33 research outputs found

    Single Mode Lamb Wave Inspection of Composite Laminates

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    Flaw detection in composite plates presents a very difficult problem. Conventional echoscopic techniques are not feasible because the back-scattered signal from a possible defect is usually overshadowed by much stronger reflections from the walls of the thin plate and by additional scattering from inherent inhomogeneities such as imbedded fibers and alternating plies. Single or double transmission attenuation measurements offer a convenient, but rather insensitive alternative. Fig. 1 shows the schematic diagrams of the conventional normal incidence and the oblique incidence so-called Lamb wave inspection techniques. At normal incidence, we can use a focused transducer of very good lateral resolution, but the sensitivity might be rather low when the defect exhibits a very small scattering cross-section from this particular direction of interrogation. This occurs, for instance, in the case of weak porosity when the defects tend to be concentrated in a thin layer parallel with the plies, or as is shown in Fig. 1, in the case of transverse cracks. In such cases, oblique incidence inspection can be expected to give better sensitivity since Lamb modes propagating parallel to the plate are more attenuated. At the same time, the lateral resolution will be inherently lower, therefore the ultrasonic contrast must be carefully optimized on a case-by-case basis

    Machine learning and structural analysis of Mycobacterium tuberculosis pan-genome identifies genetic signatures of antibiotic resistance.

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    Mycobacterium tuberculosis is a serious human pathogen threat exhibiting complex evolution of antimicrobial resistance (AMR). Accordingly, the many publicly available datasets describing its AMR characteristics demand disparate data-type analyses. Here, we develop a reference strain-agnostic computational platform that uses machine learning approaches, complemented by both genetic interaction analysis and 3D structural mutation-mapping, to identify signatures of AMR evolution to 13 antibiotics. This platform is applied to 1595 sequenced strains to yield four key results. First, a pan-genome analysis shows that M. tuberculosis is highly conserved with sequenced variation concentrated in PE/PPE/PGRS genes. Second, the platform corroborates 33 genes known to confer resistance and identifies 24 new genetic signatures of AMR. Third, 97 epistatic interactions across 10 resistance classes are revealed. Fourth, detailed structural analysis of these genes yields mechanistic bases for their selection. The platform can be used to study other human pathogens

    Machine learning applied to enzyme turnover numbers reveals protein structural correlates and improves metabolic models.

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    Knowing the catalytic turnover numbers of enzymes is essential for understanding the growth rate, proteome composition, and physiology of organisms, but experimental data on enzyme turnover numbers is sparse and noisy. Here, we demonstrate that machine learning can successfully predict catalytic turnover numbers in Escherichia coli based on integrated data on enzyme biochemistry, protein structure, and network context. We identify a diverse set of features that are consistently predictive for both in vivo and in vitro enzyme turnover rates, revealing novel protein structural correlates of catalytic turnover. We use our predictions to parameterize two mechanistic genome-scale modelling frameworks for proteome-limited metabolism, leading to significantly higher accuracy in the prediction of quantitative proteome data than previous approaches. The presented machine learning models thus provide a valuable tool for understanding metabolism and the proteome at the genome scale, and elucidate structural, biochemical, and network properties that underlie enzyme kinetics

    Advancing Eucalyptus genomics: identification and sequencing of lignin biosynthesis genes from deep-coverage BAC libraries

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    <p>Abstract</p> <p>Background</p> <p><it>Eucalyptus </it>species are among the most planted hardwoods in the world because of their rapid growth, adaptability and valuable wood properties. The development and integration of genomic resources into breeding practice will be increasingly important in the decades to come. Bacterial artificial chromosome (BAC) libraries are key genomic tools that enable positional cloning of important traits, synteny evaluation, and the development of genome framework physical maps for genetic linkage and genome sequencing.</p> <p>Results</p> <p>We describe the construction and characterization of two deep-coverage BAC libraries EG_Ba and EG_Bb obtained from nuclear DNA fragments of <it>E. grandis </it>(clone BRASUZ1) digested with <it>Hind</it>III and <it>BstY</it>I, respectively. Genome coverages of 17 and 15 haploid genome equivalents were estimated for EG_Ba and EG_Bb, respectively. Both libraries contained large inserts, with average sizes ranging from 135 Kb (Eg_Bb) to 157 Kb (Eg_Ba), very low extra-nuclear genome contamination providing a probability of finding a single copy gene ≥ 99.99%. Libraries were screened for the presence of several genes of interest <it>via </it>hybridizations to high-density BAC filters followed by PCR validation. Five selected BAC clones were sequenced and assembled using the Roche GS FLX technology providing the whole sequence of the <it>E. grandis </it>chloroplast genome, and complete genomic sequences of important lignin biosynthesis genes.</p> <p>Conclusions</p> <p>The two <it>E. grandis </it>BAC libraries described in this study represent an important milestone for the advancement of <it>Eucalyptus </it>genomics and forest tree research. These BAC resources have a highly redundant genome coverage (> 15×), contain large average inserts and have a very low percentage of clones with organellar DNA or empty vectors. These publicly available BAC libraries are thus suitable for a broad range of applications in genetic and genomic research in <it>Eucalyptus </it>and possibly in related species of <it>Myrtaceae</it>, including genome sequencing, gene isolation, functional and comparative genomics. Because they have been constructed using the same tree (<it>E. grandis </it>BRASUZ1) whose full genome is being sequenced, they should prove instrumental for assembly and gap filling of the upcoming <it>Eucalyptus </it>reference genome sequence.</p

    Transition, Integration and Convergence. The Case of Romania

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    Single Mode Lamb Wave Inspection of Composite Laminates

    Get PDF
    Flaw detection in composite plates presents a very difficult problem. Conventional echoscopic techniques are not feasible because the back-scattered signal from a possible defect is usually overshadowed by much stronger reflections from the walls of the thin plate and by additional scattering from inherent inhomogeneities such as imbedded fibers and alternating plies. Single or double transmission attenuation measurements offer a convenient, but rather insensitive alternative. Fig. 1 shows the schematic diagrams of the conventional normal incidence and the oblique incidence so-called Lamb wave inspection techniques. At normal incidence, we can use a focused transducer of very good lateral resolution, but the sensitivity might be rather low when the defect exhibits a very small scattering cross-section from this particular direction of interrogation. This occurs, for instance, in the case of weak porosity when the defects tend to be concentrated in a thin layer parallel with the plies, or as is shown in Fig. 1, in the case of transverse cracks. In such cases, oblique incidence inspection can be expected to give better sensitivity since Lamb modes propagating parallel to the plate are more attenuated. At the same time, the lateral resolution will be inherently lower, therefore the ultrasonic contrast must be carefully optimized on a case-by-case basis.</p
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