116 research outputs found

    Numerical performances of low rank stap based on different heterogeneous clutter subspace estimators

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    International audienceSpace time Adaptive Processing (STAP) for airborne RADAR fits the context of a disturbance composed of a Low Rank (LR) clutter, here modeled by a Compound Gaussian (CG) process, plus a white Gaussian noise (WGN). In such context, the corresponding LR adaptive filters used to detect a target require less training vectors than classical methods to reach equivalent performance. Unlike the classical filter which is based on the Covariance Matrix (CM) of the noise, the LR filter is based on the clutter subspace projector, which is usually derived from a Singular Value Decomposition (SVD) of a noise CM estimate. Regarding to the considered model of LR-CG plus WGN, recent results are providing both direct estimators of the clutter subspace [1][2] and an exact MLE of the noise CM [3]. To promote the use of these new estimation methods, this paper proposes to apply them to realistic STAP simulations

    Robust Adaptive Detection of Buried Pipes using GPR

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    International audienceDetection of buried objects such as pipes using a Ground Penetrating Radar (GPR) is intricate for three main reasons. First, noise is important in the resulting image because of the presence of several rocks and/or layers in the ground, highly influencing the Probability of False Alarm (PFA) level. Also, wave speed and object responses are unknown in the ground and depend on the relative permit-tivity, which is not directly measurable. Finally, the depth of the pipes leads to strong attenuation of the echoed signal, leading to poor SNR scenarios. In this paper, we propose a detection method: (1) enhancing the signal of interest while reducing the noise and layer contributions, and (2) giving a local estimate of the relative permittivity. We derive an adaptive detector where the signal of interest is parametrised by the wave speed in the ground. For this detector, noise is assumed to follow a Spherically Invariant Random Vector (SIRV) distribution in order to obtain a robust detection. We use robust maximum likelihood-type covariance matrix estimators called M-estimators. To handle the significant amount of data, we consider regularised versions of said estimators. Simulation will allow to estimate the relation PFA-Threshold. Comparison is performed with standard GPR processing methods, showing the aptitude of the method in detecting pipes having low response levels with a reasonable PFA

    Application de l'algorithme Principal Component Inverse 3D pour la détection de mines enfouies

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    - Cet article s'intéresse à la réduction de fausses alarmes dans le cadre de la détection de mines sous marines enfouies. Nous proposons d'utiliser un algorithme algèbrique. le Principal Component Inverse 3D, pour réduire l'influence de la réverbération et séparer les échos de mines entre eux. Cette méthode est testée sur des données réelles fournies par le GESMA et les résultats sont comparés à ceux donnés par des algorithmes algébriques 2D

    Fragmentation of Contaminant and Endogenous DNA in Ancient Samples Determined by Shotgun Sequencing; Prospects for Human Palaeogenomics

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    Despite the successful retrieval of genomes from past remains, the prospects for human palaeogenomics remain unclear because of the difficulty of distinguishing contaminant from endogenous DNA sequences. Previous sequence data generated on high-throughput sequencing platforms indicate that fragmentation of ancient DNA sequences is a characteristic trait primarily arising due to depurination processes that create abasic sites leading to DNA breaks

    Early Pleistocene enamel proteome from Dmanisi resolves Stephanorhinus phylogeny

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    The sequencing of ancient DNA has enabled the reconstruction of speciation, migration and admixture events for extinct taxa. However, the irreversible post-mortem degradation2 of ancient DNA has so far limited its recovery—outside permafrost areas—to specimens that are not older than approximately 0.5 million years (Myr). By contrast, tandem mass spectrometry has enabled the sequencing of approximately 1.5-Myr-old collagen type I, and suggested the presence of protein residues in fossils of the Cretaceous period—although with limited phylogenetic use. In the absence of molecular evidence, the speciation of several extinct species of the Early and Middle Pleistocene epoch remains contentious. Here we address the phylogenetic relationships of the Eurasian Rhinocerotidae of the Pleistocene epoch, using the proteome of dental enamel from a Stephanorhinus tooth that is approximately 1.77-Myr old, recovered from the archaeological site of Dmanisi (South Caucasus, Georgia). Molecular phylogenetic analyses place this Stephanorhinus as a sister group to the clade formed by the woolly rhinoceros (Coelodonta antiquitatis) and Merck’s rhinoceros (Stephanorhinus kirchbergensis). We show that Coelodonta evolved from an early Stephanorhinus lineage, and that this latter genus includes at least two distinct evolutionary lines. The genus Stephanorhinus is therefore currently paraphyletic, and its systematic revision is needed. We demonstrate that sequencing the proteome of Early Pleistocene dental enamel overcomes the limitations of phylogenetic inference based on ancient collagen or DNA. Our approach also provides additional information about the sex and taxonomic assignment of other specimens from Dmanisi. Our findings reveal that proteomic investigation of ancient dental enamel—which is the hardest tissue in vertebrates, and is highly abundant in the fossil record—can push the reconstruction of molecular evolution further back into the Early Pleistocene epoch, beyond the currently known limits of ancient DNA preservation

