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.

Automatic road extraction using high resolution satellite images based on Level Set and Mean Shift methods

Analysis of high resolution satellite images has been an important research topic for urban analysis. One of the important features of urban areas in urban analysis is the automatic road network extraction. Two approaches for road extraction based on Level Set and Mean Shift methods are proposed. From an original image it is difficult and computationally expensive to extract roads due to presences of other road-like features with straight edges. The image is preprocessed to improve the tolerance by reducing the noise (the buildings, parking lots, vegetation regions and other open spaces) and roads are first extracted as elongated regions, nonlinear noise segments are removed using a median filter (based on the fact that road networks constitute large number of small linear structures). Then road extraction is performed using Level Set and Mean Shift method. Finally the accuracy for the road extracted images is evaluated based on quality measures. The 1m resolution IKONOS data has been used for the experiment.

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.

A cyclic peptide mimic of an RNA recognition motif of human La protein is a potent inhibitor of hepatitis C virus

Due to limited available therapeutic options, developing new lead compounds against hepatitis C virus is an urgent need. Human La protein stimulates hepatitis C virus translation through interaction with the hepatitis C viral RNA. A cyclic peptide mimicking the beta-turn of the human La protein that interacts with the viral RNA was synthesized. It inhibits hepatitis C viral RNA translation significantly better than the corresponding linear peptide at longer post-treatment times. The cyclic peptide also inhibited replication as measured by replicon RNA levels using real time RT-PCR. The cyclic peptide emerges as a promising lead compound against hepatitis C.

Human la protein interaction with GCAC near the initiator AUG enhances hepatitis C virus RNA replication by promoting linkage between 5 ` and 3 ` untranslated regions

Human La protein has been implicated in facilitating the internal initiation of translation as well as replication of hepatitis C virus (HCV) RNA. Previously, we demonstrated that La interacts with the HCV internal ribosome entry site (IRES) around the GCAC motif near the initiator AUG within stem-loop IV by its RNA recognition motif (RRM) (residues 112 to 184) and influences HCV translation. In this study, we have deciphered the role of this interaction in HCV replication in a hepatocellular carcinoma cell culture system. We incorporated mutation of the GCAC motif in an HCV monocistronic subgenomic replicon and a pJFH1 construct which altered the binding of La and checked HCV RNA replication by reverse transcriptase PCR (RT-PCR). The mutation drastically affected HCV replication. Furthermore, to address whether the decrease in replication is a consequence of translation inhibition or not, we incorporated the same mutation into a bicistronic replicon and observed a substantial decrease in HCV RNA levels. Interestingly, La overexpression rescued this inhibition of replication. More importantly, we observed that the mutation reduced the association between La and NS5B. The effect of the GCAC mutation on the translation-to-replication switch, which is regulated by the interplay between NS3 and La, was further investigated. Additionally, our analyses of point mutations in the GCAC motif revealed distinct roles of each nucleotide in HCV replication and translation. Finally, we showed that a specific interaction of the GCAC motif with human La protein is crucial for linking 5' and 3' ends of the HCV genome. Taken together, our results demonstrate the mechanism of regulation of HCV replication by interaction of the cis-acting element GCAC within the HCV IRES with human La protein.

Satellite Evaluation of Current status of Irrigation management in Rajolibanda diversion scheme command, Mahaboobnagar District, AP

This article presents the results of a study using satellite remote sensing techniques to evaluate the current status of canal system performance in terms of the spatial and temporal mismatch between water requirements and water releases within the command area The Rajolibanda Diversion Scheme(RDS)is the only operational major irrigation project in the drought prone district of Mahaboobnagar in Andra Pradesh. It is an inter-state project between Karnataka and Andra Pradesh which comprises of an anicut constructed in Karnataka in 1995 across river Thungabhdra and a 143 km long left bank main canel. The initial 42.6 km of the canel lies in Karnataka consisting of 12 distributaries and servers and serves an localised ayacut of 2739ha. In Andra Pradesh, the latter stretch of the main canal consists of distributaries 12A to 40, is localised to serve an ayacut of 35,410 ha.of which 14,215 ha during kharif season,19,332 ha, during rabi season and 1,863 ha.of perennial crops

Estimates of aerosol absorption over India using multi-satellite retrieval

Aerosol absorption is poorly quantified because of the lack of adequate measurements. It has been shown that the Ozone Monitoring Instrument (OMI) aboard EOS-Aura and the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard EOS-Aqua, which fly in formation as part of the A-train, provide an excellent opportunity to improve the accuracy of aerosol retrievals. Here, we follow a multi-satellite approach to estimate the regional distribution of aerosol absorption over continental India for the first time. Annually and regionally averaged aerosol single-scattering albedo over the Indian landmass is estimated as 0.94 +/- 0.03. Our study demonstrates the potential of multi-satellite data analysis to improve the accuracy of retrieval of aerosol absorption over land.

