Targeting ribosome assembly on the HCV RNA using a small RNA molecule

Translation initiation of hepatitis C virus (HCV) RNA is the initial obligatory step of the viral life cycle, mediated through the internal ribosome entry site (IRES) present in the 5'-untranslated region (UTR). Initiation on the HCV IRES is mediated by multiple structure-specific interactions between IRES RNA and host 40S ribosomal subunit. In the present study we demonstrate that the SLIIIef domain, in isolation from other structural elements of HCV IRES, retain the ability to interact with 40S ribosome subunit. A small RNA SLRef, mimicking the SLIIIef domain was found to interact specifically with human La protein and the ribosomal protein S5 and selectively inhibit HCV RNA translation. More importantly, SLRef RNA showed significant suppression of replication in HCV monocistronic replicon and decrease of negative strand synthesis in HCV cell culture system. Finally, using Sendai virus based virosome, the targeted delivery of SLRef RNA into mice liver succeeded in selectively inhibiting HCV IRES mediated translation in vivo.

An approach to multi-temporal MODIS image analysis using image classification and segmentation

This paper discusses an approach for river mapping and flood evaluation based on multi-temporal time series analysis of satellite images utilizing pixel spectral information for image classification and region-based segmentation for extracting water-covered regions. Analysis of MODIS satellite images is applied in three stages: before flood, during flood and after flood. Water regions are extracted from the MODIS images using image classification (based on spectral information) and image segmentation (based on spatial information). Multi-temporal MODIS images from ``normal'' (non-flood) and flood time-periods are processed in two steps. In the first step, image classifiers such as Support Vector Machines (SVMs) and Artificial Neural Networks (ANNs) separate the image pixels into water and non-water groups based on their spectral features. The classified image is then segmented using spatial features of the water pixels to remove the misclassified water. From the results obtained, we evaluate the performance of the method and conclude that the use of image classification (SVM and ANN) and region-based image segmentation is an accurate and reliable approach for the extraction of water-covered regions. (c) 2012 COSPAR. Published by Elsevier Ltd. All rights reserved.

Inhibition of the Interaction Between NS3 Protease and HCV IRES With a Small Peptide: A Novel Therapeutic Strategy

Recently, we have demonstrated that the protease domain of NS3 alone can bind specifically to hepatitis C virus (HCV) internal ribosome entry site (IRES) near the initiator AUG, dislodges human La protein and inhibits translation in favor of viral RNA replication. Here, by using a computational approach, the contact points of the protease on the HCV IRES were putatively mapped. A 30-mer NS3 peptide was designed from the predicted RNA-binding region that retained RNA-binding ability and also inhibited IRES-mediated translation. This peptide was truncated to 15 mer and this also demonstrated ability to inhibit HCV RNA-directed translation as well as replication. More importantly, its activity was tested in an in vivo mouse model by encapsulating the peptide in Sendai virus virosomes followed by intravenous delivery. The study demonstrates for the first time that the HCV NS3-IRES RNA interaction can be selectively inhibited using a small peptide and reports a strategy to deliver the peptide into the liver.

Determination of Isospectral Nonuniform Rotating Beams

In this paper we look for nonuniform rotating beams that are isospectral to a given uniform nonrotating beam. A rotating nonuniform beam is isospectral to the given uniform nonrotating beam if both the beams have the same spectral properties, i.e., both the beams have the same set of natural frequencies under a given boundary condition. The Barcilon-Gottlieb type transformation is proposed that converts the governing equation of a rotating beam to that of a uniform nonrotating beam. We show that there exist rotating beams isospectral to a given uniform nonrotating beam under some special conditions. The boundary conditions we consider are clamped-free and hinged-free with an elastic hinge spring. An upper bound on the rotation speed for which isospectral beams exist is proposed. The mass and stiffness distributions for these nonuniform rotating beams which are isospectral to the given uniform nonrotating beam are obtained. We use these mass and stiffness distributions in a finite element analysis to show that the obtained beams are isospectral to the given uniform nonrotating beam. A numerical example of a beam having a rectangular cross section is presented to show the application of our analysis. DOI: 10.1115/1.4006460]

MULTI-OBJECTIVE GENETIC ALGORITHM FOR EFFICIENT POINT MATCHING IN MULTI-SENSOR SATELLITE IMAGE

This paper investigates a new approach for point matching in multi-sensor satellite images. The feature points are matched using multi-objective optimization (angle criterion and distance condition) based on Genetic Algorithm (GA). This optimization process is more efficient as it considers both the angle criterion and distance condition to incorporate multi-objective switching in the fitness function. This optimization process helps in matching three corresponding corner points detected in the reference and sensed image and thereby using the affine transformation, the sensed image is aligned with the reference image. From the results obtained, the performance of the image registration is evaluated and it is concluded that the proposed approach is efficient.

