Conformational transition of DNA induced by cationic lipid vesicle in acidic solution: spectroscopy investigation

The conformational transition of DNA induced by the interaction between DNA and a cationic lipid vesicle, didodecyidimethylammonium bromide (DDAB), had been investigated by circular dichroism (CD) and UV spectroscopy methods. We used singular value decomposition least squares method (SVDLS) to analyze the experimental CD spectra. Although pH value influenced the conformation of DNA in solution, the results showed that upon binding to double helical DNA, positively charged liposomes induced a conformational transition of DNA molecules from the native B-form to more compact conformations. At the same time, no obvious conformational changes occurred at single-strand DNA (ssDNA). While the cationic lipid vesicles and double-strand DNA (dsDNA) were mixed at a high molar ratio of DDAB vesicles to dsDNA, the conformation of dsDNA transformed from the B-form to the C-form resulting in an increase in duplex stability (DeltaT(m) = 8 +/- 0.4 degreesC). An increasing in T-m was also observed while the cationic lipid vesicles interacted with ssDNA.

Structural electrochemical study of hemoglobin by in situ circular dichroism thin layer spectroelectrochemistry

Secondary and tertiary or quaternary structural changes in hemoglobin (HB) during an electroreduction process were studied by in situ circular dichroism (CD) spectroelectrochemistry with a long optical path thin-layer cell. By means of singular value decomposition least-squares analysis, CD spectra in the far-UV region give two similar a components with different CD intensity, indicating slight denaturation in the secondary structures due to the electric field effect. CD spectra in the Soret band show a R --> T transition of two quaternary structural components induced by electroreduction of the heme, which changes the redox states of the center ion from Fe3+ to Fe2+ and the coordination number from 6 to 5. The double logarithmic analysis shows that electroreduction of hemoglobin follows a chemical reaction with R --> T transition. Some parameters in the electrochemical process were obtained: formal potential, E-0t = -0.167 V; electrochemical kinetic overpotential, DeltaE(0) = -0.32 V; standard electrochemical reaction rate constant, k(0) = 1.79 x 10(-5) cm s(-1); product of electron transfer coefficient and electron number, alphan=0.14; and the equilibrium constant of R --> T transition, K-c = 9.0.

Conformational transition of DNA in electroreduction studied by in situ UV and CD thin layer spectroelectrochemistry

Electrochemically induced three conformational transitions of calf thymus DNA from B-10.4 to Z(10.2)-DNA and from B-10.2 to B-10.4 and to C-DNA in 10 mM phosphate buffer solution (pH 7.21) at glassy carbon electrode are found and studied by in situ circular dichroism (CD) thin layer spectroelectrochemistry with singular value decomposition least square (SVDLS) analysis. It indicates that the so-called B-10.2 form and the C-form of DNA may be composed of B-10.4 and left-A DNA and of B-10.4 and right-A DNA, respectively. The irreversible electrochemical reduction of adenine and cytosine groups in the DNA molecule is studied by UV-Vis spectroelectrochemistry. Some electrochemical parameters alphan = 0.17, E-0' = -0.70 V (vs. Ag/AgCl), and the standard heterogeneous electron transfer rate constant, k(0) = 1.8 x 10(-5) cm s(-1) are obtained by double logarithmic analysis and non-linear regression. (C) 2000 Elsevier Science B.V. All rights reserved.

Circular dichroism spectro electrochemical and voltammetric studies of vitamin B-2

Electroreduction of vitamin B-2 (VB2) was studied by in situ circular dichroism (CD) spectroelectrochemistry (SEC) with a long optical path length thin layer cell (LOPLTLC). The results showed that the electroreduction of VB2 in phosphate buffer solution (PBS) (PH 6.8) was a two-electron electrochemical process with weak adsorption of the reactant at the glassy carbon (GC) electrode surface. The CD spectra change of VB2 in the reduction process was explained with the theory of electronic states. We also treated the CD spectra with a singular value decomposition least square (SVDLS) method, and have found not only the number of components and their spectra, but also the fraction distribution of each component in the electroreduction process of VB2.

The electrochemically induced conformational transition of disulfides in bovine serum albumin studied by thin layer circular dichroism spectroelectrochemistry

The conformational transition of disulfides in bovine serum albumin (BSA) induced by electrochemical redox reaction of disulfides were monitored by in-situ circular dichroism (CD) spectroelectrochemistry, with a long optical path thin layer cell and analyzed by a singular value decomposition least square (SVDLS) method. Electrochemical reduction of disulfides drives the left-handed conformation of disulfides changed into the right-handed. At open circuit, eight of the 17 disulfides were of left-handed conformation. Four of the 17 disulfides took part in the electrochemical reduction with an EC mechanism. Only one-fourth of the reduced disulfides returned to left-handed conformation in the re-oxidation process. Some parameters of the electrochemical reduction process, i.e. the number of electrons transferred and electron transfer coefficient, n=8, alphan=0.15, apparent formal potential, E-1(0') = -0.65(+/-0.01) V, standard heterogeneous electron transfer rate constant, k(1)(0) = (2.84 +/- 0.14)x 10(-5) cm s(-1) and chemical reaction equilibrium constant, K-c=(5.13 +/- 0.12) x 10(-2), were also obtained by double logarithmic analysis based on the near-UV absorption spectra with applied potentials. (C) 2001 Elsevier Science B.V. All rights reserved.

基于SVD和能量最小原则的图像自适应降噪算法

基于奇异值分解和能量最小原则,提出了一种自适应图像降噪算法,并给出了基于有界变差的能量降噪模型的代数形式。通过在矩阵范数意义下求能量最小,自适应确定去噪图像重构的奇异值个数。该算法的特点是将能量最小法则和奇异值分解结合起来,在代数空间中建立了一种自适应的图像降噪算法。与基于压缩比和奇异值分解的降噪方法相比,由于该算法避免了图像压缩比函数及其拐点的计算,因此具有快速去噪和简单可行的优点。实验结果证明,该算法是有效的。

小波域地震资料的处理方法（WSSP）研究

The modeling formula based on seismic wavelet can well simulate zero - phase wavelet and hybrid-phase wavelet, and approximate maximal - phase and minimal - phase wavelet in a certain sense. The modeling wavelet can be used as wavelet function after suitable modification item added to meet some conditions. On the basis of the modified Morlet wavelet, the derivative wavelet function has been derived. As a basic wavelet, it can be sued for high resolution frequency - division processing and instantaneous feature extraction, in acoordance with the signal expanding characters in time and scale domains by each wavelet structured. Finally, an application example proves the effectiveness and reasonability of the method. Based on the analysis of SVD (Singular Value Decomposition) filter, by taking wavelet as basic wavelet and combining SVD filter and wavelet transform, a new de - noising method, which is Based on multi - dimension and multi-space de - noising method, is proposed. The implementation of this method is discussed the detail. Theoretical analysis and modeling show that the method has strong capacity of de - noising and keeping attributes of effective wave. It is a good tool for de - noising when the S/N ratio is poor. To give prominence to high frequency information of reflection event of important layer and to take account of other frequency information under processing seismic data, it is difficult for deconvolution filter to realize this goal. A filter from Fourier Transform has some problems for realizing the goal. In this paper, a new method is put forward, that is a method of processing seismic data in frequency division from wavelet transform and reconstruction. In ordinary seismic processing methods for resolution improvement, deconvolution operator has poor part characteristics, thus influencing the operator frequency. In wavelet transform, wavelet function has very good part characteristics. Frequency - division data processing in wavelet transform also brings quite good high resolution data, but it needs more time than deconvolution method does. On the basis of frequency - division processing method in wavelet domain, a new technique is put forward, which involves 1) designing filter operators equivalent to deconvolution operator in time and frequency domains in wavelet transform, 2) obtaining derivative wavelet function that is suitable to high - resolution seismic data processing, and 3) processing high resolution seismic data by deconvolution method in time domain. In the method of producing some instantaneous characteristic signals by using Hilbert transform, Hilbert transform is very sensitive to high - frequency random noise. As a result, even though there exist weak high - frequency noises in seismic signals, the obtained instantaneous characteristics of seismic signals may be still submerged by the noises. One method for having instantaneous characteristics of seismic signals in wavelet domain is put forward, which obtains directly the instantaneous characteristics of seismic signals by taking the characteristics of both the real part (real signals, namely seismic signals) and the imaginary part (the Hilbert transfom of real signals) of wavelet transform. The method has the functions of frequency division and noise removal. What is more, the weak wave whose frequency is lower than that of high - frequency random noise is retained in the obtained instantaneous characteristics of seismic signals, and the weak wave may be seen in instantaneous characteristic sections (such as instantaneous frequency, instantaneous phase and instantaneous amplitude). Impedance inversion is one of tools in the description of oil reservoir. one of methods in impedance inversion is Generalized Linear Inversion. This method has higher precision of inversion. But, this method is sensitive to noise of seismic data, so that error results are got. The description of oil reservoir in researching important geological layer, in order to give prominence to geological characteristics of the important layer, not only high frequency impedance to research thin sand layer, but other frequency impedance are needed. It is difficult for some impedance inversion method to realize the goal. Wavelet transform is very good in denoising and processing in frequency division. Therefore, in the paper, a method of impedance inversion is put forward based on wavelet transform, that is impedance inversion in frequency division from wavelet transform and reconstruction. in this paper, based on wavelet transform, methods of time - frequency analysis is given. Fanally, methods above are in application on real oil field - Sansan oil field.

