GBJOF: Gradient Boosting Integrated with Jaya Algorithm to Optimize the Features in Malware Analysis

Malware analysis is used to identify suspicious file transferring in the network. It can be identified efficiently by using the reverse engineering hybrid approach. Implementing a hybrid approach depends on the feature selection because the dataset contains static and dynamic parameters. The given dataset contains 85 attributes with 10 different class labels. Since it has high dimensional and multi-classification data, existing approaches of ML could be more efficient in reducing the features. The model combines the enhanced JAYA genetic algorithm with a gradient boosting technique to identify the efficiency and a smaller number of features. Many existing approaches for feature selection either implement correlation analysis or wrapper techniques. The major disadvantages of these issues are that they are facing fitting problems with a very small number of features. With the Usage of the genetic approach, this paper has achieved 95% accuracy with 12 features, approximately 7% greater than ML approaches

Performance of the ocean state forecast system at Indian National Centre for Ocean Information Services

The reliability of the operational Ocean State Forecast system at the Indian National Centre for Ocean Information Services (INCOIS) during tropical cyclones that affect the coastline of India is described in this article. The performance of this system during cyclone Thane that severely affected the southeast coast of India during the last week of December 2011 is reported here. Spec-tral wave model is used for forecasting the wave fields generated by the tropical cyclone and vali-dation of the same is done using real-time automated observation systems. The validation results indicate that the forecasted wave parameters agree well with the measurements. The feedback from the user community indicates that the forecast was reliable and highly useful. Alerts based on this operational ocean state forecast system are thus useful for protecting the property and lives of the coastal communities along the coastline of India. INCOIS is extending this service for the benefit of the other countries along the Indian Ocean rim

Meraculous: De Novo Genome Assembly with Short Paired-End Reads

We describe a new algorithm, meraculous, for whole genome assembly of deep paired-end short reads, and apply it to the assembly of a dataset of paired 75-bp Illumina reads derived from the 15.4 megabase genome of the haploid yeast Pichia stipitis. More than 95% of the genome is recovered, with no errors; half the assembled sequence is in contigs longer than 101 kilobases and in scaffolds longer than 269 kilobases. Incorporating fosmid ends recovers entire chromosomes. Meraculous relies on an efficient and conservative traversal of the subgraph of the k-mer (deBruijn) graph of oligonucleotides with unique high quality extensions in the dataset, avoiding an explicit error correction step as used in other short-read assemblers. A novel memory-efficient hashing scheme is introduced. The resulting contigs are ordered and oriented using paired reads separated by ∼280 bp or ∼3.2 kbp, and many gaps between contigs can be closed using paired-end placements. Practical issues with the dataset are described, and prospects for assembling larger genomes are discussed

Schizophrenia-associated somatic copy-number variants from 12,834 cases reveal recurrent NRXN1 and ABCB11 disruptions

While germline copy-number variants (CNVs) contribute to schizophrenia (SCZ) risk, the contribution of somatic CNVs (sCNVs)—present in some but not all cells—remains unknown. We identified sCNVs using blood-derived genotype arrays from 12,834 SCZ cases and 11,648 controls, filtering sCNVs at loci recurrently mutated in clonal blood disorders. Likely early-developmental sCNVs were more common in cases (0.91%) than controls (0.51%, p = 2.68e−4), with recurrent somatic deletions of exons 1–5 of the NRXN1 gene in five SCZ cases. Hi-C maps revealed ectopic, allele-specific loops forming between a potential cryptic promoter and non-coding cis-regulatory elements upon 5′ deletions in NRXN1. We also observed recurrent intragenic deletions of ABCB11, encoding a transporter implicated in anti-psychotic response, in five treatment-resistant SCZ cases and showed that ABCB11 is specifically enriched in neurons forming mesocortical and mesolimbic dopaminergic projections. Our results indicate potential roles of sCNVs in SCZ risk

Assessment of Genetic and Pathogenic Diversity of Xanthomonas oryzae pv. oryzae on High Yielding Local Variety, Tella Hamsa, from Farmer Fields in Gagillapur and Kompally, Andhra Pradesh