Quasi-based hierarchical clustering for land cover mapping using satellite images

This paper presents an improved hierarchical clustering algorithm for land cover mapping problem using quasi-random distribution. Initially, Niche Particle Swarm Optimization (NPSO) with pseudo/quasi-random distribution is used for splitting the data into number of cluster centers by satisfying Bayesian Information Criteria (BIC). Themain objective is to search and locate the best possible number of cluster and its centers. NPSO which highly depends on the initial distribution of particles in search space is not been exploited to its full potential. In this study, we have compared more uniformly distributed quasi-random with pseudo-random distribution with NPSO for splitting data set. Here to generate quasi-random distribution, Faure method has been used. Performance of previously proposed methods namely K-means, Mean Shift Clustering (MSC) and NPSO with pseudo-random is compared with the proposed approach - NPSO with quasi distribution(Faure). These algorithms are used on synthetic data set and multi-spectral satellite image (Landsat 7 thematic mapper). From the result obtained we conclude that use of quasi-random sequence with NPSO for hierarchical clustering algorithm results in a more accurate data classification.

Clustering using Levy Flight Cuckoo Search

In this paper, a comparative study is carried using three nature-inspired algorithms namely Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Cuckoo Search (CS) on clustering problem. Cuckoo search is used with levy flight. The heavy-tail property of levy flight is exploited here. These algorithms are used on three standard benchmark datasets and one real-time multi-spectral satellite dataset. The results are tabulated and analysed using various techniques. Finally we conclude that under the given set of parameters, cuckoo search works efficiently for majority of the dataset and levy flight plays an important role.

Spectral-spatial MODIS image analysis using swarm intelligence algorithms and region based segmentation for flood assessment

This paper discusses an approach for river mapping and flood evaluation based on multi-temporal time-series analysis of satellite images utilizing pixel spectral information for image clustering and region based segmentation for extracting water covered regions. MODIS satellite images are analyzed at two stages: before flood and during flood. Multi-temporal MODIS images are processed in two steps. In the first step, clustering algorithms such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are used to distinguish the water regions from the non-water based on spectral information. These algorithms are chosen since they are quite efficient in solving multi-modal optimization problems. These classified images are then segmented using spatial features of the water region to extract the river. From the results obtained, we evaluate the performance of the methods and conclude that incorporating region based image segmentation along with clustering algorithms provides accurate and reliable approach for the extraction of water covered region.

Multi-objective optimization of satellite image registration using discrete Pparticle swarm optimisation

A new multi-sensor image registration technique is proposed based on detecting the feature corner points using modified Harris Corner Detector (HDC). These feature points are matched using multi-objective optimization (distance condition and angle criterion) based on Discrete Particle Swarm Optimization (DPSO). This optimization process is more efficient as it considers both the distance and angle criteria to incorporate multi-objective switching in the fitness function. This optimization process helps in picking up three corresponding corner points detected in the sensed and base image and thereby using the affine transformation, the sensed image is aligned with the base image. Further, the results show that the new approach can provide a new dimension in solving multi-sensor image registration problems. From the obtained results, the performance of image registration is evaluated and is concluded that the proposed approach is efficient.

Hierarchical artificial immune system for crop stage classification

This paper presents a new hierarchical clustering algorithm for crop stage classification using hyperspectral satellite image. Amongst the multiple benefits and uses of remote sensing, one of the important application is to solve the problem of crop stage classification. Modern commercial imaging satellites, owing to their large volume of satellite imagery, offer greater opportunities for automated image analysis. Hence, we propose a unsupervised algorithm namely Hierarchical Artificial Immune System (HAIS) of two steps: splitting the cluster centers and merging them. The high dimensionality of the data has been reduced with the help of Principal Component Analysis (PCA). The classification results have been compared with K-means and Artificial Immune System algorithms. From the results obtained, we conclude that the proposed hierarchical clustering algorithm is accurate.