Intensification of summer rainfall variability in the southeastern United States during recent decades

The variability of summer precipitation in the southeastern United States is examined in this study using 60-yr (1948-2007) rainfall data. The Southeast summer rainfalls exhibited higher interannual variability with more intense summer droughts and anomalous wetness in the recent 30 years (1978-2007) than in the prior 30 years (1948-77). Such intensification of summer rainfall variability was consistent with a decrease of light (0.1-1 mm day-1) and medium (1-10 mm day-1) rainfall events during extremely dry summers and an increase of heavy (.10 mm day-1) rainfall events in extremely wet summers. Changes in rainfall variability were also accompanied by a southward shift of the region of maximum zonal wind variability at the jet stream level in the latter period. The covariability between the Southeast summer precipitation and sea surface temperatures (SSTs) is also analyzed using the singular value decomposition (SVD) method. It is shown that the increase of Southeast summer precipitation variability is primarily associated with a higher SST variability across the equatorial Atlantic and also SST warming in the Atlantic. © 2010 American Meteorological Society.

Application of regularization methods to damage detection in large scale plane frame structures using incomplete noisy modal data

This paper presents an approach for detecting local damage in large scale frame structures by utilizing regularization methods for ill-posed problems. A direct relationship between the change in stiffness caused by local damage and the measured modal data for the damaged structure is developed, based on the perturbation method for structural dynamic systems. Thus, the measured incomplete modal data can be directly adopted in damage identification without requiring model reduction techniques, and common regularization methods could be effectively employed to solve the developed equations. Damage indicators are appropriately chosen to reflect both the location and severity of local damage in individual components of frame structures such as in brace members and at beam-column joints. The Truncated Singular Value Decomposition solution incorporating the Generalized Cross Validation method is introduced to evaluate the damage indicators for the cases when realistic errors exist in modal data measurements. Results for a 16-story building model structure show that structural damage can be correctly identified at detailed level using only limited information on the measured noisy modal data for the damaged structure.

Application-Specific Instruction Set Processor for SoC implementation of Modern Signal Processing Algorithms

A novel application-specific instruction set processor (ASIP) for use in the construction of modern signal processing systems is presented. This is a flexible device that can be used in the construction of array processor systems for the real-time implementation of functions such as singular-value decomposition (SVD) and QR decomposition (QRD), as well as other important matrix computations. It uses a coordinate rotation digital computer (CORDIC) module to perform arithmetic operations and several approaches are adopted to achieve high performance including pipelining of the micro-rotations, the use of parallel instructions and a dual-bus architecture. In addition, a novel method for scale factor correction is presented which only needs to be applied once at the end of the computation. This also reduces computation time and enhances performance. Methods are described which allow this processor to be used in reduced dimension (i.e., folded) array processor structures that allow tradeoffs between hardware and performance. The net result is a flexible matrix computational processing element (PE) whose functionality can be changed under program control for use in a wider range of scenarios than previous work. Details are presented of the results of a design study, which considers the application of this decomposition PE architecture in a combined SVD/QRD system and demonstrates that a combination of high performance and efficient silicon implementation are achievable. © 2005 IEEE.