Rice is one of the most important food crops of the world which is grown in various agro climatic conditions and it encounters several biotic and abiotic stresses. Among biotic stresses bacterial leaf blight caused by Xanthomonas oryzae pv. oryzae is the major destructive disease in the world. There is no chemical effective against this disease, so growing resistant varieties is the only way to decrease the losses caused by the disease. To develop durable resistance varieties in the particular area under biotic stress conditions necessitates evaluation of rice genotypes. The present study revealed significant fingerprinting variations observed among the 44 Xanthomonas oryzae pv. oryzae isolates from Tella Hamsa genotype collected from different areas, Gagillapur and Kompally. In addition, much diverse pathotypic variation or virulence pattern was detected from set of differentials containing near isogenic lines and traditional cultivar differentials. Virulence data obtained from these differentials revealed that all of them were compatible with the resistance genes. However, these pathotypes were incompatible with the genes, xa-5, Xa-10, xa-13 and Xa-21 suggesting the possibility of deploying them for enhancing the resistance. Similar observations were reported in the research area of rice crop improvement. So, this study suggests the deployment of genes in combinations of two and three expressed wide spectrum of longevity resistance to bacterial blight pathogen

Factors affecting the ability of the spectral domain optical coherence tomograph to detect photographic retinal nerve fiber layer defects.

To evaluate the ability of normative database classification (color-coded maps) of spectral domain optical coherence tomograph (SDOCT) in detecting wedge shaped retinal nerve fiber layer (RNFL) defects identified on photographs and the factors affecting the ability of SDOCT in detecting these RNFL defects.In a cross-sectional study, 238 eyes (476 RNFL quadrants) of 172 normal subjects and 85 eyes (103 RNFL quadrants with wedge shaped RNFL defects) of 66 glaucoma patients underwent RNFL imaging with SDOCT. Logistic regression models were used to evaluate the factors associated with false positive and false negative RNFL classifications of the color-coded maps of SDOCT.False positive classification at a p value of <5% was seen in 108 of 476 quadrants (22.8%). False negative classification at a p value of <5% was seen in 16 of 103 quadrants (15.5%). Of the 103 quadrants with RNFL defects, 64 showed a corresponding VF defect in the opposite hemisphere and 39 were preperimetric. Higher signal strength index (SSI) of the scan was less likely to have a false positive classification (odds ratio: 0.97, p = 0.01). Presence of an associated visual field defect (odds ratio: 0.17, p = 0.01) and inferior quadrant RNFL defects as compared to superior (odds ratio: 0.24, p = 0.04) were less likely to show false negative classifications.Scans with lower signal strengths were more likely to show false positive RNFL classifications, and preperimetric and superior quadrant RNFL defects were more likely to show false negative classifications on color-coded maps of SDOCT

Peripapillary retinal nerve fiber layer assessment of spectral domain optical coherence tomography and scanning laser polarimetry to diagnose preperimetric glaucoma.

To compare the abilities of peripapillary retinal nerve fiber layer (RNFL) parameters of spectral domain optical coherence tomograph (SDOCT) and scanning laser polarimeter (GDx enhanced corneal compensation; ECC) in detecting preperimetric glaucoma.In a cross-sectional study, 35 preperimetric glaucoma eyes (32 subjects) and 94 control eyes (74 subjects) underwent digital optic disc photography and RNFL imaging with SDOCT and GDx ECC. Ability of RNFL parameters of SDOCT and GDx ECC to discriminate preperimetric glaucoma eyes from control eyes was compared using area under receiver operating characteristic curves (AUC), sensitivities at fixed specificities and likelihood ratios (LR).AUC of the global average RNFL thickness of SDOCT (0.786) was significantly greater (p<0.001) than that of GDx ECC (0.627). Sensitivities at 95% specificity of the corresponding parameters were 20% and 8.6% respectively. AUCs of the inferior, superior and temporal quadrant RNFL thickness parameters of SDOCT were also significantly (p<0.05) greater than the respective RNFL parameters of GDx ECC. LRs of outside normal limits category of SDOCT parameters ranged between 3.3 and 4.0 while the same of GDx ECC parameters ranged between 1.2 and 2.1. LRs of within normal limits category of SDOCT parameters ranged between 0.4 and 0.7 while the same of GDx ECC parameters ranged between 0.7 and 1.0.Abilities of the RNFL parameters of SDOCT and GDx ECC to diagnose preperimetric glaucoma were only moderate. Diagnostic abilities of the RNFL parameters of SDOCT were significantly better than that of GDx ECC in preperimetric glaucoma