An Enhanced Table Driven Source Routing Protocol for Wireless Ad Hoc Networks

Analysis of MANETs led to the research on network layer. Different routing protocols were designed for numerous objectives and purposes. The way data packets are handled with in a multi-hop wireless network refers to Opportunistic data forwarding. During present research, we propose enhanced table-driven source routing protocol. This protocol maintains additional topology information which is different from Distance Vector (DV) routing protocol. The proposed approach will reduce overhead compared to the ancient Distance Vector based protocols. Base on the test results performed using Computer Simulator (Network Simulator 2) observed that the overhead in the proposed solution is just a fraction of the overhead of the standard proactive protocols. Performance of the current solution is better for transportation of higher information compared to existing proactive routing protocols

Comparative Analysis of Metaheuristic Approaches for Makespan Minimization for No Wait Flow Shop Scheduling Problem

This paper provides comparative analysis of various metaheuristic approaches for m-machine no wait flow shop scheduling (NWFSS) problem with makespan as an optimality criterion. NWFSS problem is NP hard and brute force method unable to find the solutions so approximate solutions are found with metaheuristic algorithms. The objective is to find out the scheduling sequence of jobs to minimize total completion time. In order to meet the objective criterion, existing metaheuristic techniques viz. Tabu Search (TS), Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are implemented for small and large sized problems and effectiveness of these techniques are measured with statistical metric

Android Security: A Survey of Issues, Malware Penetration, and Defenses

Smartphones have become pervasive due to the availability of office applications, Internet, games, vehicle guidance using location-based services apart from conventional services such as voice calls, SMSes, and multimedia services. Android devices have gained huge market share due to the open architecture of Android and the popularity of its application programming interface (APIs) in the developer community. Increased popularity of the Android devices and associated monetary benefits attracted the malware developers, resulting in big rise of the Android malware apps between 2010 and 2014. Academic researchers and commercial antimalware companies have realized that the conventional signature-based and static analysis methods are vulnerable. In particular, the prevalent stealth techniques, such as encryption, code transformation, and environment-aware approaches, are capable of generating variants of known malware. This has led to the use of behavior-, anomaly-, and dynamic-analysis-based methods. Since a single approach may be ineffective against the advanced techniques, multiple complementary approaches can be used in tandem for effective malware detection. The existing reviews extensively cover the smartphone OS security. However, we believe that the security of Android, with particular focus on malware growth, study of antianalysis techniques, and existing detection methodologies, needs an extensive coverage. In this survey, we discuss the Android security enforcement mechanisms, threats to the existing security enforcements and related issues, malware growth timeline between 2010 and 2014, and stealth techniques employed by the malware authors, in addition to the existing detection methods. This review gives an insight into the strengths and shortcomings of the known research methodologies and provides a platform, to the researchers and practitioners, toward proposing the next-generation Android security, analysis, and malware detection techniques

Integrative genome-wide association studies (GWAS) to understand complex genetic architecture of quantitative traits in chickpea

Development of high-yielding stress-tolerant chickpea cultivars is essential to enhance its yield potential and productivity amidst climate change scenario. Unfortunately, superior lines/recombinants producing higher pod and seed yield under stress are not available in world chickpea collection. Therefore, genetic dissection of complex stress tolerance and yield-contributing quantitative traits is the prime objective in current chickpea genomics and breeding research. Our study employed diverse GWAS-assisted integrated genomic strategies involving classical genetic inheritance analysis, QTL mapping, differential transcript profiling, molecular haplotyping and haplotype-based gene domestication/ evolution study for rapid quantitative dissection of complex yield and stress tolerance traits in chickpea. To accomplish this, multi-location/years replicated yield traits-related field phenotyping and high-throughput marker genotyping information generated from numerous natural germplasm accessions (association panel) and multiple intra- and inter-specific mapping populations of chickpea were deployed in the aforesaid combinatorial genomic approaches. These analyses delineated 12 novel alleles and six haplotypes from 10 transcription factor genes and 16 major QTLs/eQTLs governing yield and stress tolerance traits that were mapped on 10 ultra-high density chickpea genetic linkage maps. The superior natural alleles/haplotypes of two major genes (QTLs) regulating seed weight and pod/seed number identified from cultivated and wild Cicer gene pools are being introduced into multiple high-yielding Indian varieties of chickpea for its marker-assisted genetic improvement. The potential molecular signatures delineated using integrated genomics- assisted breeding strategies have functional significance to understand the molecular genetic mechanism and natural allelic diversity-led domestication pattern underlying these complex quantitative traits at a genome-wide scale, leading to fast-paced translational genomics for chickpea genetic enhancement. These essential outcomes will be useful for devising the most efficient strategies to produce high-yielding climate-resilient chickpea cultivars for sustaining global food security

Deploying QTL-seq for rapid delineation of a potential candidate gene underlying major trait-associated QTL in chickpea

A rapid high-resolution genome-wide strategy for molecular mapping of major QTL(s)/gene(s) regulating important agronomic traits is vital for in-depth dissection of complex quantitative traits and genetic enhancement in chickpea. The present study for the first time employed a NGS-based whole-genomeQTL-seq strategy to identify one major genomic region harbouring a robust 100- seed weight QT Lusinganintra-specific 221 chickpea mapping population (desicv.ICC7184×desicv.ICC 15061). The QTL-seq-derived major SW QTL (CaqSW1.1) was further validated by single-nucleotide polymorphism (SNP) and simple sequence repeat (SSR) marker-based traditional QTL mapping (47.6% R2 at higher LOD >19). This reflects the reliability and efficacy of QTL-seq as a strategy for rapid genome-wide scanning and fine mapping of major trait regulatory QTLs in chickpea. The use of QTL-seq and classical QTL mapping in combination narrowed down the 1.37 Mb (comprising 177genes) major SWQTL (CaqSW1.1) regionintoa 35 kb genomic intervalondesi chickpea chromosome 1 containing six genes. One coding SNP (G/A)-carrying constitutive photomorphogenic 9 (COP9) signalo some complex subunit (CSN8) gene of the see xhibited seed-specific expression, including pronounced differential up-/down-regulation in low and high seed weight mapping parents and homo zygous individuals duringseed development.The coding SNP mined in this potential seed weight- governing candidate CSN8 genewas found to be present exclusively in all cultivated species/ genotypes, but notin any wild species/genotypes of primary, secondary and tertiary gene pools.This indicates the effect of strong artificial and/or natural selection pressure on target SW locus during chickpea domestication. The proposed QTL-seq-driven integrated genome-wide strategy has potential to delineate major candidate gene(s) harbouring a robust trait regulatory QTL rapidly with optimal use of resources. This will further assist us to extrapolate the molecular mechanism underlying complex quantitative traits at a genome-wide scale leading to fast-paced marker-assisted genetic improvement in diverse crop plants, including chickpea

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin