795 research outputs found

    Single-realization recovery of a random Schr\"odinger equation with unknown source and potential

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    In this paper, we study an inverse scattering problem associated with the stationary Schr\"odinger equation where both the potential and the source terms are unknown. The source term is assumed to be a generalised Gaussian random distribution of the microlocally isotropic type, whereas the potential function is assumed to be deterministic. The well-posedness of the forward scattering problem is first established in a proper sense. It is then proved that the rough strength of the random source can be uniquely recovered, independent of the unknown potential, by a single realisation of the passive scattering measurement. We develop novel techniques to completely remove a restrictive geometric condition in our earlier study [25], at an unobjectionable cost of requiring the unknown potential to be deterministic. The ergodicity is used to establish the single realization recovery, and the asymptotic arguments in our analysis are based on techniques from the theory of pseudo-differential operators and the stationary phase principle.Comment: 28 page

    Microsatellite Markers in the Mud Crab (Scylla paramamosain) and their Application in Population Genetics and Marker- Assisted Selection

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    The mud crab (Scylla paramamosain) is a commercially important species for aquaculture and fisheries in China. In this study, a total of 302 polymorphic microsatellite markers have been isolated and characterized. The observed and expected heterozygosity ranged from 0.04 to 1.00 and from 0.04 to 0.96 per locus. The wild populations distributed along South-eastern China coasts showed high genetic diversity (HO ranged from 0.62 to 0.77) and low genetic differentiation (FST = 0.018). Meanwhile, a significant association (r2 = 0.11) was identified between genetic and geographic distance of 11 locations. Furthermore, a PCR-based parentage assignment method was successfully developed using seven polymorphic microsatellite loci that could correctly assign 95% of the progeny to their parents. Moreover, three polymorphic microsatellite loci were identified to be significantly associated with 12 growth traits of S. paramamosain, and four genotypes were considered to be great potential for marker-assisted selection. Finally, a first preliminary genetic linkage map with 65 linkage groups and 212 molecular markers was constructed using microsatellite and AFLP markers for S. paramamosain. This map was 2746 cM in length, and covered approximately 50% of the estimated genome. This study provides novel insights into genome biology and molecular marker-assisted selection for S. paramamosain

    Exact Transcript Quantification Over Splice Graphs

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    The probability of sequencing a set of RNA-seq reads can be directly modeled using the abundances of splice junctions in splice graphs instead of the abundances of a list of transcripts. We call this model graph quantification, which was first proposed by Bernard et al. (2014). The model can be viewed as a generalization of transcript expression quantification where every full path in the splice graph is a possible transcript. However, the previous graph quantification model assumes the length of single-end reads or paired-end fragments is fixed. We provide an improvement of this model to handle variable-length reads or fragments and incorporate bias correction. We prove that our model is equivalent to running a transcript quantifier with exactly the set of all compatible transcripts. The key to our method is constructing an extension of the splice graph based on Aho-Corasick automata. The proof of equivalence is based on a novel reparameterization of the read generation model of a state-of-art transcript quantification method. This new approach is useful for modeling scenarios where reference transcriptome is incomplete or not available and can be further used in transcriptome assembly or alternative splicing analysis

    A Penalized Multi-trait Mixed Model for Association Mapping in Pedigree-based GWAS

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    In genome-wide association studies (GWAS), penalization is an important approach for identifying genetic markers associated with trait while mixed model is successful in accounting for a complicated dependence structure among samples. Therefore, penalized linear mixed model is a tool that combines the advantages of penalization approach and linear mixed model. In this study, a GWAS with multiple highly correlated traits is analyzed. For GWAS with multiple quantitative traits that are highly correlated, the analysis using traits marginally inevitably lose some essential information among multiple traits. We propose a penalized-MTMM, a penalized multivariate linear mixed model that allows both the within-trait and between-trait variance components simultaneously for multiple traits. The proposed penalized-MTMM estimates variance components using an AI-REML method and conducts variable selection and point estimation simultaneously using group MCP and sparse group MCP. Best linear unbiased predictor (BLUP) is used to find predictive values and the Pearson's correlations between predictive values and their corresponding observations are used to evaluate prediction performance. Both prediction and selection performance of the proposed approach and its comparison with the uni-trait penalized-LMM are evaluated through simulation studies. We apply the proposed approach to a GWAS data from Genetic Analysis Workshop (GAW) 18

    Links Assignment Scheme based on Potential Edges Importance in Dual-layer Wavelength Routing Optical Satellite Networks

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    With the development of the massive satellite constellation and the on-orbit laser-based communication equipment, the wavelength routing optical satellite network (WROSN) becomes a potential solution for on-orbit, high-capacity, and high-speed communication. Since the inter-satellite links (ISLs) are time-varying, one of the fundamental considerations in the construction of the WROSN is assigning limited laser communication terminals for each satellite to establish ISLs with the visible satellites. Therefore, we propose a links assignment scheme (LAS) based on the potential edges importance matrix (PEIM) algorithm to construct a temporarily stable topology of the ISLs for a dual-layer constellation. The simulation results showed that the LAS based on the PEIM algorithm is better than LAS based on the random or Greedy algorithm in terms of node-to-node distance, node pair connectivity, wavelength demand, and transmission delay. The node pair connectivity and wavelength demand in WROSN is a trade-off problem. The research in this paper also brings a novel method for reduction of the cost of the on-board resources, that is through designing topology of the ISLs with links assignment algorithm.Comment: This is the manuscript version that was submitted to the International Journal of Satellite Communications and Networking (SAT-23-0018
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