmentation is to identify the image areas projected by different moving objects in 3-D space. However, many prevailing methods merely detected the discontinuity of optical flow field and usually considered these boundaries as that produced by different 3-D motions. In fact, the flow discontinuity can be generated either by two different 3-D motions or by the structural discontinuity on the same moving object. The wrong identification causes several problems in 3-D motion estimation. A simple method called the extrapolation and subtraction (ES) technique is proposed to solve these problems. The input image flow field is first partitioned into several functionally analytic regions. Each analytic region is assumed to be projected by a roughly planar patch moving in 3-D space. Based on the parameterization of these analytic flow fields, the ES technique provides a very simple and fast method to test the 3-D motion compatibility between two interested analytic flow fields.

A parallel decoding algorithm for IFS codes without transient behavior.

Iterated function systems (IFSs) have received great attention in encoding and decoding fractal images. Barnsley (1988) has shown that IFSs for image compression can achieve a very high compression ratio for a single image. However, the major drawback of such a technique is the large computation load required to both encode and decode a fractal image. We provide a novel algorithm to decode IFS codes. The main features of this algorithm are that it is very suitable for parallel implementation and has no transient behavior. Also, from the decoding process of this method we can understand the encoding procedure explicitly. One example is illustrated to demonstrate the quality of its performance.

Elimination of AC interference in electrocardiogram using IIR notch filter with transient suppression.

In this paper, a technique for suppressing the transient states of IIR notch filter is investigated. This technique uses the vector projection to find better initial values for notch filters. When a notch or comb filter is used to eliminate power line (AC) interference in the recording of electrocardiograms (ECG), the performance of the notch filter with transient suppression is better than that of the conventional notch filter with arbitrary initial condition. The improvements with this technique are at the cost of additional computation load at the beginning of filtering.

Wavelet transform and scale space filtering of fractal images.

In this correspondence, we consider wavelet transform and scale space filtering as special cases of general scale shift mapping (SSM). Then, the SSM is used as a tool for characterizing the geometrical complexity of uniform fractals. This tool can reveal the construction rule of fractals and estimate fractal dimension. Finally, we use the results obtained from scale shift mapping to estimate iterated function system (IFS) codes of a class of fractal images. Some examples have been illustrated to demonstrate its good performance.