Surface freshwater storage and variability in the Amazon basin from multi-satellite observations, 1993-2007

The amount of water stored and moving through the surface water bodies of large river basins (river, floodplains, wetlands) plays a major role in the global water and biochemical cycles and is a critical parameter for water resources management. However, the spatiotemporal variations of these freshwater reservoirs are still widely unknown at the global scale. Here, we propose a hypsographic curve approach to estimate surface freshwater storage variations over the Amazon basin combining surface water extent from a multi-satellite-technique with topographic data from the Global Digital Elevation Model (GDEM) from Advance Spaceborne Thermal Emission and Reflection Radiometer (ASTER). Monthly surface water storage variations for 1993-2007 are presented, showing a strong seasonal and interannual variability, and are evaluated against in situ river discharge and precipitation. The basin-scale mean annual amplitude of similar to 1200 km(3) is in the range of previous estimates and contributes to about half of the Gravity Recovery And Climate Experiment (GRACE) total water storage variations. For the first time, we map the surface water volume anomaly during the extreme droughts of 1997 (October-November) and 2005 (September-October) and found that during these dry events the water stored in the river and floodplains of the Amazon basin was, respectively, similar to 230 (similar to 40%) and 210 (similar to 50%) km(3) below the 1993-2007 average. This new 15 year data set of surface water volume represents an unprecedented source of information for future hydrological or climate modeling of the Amazon. It is also a first step toward the development of such database at the global scale.

Inactivation of the Bacterial RNA Polymerase Due to Acquisition of Secondary Structure by the omega Subunit

The widely conserved omega subunit encoded by rpoZ is the smallest subunit of Escherichia coli RNA polymerase (RNAP) but is dispensable for bacterial growth. Function of omega is known to be substituted by GroEL in omega-null strain, which thus does not exhibit a discernable phenotype. In this work, we report isolation of omega variants whose expression in vivo leads to a dominant lethal phenotype. Studies show that in contrast to omega, which is largely unstructured, omega mutants display substantial acquisition of secondary structure. By detailed study with one of the mutants, omega(6) bearing N60D substitution, the mechanism of lethality has been deciphered. Biochemical analysis reveals that omega(6) binds to beta ` subunit in vitro with greater affinity than that of omega. The reconstituted RNAP holoenzyme in the presence of omega(6) in vitro is defective in transcription initiation. Formation of a faulty RNAP in the presence of mutant omega results in death of the cell. Furthermore, lethality of omega(6) is relieved in cells expressing the rpoC2112 allele encoding beta ` (2112), a variant beta ` bearing Y457S substitution, immediately adjacent to the beta ` catalytic center. Our results suggest that the enhanced omega(6)-beta ` interaction may perturb the plasticity of the RNAP active center, implicating a role for omega and its flexible state.

Transcriptional Repression of Tumor Suppressor CDC73, Encoding an RNA Polymerase II Interactor, by Wilms Tumor 1 Protein (WT1) Promotes Cell Proliferation IMPLICATION FOR CANCER THERAPEUTICS

The Wilms tumor 1 gene (WT1) can either repress or induce the expression of genes. Inconsistent with its tumor suppressor role, elevated WT1 levels have been observed in leukemia and solid tumors. WT1 has also been suggested to act as an oncogene by inducing the expression of MYC and BCL-2. However, these are only the correlational studies, and no functional study has been performed to date. Consistent with its tumor suppressor role, CDC73 binds to RNA polymerase II as part of a PAF1 transcriptional regulatory complex and causes transcriptional repression of oncogenes MYC and CCND1. It also represses beta-catenin-mediated transcription. Based on the reduced level of CDC73 in oral squamous cell carcinoma (OSCC) samples in the absence of loss-of-heterozygosity, promoter methylation, and mutations, we speculated that an inhibitory transcription factor is regulating its expression. The bioinformatics analysis predicted WT1 as an inhibitory transcription factor to regulate the CDC73 level. Our results showed that overexpression of WT1 decreased CDC73 levels and promoted proliferation of OSCC cells. ChIP and EMSA results demonstrated binding of WT1 to the CDC73 promoter. The 5-azacytidine treatment of OSCC cells led to an up-regulation of WT1 with a concomitant down-regulation of CDC73, further suggesting regulation of CDC73 by WT1. Exogenous CDC73 attenuated the protumorigenic activity of WT1 by apoptosis induction. An inverse correlation between expression levels of CDC73 and WT1 was observed in OSCC samples. These observations indicated that WT1 functions as an oncogene by repressing the expression of CDC73 in OSCC. We suggest that targeting WT1 could be a therapeutic strategy for cancer, including OSCC.