    Linking species concepts to natural product discovery in the post-genomic era

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    A widely accepted species concept for bacteria has yet to be established. As a result, species designations are inconsistently applied and tied to what can be considered arbitrary metrics. Increasing access to DNA sequence data and clear evidence that bacterial genomes are dynamic entities that include large numbers of horizontally acquired genes have added a new level of insight to the ongoing species concept debate. Despite uncertainties over how to apply species concepts to bacteria, there is clear evidence that sequence-based approaches can be used to resolve cohesive groups that maintain the properties of species. This cohesion is clearly evidenced in the genus Salinispora, where three species have been discerned despite very close relationships based on 16S rRNA sequence analysis. The major phenotypic differences among the three species are associated with secondary metabolite production, which occurs in species-specific patterns. These patterns are maintained on a global basis and provide evidence that secondary metabolites have important ecological functions. These patterns also suggest that an effective strategy for natural product discovery is to target the cultivation of new Salinispora taxa. Alternatively, bioinformatic analyses of biosynthetic genes provide opportunities to predict secondary metabolite novelty and reduce the redundant isolation of well-known metabolites. Although much remains to be learned about the evolutionary relationships among bacteria and how fundamental units of diversity can be resolved, genus and species descriptions remain the most effective method of scientific communication

    The efficacy of high-throughput sequencing and target enrichment on charred archaeobotanical remains

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    The majority of archaeological plant material is preserved in a charred state. Obtaining reliable ancient DNA data from these remains has presented challenges due to high rates of nucleotide damage, short DNA fragment lengths, low endogenous DNA content and the potential for modern contamination. It has been suggested that high-throughput sequencing (HTS) technologies coupled with DNA enrichment techniques may overcome some of these limitations. Here we report the findings of HTS and target enrichment on four important archaeological crops (barley, grape, maize and rice) performed in three different laboratories, presenting the largest HTS assessment of charred archaeobotanical specimens to date. Rigorous analysis of our data-excluding false-positives due to background contamination or incorrect index assignments-indicated a lack of endogenous DNA in nearly all samples, except for one lightly-charred maize cob. Even with target enrichment, this sample failed to yield adequate data required to address fundamental questions in archaeology and biology. We further reanalysed part of an existing dataset on charred plant material, and found all purported endogenous DNA sequences were likely to be spurious. We suggest these technologies are not suitable for use with charred archaeobotanicals and urge great caution when interpreting data obtained by HTS of these remains

    Ancient DNA analysis suggests negligible impact of the Wari Empire expansion in Peru's Central Coast during the Middle Horizon

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    The analysis of ancient human DNA from South America allows the exploration of pre-Columbian population history through time and to directly test hypotheses about cultural and demographic evolution. The Middle Horizon (650-1100 AD) represents a major transitional period in the Central Andes, which is associated with the development and expansion of ancient Andean empires such as Wari and Tiwanaku. These empires facilitated a series of interregional interactions and socio-political changes, which likely played an important role in shaping the region's demographic and cultural profiles. We analyzed individuals from three successive pre-Columbian cultures present at the Huaca Pucllana archaeological site in Lima, Peru: Lima (Early Intermediate Period, 500-700 AD), Wari (Middle Horizon, 800-1000 AD) and Ychsma (Late Intermediate Period, 1000-1450 AD). We sequenced 34 complete mitochondrial genomes to investigate the potential genetic impact of the Wari Empire in the Central Coast of Peru. The results indicate that genetic diversity shifted only slightly through time, ruling out a complete population discontinuity or replacement driven by the Wari imperialist hegemony, at least in the region around present-day Lima. However, we caution that the very subtle genetic contribution of Wari imperialism at the particular Huaca Pucllana archaeological site might not be representative for the entire Wari territory in the Peruvian Central Coast.Guido Valverde, María Inés Barreto Romero, Isabel Flores Espinoza, Alan Cooper, Lars Fehren-Schmitz, Bastien Llamas, Wolfgang Haa

    The Natural Product Domain Seeker NaPDoS: A Phylogeny Based Bioinformatic Tool to Classify Secondary Metabolite Gene Diversity

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    New bioinformatic tools are needed to analyze the growing volume of DNA sequence data. This is especially true in the case of secondary metabolite biosynthesis, where the highly repetitive nature of the associated genes creates major challenges for accurate sequence assembly and analysis. Here we introduce the web tool Natural Product Domain Seeker (NaPDoS), which provides an automated method to assess the secondary metabolite biosynthetic gene diversity and novelty of strains or environments. NaPDoS analyses are based on the phylogenetic relationships of sequence tags derived from polyketide synthase (PKS) and non-ribosomal peptide synthetase (NRPS) genes, respectively. The sequence tags correspond to PKS-derived ketosynthase domains and NRPS-derived condensation domains and are compared to an internal database of experimentally characterized biosynthetic genes. NaPDoS provides a rapid mechanism to extract and classify ketosynthase and condensation domains from PCR products, genomes, and metagenomic datasets. Close database matches provide a mechanism to infer the generalized structures of secondary metabolites while new phylogenetic lineages provide targets for the discovery of new enzyme architectures or mechanisms of secondary metabolite assembly. Here we outline the main features of NaPDoS and test it on four draft genome sequences and two metagenomic datasets. The results provide a rapid method to assess secondary metabolite biosynthetic gene diversity and richness in organisms or environments and a mechanism to identify genes that may be associated with uncharacterized biochemistry
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