TDM modelling and evaluation of different domain transforms for LSI

Latent semantic indexing (LSI) is a popular technique used in information retrieval (IR) applications. This paper presents a novel evaluation strategy based on the use of image processing tools. The authors evaluate the use of the discrete cosine transform (DCT) and Cohen Daubechies Feauveau 9/7 (CDF 9/7) wavelet transform as a pre-processing step for the singular value decomposition (SVD) step of the LSI system. In addition, the effect of different threshold types on the search results is examined. The results show that accuracy can be increased by applying both transforms as a pre-processing step, with better performance for the hard-threshold function. The choice of the best threshold value is a key factor in the transform process. This paper also describes the most effective structure for the database to facilitate efficient searching in the LSI system.

SVD-Based Universal Spatial Domain Image Steganalysis

This paper is concerned with the universal (blind) image steganalysis problem and introduces a novel method to detect especially spatial domain steganographic methods. The proposed steganalyzer models linear dependencies of image rows/columns in local neighborhoods using singular value decomposition transform and employs content independency provided by a Wiener filtering process. Experimental results show that the novel method has superior performance when compared with its counterparts in terms of spatial domain steganography. Experiments also demonstrate the reasonable ability of the method to detect discrete cosine transform-based steganography as well as the perturbation quantization method.

Enhanced approach for latent semantic indexing using wavelet transform

Latent semantic indexing (LSI) is a technique used for intelligent information retrieval (IR). It can be used as an alternative to traditional keyword matching IR and is attractive in this respect because of its ability to overcome problems with synonymy and polysemy. This study investigates various aspects of LSI: the effect of the Haar wavelet transform (HWT) as a preprocessing step for the singular value decomposition (SVD) in the key stage of the LSI process; and the effect of different threshold types in the HWT on the search results. The developed method allows the visualisation and processing of the term document matrix, generated in the LSI process, using HWT. The results have shown that precision can be increased by applying the HWT as a preprocessing step, with better results for hard thresholding than soft thresholding, whereas standard SVD-based LSI remains the most effective way of searching in terms of recall value.

Loss-of-Main Monitoring and Detection for Distributed Generations Using Dynamic Principal Component Analysis

In this paper, our previous work on Principal Component Analysis (PCA) based fault detection method is extended to the dynamic monitoring and detection of loss-of-main in power systems using wide-area synchrophasor measurements. In the previous work, a static PCA model was built and verified to be capable of detecting and extracting system faulty events; however the false alarm rate is high. To address this problem, this paper uses a well-known ‘time lag shift’ method to include dynamic behavior of the PCA model based on the synchronized measurements from Phasor Measurement Units (PMU), which is named as the Dynamic Principal Component Analysis (DPCA). Compared with the static PCA approach as well as the traditional passive mechanisms of loss-of-main detection, the proposed DPCA procedure describes how the synchrophasors are linearly
auto- and cross-correlated, based on conducting the singular value decomposition on the augmented time lagged synchrophasor matrix. Similar to the static PCA method, two statistics, namely T2 and Q with confidence limits are calculated to form intuitive charts for engineers or operators to monitor the loss-of-main situation in real time. The effectiveness of the proposed methodology is evaluated on the loss-of-main monitoring of a real system, where the historic data are recorded from PMUs installed in several locations in the UK/Ireland power system.

Anytime information processing based on fuzzy and neural network models

In modern measurement and control systems, the available time and resources are often not only limited, but could change during the operation of the system. In these cases, the so-called anytime algorithms could be used advantageously. While diflerent soft computing methods are wide-spreadly used in system modeling, their usability in these cases are limited.