RNA-dependent RNA polymerase of Japanese encephalitis virus binds the initiator nucleotide GTP to form a mechanistically important pre-initiation state

Flaviviral RNA-dependent RNA polymerases (RdRps) initiate replication of the single-stranded RNA genome in the absence of a primer. The template sequence 5'-CU-3' at the 3'-end of the flaviviral genome is highly conserved. Surprisingly, flaviviral RdRps require high concentrations of the second incoming nucleotide GTP to catalyze de novo template-dependent RNA synthesis. We show that GTP stimulates de novo RNA synthesis by RdRp from Japanese encephalitis virus (jRdRp) also. Crystal structures of jRdRp complexed with GTP and ATP provide a basis for specific recognition of GTP. Comparison of the jRdRp(GTP) structure with other viral RdRp-GTP structures shows that GTP binds jRdRp in a novel conformation. Apo-jRdRp structure suggests that the conserved motif F of jRdRp occupies multiple conformations in absence of GTP. Motif F becomes ordered on GTP binding and occludes the nucleotide triphosphate entry tunnel. Mutational analysis of key residues that interact with GTP evinces that the jRdRp(GTP) structure represents a novel pre-initiation state. Also, binding studies show that GTP binding reduces affinity of RdRp for RNA, but the presence of the catalytic Mn2+ ion abolishes this inhibition. Collectively, these observations suggest that the observed pre-initiation state may serve as a check-point to prevent erroneous template-independent RNA synthesis by jRdRp during initiation.

Accurate point matching based on multi-objective Genetic Algorithm for multi-sensor satellite imagery

This paper investigates a novel approach for point matching of multi-sensor satellite imagery. The feature (corner) points extracted using an improved version of the Harris Corner Detector (HCD) is matched using multi-objective optimization based on a Genetic Algorithm (GA). An objective switching approach to optimization that incorporates an angle criterion, distance condition and point matching condition in the multi-objective fitness function is applied to match corresponding corner-points between the reference image and the sensed image. The matched points obtained in this way are used to align the sensed image with a reference image by applying an affine transformation. From the results obtained, the performance of the image registration is evaluated and compared with existing methods, namely Nearest Neighbor-Random SAmple Consensus (NN-Ran-SAC) and multi-objective Discrete Particle Swarm Optimization (DPSO). From the performed experiments it can be concluded that the proposed approach is an accurate method for registration of multi-sensor satellite imagery. (C) 2014 Elsevier Inc. All rights reserved.

Analysis of the Genome and Transcriptome of Cryptococcus neoformans var. grubii Reveals Complex RNA Expression and Microevolution Leading to Virulence Attenuation

Cryptococcus neoformans is a pathogenic basidiomycetous yeast responsible for more than 600,000 deaths each year. It occurs as two serotypes (A and D) representing two varieties (i.e. grubii and neoformans, respectively). Here, we sequenced the genome and performed an RNA-Seq-based analysis of the C. neoformans var. grubii transcriptome structure. We determined the chromosomal locations, analyzed the sequence/structural features of the centromeres, and identified origins of replication. The genome was annotated based on automated and manual curation. More than 40,000 introns populating more than 99% of the expressed genes were identified. Although most of these introns are located in the coding DNA sequences (CDS), over 2,000 introns in the untranslated regions (UTRs) were also identified. Poly(A)-containing reads were employed to locate the polyadenylation sites of more than 80% of the genes. Examination of the sequences around these sites revealed a new poly(A)-site-associated motif (AUGHAH). In addition, 1,197 miscRNAs were identified. These miscRNAs can be spliced and/or polyadenylated, but do not appear to have obvious coding capacities. Finally, this genome sequence enabled a comparative analysis of strain H99 variants obtained after laboratory passage. The spectrum of mutations identified provides insights into the genetics underlying the micro-evolution of a laboratory strain, and identifies mutations involved in stress responses, mating efficiency, and virulence.

Multi-Temporal Satellite Image Analysis Using Gene Expression Programming

This paper discusses an approach for river mapping and flood evaluation to aid multi-temporal time series analysis of satellite images utilizing pixel spectral information for image classification and region-based segmentation to extract water covered region. Analysis of Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images is applied in two stages: before flood and during flood. For these images the extraction of water region utilizes spectral information for image classification and spatial information for image segmentation. 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 artificial neural networks and gene expression programming to 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 region. From the results obtained, we evaluate the performance of the method and conclude that the use of image classification and region-based segmentation is an accurate and reliable for the extraction of water-covered region.