Microwave Spectroscopic and Atoms in Molecules Theoretical Investigations on the ArPropargyl Alcohol Complex: ArHO, Ar, and ArC Interactions

The structure of the Arpropargyl alcohol (ArPA) complex is determined from the rotational spectra of the parent complex and its two deuterated isotopologues, namely ArPA-D(OD) and ArPA-D(CD). The spectra confirm a geometry in which PA exists in the gauche form with Ar located in between OH and CCH groups. All a, b and c types of transitions show small splitting due to some large-amplitude motion dominated by COH torsion, as in the monomer. Splittings in a- and b-type transitions are of the order of a few kilohertz, whereas splitting in the c-type transitions is relatively larger (0.92.6 MHz) and decreases in the order ArPA>ArPA-D(CD)>ArPA-D(OD). The assignments are well supported by ab initio calculations. Atoms in molecules (AIM) and electrostatic potential calculations are used to explore the nature of the interactions in this complex. AIM calculations not only reveal the expected OHAr and Ar interactions in the Argauche-PA complex, but also novel CAr (of CH2OH group) and OHAr interactions in the Artrans-PA complex. Similar interactions are also present in the Armethanol complex.

Non-rotating beams isospectral to a given rotating uniform beam

In this paper, we seek to find non-rotating beams with continuous mass and flexural stiffness distributions, that are isospectral to a given uniform rotating beam. The Barcilon-Gottlieb transformation is used to convert the fourth order governing equation of a non-rotating beam, to a canonical fourth order eigenvalue problem. If the coefficients in this canonical equation match with the coefficients of the uniform rotating beam equation, then the non-rotating beam is isospectral to the given rotating beam. The conditions on matching the coefficients leads to a pair of coupled differential equations. We solve these coupled differential equations for a particular case, and thereby obtain a class of non-rotating beams that are isospectral to a uniform rotating beam. However, to obtain isospectral beams, the transformation must leave the boundary conditions invariant. We show that the clamped end boundary condition is always invariant, and for the free end boundary condition to be invariant, we impose certain conditions on the beam characteristics. We also verify numerically that the frequencies of the non-rotating beam obtained using the finite element method (FEM) are the exact frequencies of the uniform rotating beam. Finally, the example of beams having a rectangular cross-section is presented to show the application of our analysis. Since experimental determination of rotating beam frequencies is a difficult task, experiments can be easily conducted on these rectangular non-rotating beams, to calculate the frequencies of the rotating beam. (c) 2012 Elsevier Ltd. All rights reserved.

Multiple parents crossover operators: A new approach removes the overlapping solutions for sequencing problems

Maintaining population diversity throughout generations of Genetic Algorithms (GAs) is key to avoid premature convergence. Redundant solutions is one cause for the decreasing population diversity. To prevent the negative effect of redundant solutions, we propose a framework that is based on the multi-parents crossover (MPX) operator embedded in GAs. Because MPX generates diversified chromosomes with good solution quality, when a pair of redundant solutions is found, we would generate a new offspring by using the MPX to replace the redundant chromosome. Three schemes of MPX will be examined and will be compared against some algorithms in literature when we solve the permutation flowshop scheduling problems, which is a strong NP-Hard sequencing problem. The results indicate that our approach significantly improves the solution quality. This study is useful for researchers who are trying to avoid premature convergence of evolutionary algorithms by solving the sequencing problems.

Rotating beams isospectral to axially loaded nonrotating uniform beams

In this paper, the stiffness and mass per unit length distributions of a rotating beam, which is isospectral to a given uniform axially loaded nonrotating beam, are determined analytically. The Barcilon-Gottlieb transformation is extended so that it transforms the governing equation of a rotating beam into the governing equation of a uniform, axially loaded nonrotating beam. Analysis is limited to a certain class of Euler-Bernoulli cantilever beams, where the product between the stiffness and the cube of mass per unit length is a constant. The derived mass and stiffness distributions of the rotating beam are used in a finite element analysis to confirm the frequency equivalence of the given and derived beams. Examples of physically realizable beams that have a rectangular cross section are shown as a practical application of the analysis.