A frequency-domain full waveform inversion method of elastic waves in quantitative defection investigation

857-866Full waveform inversion is a challenging data-fitting procedure based on full wave field modeling to extract quantitative information on elastic properties of subsurface structures. We developed a frequency-domain full-waveform inversion method of elastic waves for stratified media, adopting a quasi-linearization method coupled with a random search algorithm. The inversion process of this method is irrelevant to hypocenter function and can be considered as a kind of combination between the heuristic and non-heuristic inversion methods. To verify our method, we apply it to three numerical two-dimensional models with different intermediate structures (dipping, arched and hollow), and their structures are well revealed. With some pretreatments on response waveforms, such as filtering, normalization and correlation analysis, the full-waveform inversion method is extended to models with damaged area and its feasibility and accuracy verified. Alignment of full waveform inversion method and its cost of computing, several strategies exist to treat this quantitative detecting problem. In Chengdu-Chongqing guest emergency project, the application of full waveform inversion method saves a lot of time. In this method, each section only needs 2 detectors and only need to be hammered twice, while the traditional CT (Computed Tomography) test requires 11 detection filters and at least 11 hammering, and each section has 121 waveform data. In some cases, we can obtain some important priori information through field investigation. The priori information can be used to accelerate the inversion process

Gene Expression Profile of <i>Bombyx mori</i> Hemocyte under the Stress of Destruxin A

<div><p>Destruxin A (DA) is a cyclo-peptidic mycotoxin from the entomopathogenic fungus <i>Metarhizium anisopliae</i>. To uncover potential genes associated with its molecular mechanisms, a digital gene expression (DGE) profiling analysis was used to compare differentially expressed genes in the hemocytes of silkworm larvae treated with DA. Ten DGE libraries were constructed, sequenced, and assembled, and the unigenes with least 2.0-fold difference were further analyzed. The numbers of up-regulated genes were 10, 20, 18, 74 and 8, as well as the numbers of down-regulated genes were 0, 1, 8, 13 and 3 at 1, 4, 8, 12 and 24 h post treatment, respectively. Totally, the expression of 132 genes were significantly changed, among them, 1, 3 and 12 genes were continually up-regulated at 4, 3 and 2 different time points, respectively, while 1 gene was either up or down-regulated continually at 2 different time points. Furthermore, 68 genes were assigned to one or multiple gene ontology (GO) terms and 89 genes were assigned to specific Kyoto Encyclopedia of Genes and Genomes (KEGG) Orthology. In-depth analysis identified that these genes putatively involved in insecticide resistance, cell apoptosis, and innate immune defense. Finally, twenty differentially expressed genes were randomly chosen and validated by quantitative real-time PCR (qRT-PCR). Our studies provide insights into the toxic effect of this microbial insecticide on silkworm's hemocytes, and are helpful to better understanding of the molecular mechanisms of DA as a biological insecticide.</p></div

Quantitative Real Time PCR (qRT-PCR) validation of DGE result.

a<p>means significant difference existed between the DA treated and control samples.</p>b<p>means no significant difference.</p><p>DGE data were generated from two biological repeats. qPCR data were generated by the standard deviation from three biological repeats.</p

NCBI SRA accession numbers for the treatments at each time point.

<p>NCBI SRA accession numbers for the treatments at each time point.</p

Summarizing of Gene Ontology functional classification of ten DGEs by comparing DA-treated and un-treated samples in differential time intervals, which described gene products in terms of their associated biological processes, cellular components and molecular functions.

<p>Summarizing of Gene Ontology functional classification of ten DGEs by comparing DA-treated and un-treated samples in differential time intervals, which described gene products in terms of their associated biological processes, cellular components and molecular functions.</p

Quality assessment of reads in each library.

<p>Quality assessment of reads in each library.</p

Screening of more than 2-fold differentially expressed genes in <i>B.mori</i> hemocytes after the treatment of DA in differential time intervals.

<p>Screening of more than 2-fold differentially expressed genes in <i>B.mori</i> hemocytes after the treatment of DA in differential time intervals.</p