A Study on Deep CNN Structures for Defect Detection From Laser Ultrasonic Visualization Testing Images

The importance of ultrasonic nondestructive testing has been increasing in recent years, and there are high expectations for the potential of laser ultrasonic visualization testing, which combines laser ultrasonic testing with scattered wave visualization technology. Even if scattered waves are visualized, inspectors still need to carefully inspect the images. To automate this, this paper proposes a deep neural network for automatic defect detection and localization in LUVT images. To explore the structure of a neural network suitable to this task, we compared the LUVT image analysis problem with the generic object detection problem. Numerical experiments using real-world data from a SUS304 flat plate showed that the proposed method is more effective than the general object detection model in terms of prediction performance. We also show that the computational time required for prediction is faster than that of the general object detection model

Simulation-Aided Deep Learning for Laser Ultrasonic Visualization Testing

In recent years, laser ultrasonic visualization testing (LUVT) has attracted much attention because of its ability to efficiently perform non-contact ultrasonic non-destructive testing.Despite many success reports of deep learning based image analysis for widespread areas, attempts to apply deep learning to defect detection in LUVT images face the difficulty of preparing a large dataset of LUVT images that is too expensive to scale. To compensate for the scarcity of such training data, we propose a data augmentation method that generates artificial LUVT images by simulation and applies a style transfer to simulated LUVT images.The experimental results showed that the effectiveness of data augmentation based on the style-transformed simulated images improved the prediction performance of defects, rather than directly using the raw simulated images for data augmentation

Stress relaxation above and below the jamming transition

We numerically investigate stress relaxation in soft athermal disks to reveal critical slowing down when the system approaches the jamming point. The exponents describing the divergence of the relaxation time differ dramatically depending on whether the transition is approached from the jammed or unjammed phase. This contrasts sharply with conventional dynamic critical scaling scenarios, where a single exponent characterizes both sides. We explain this surprising difference in terms of the vibrational density of states (vDOS), which is a key ingredient of linear viscoelastic theory. The vDOS exhibits an extra slow mode that emerges below jamming, which we utilize to demonstrate the anomalous exponent below jamming.Comment: 5 pages, 4 figure

Rippled-pattern sebaceoma : A report of a lesion on the back with a review of the literature

A 68-year-old Japanese man presented with a nodule that had been present for 5 to 6 years on the right side of the back. Physical examination revealed a dome-shaped, 12 X 13-mm, dark red nodule. It was excised with a 2 to 3-mm margin. The patient remained free of disease during 77 months of follow-up. Microscopic examination revealed a bulb-like tumor in the dermis, contiguous with the overlying epidermis. It was composed of small, monomorphous, cigar-shaped basaloid cells in linear, parallel rows, resembling the palisading of nuclei of Verocay bodies, and presenting a rippled-pattern. There were scattered cells showing sebaceous differentiation with vacuolated cytoplasm and scalloped nuclei. There were tiny, duct-like spaces. The tumor revealed characteristics of rippled-pattem sebaceoma. The present case is the first reported rippled-pattern sebaceous neoplasm on the back. Many spindle cell tumors, such as basal cell carcinoma, pleomorphic adenoma, dermatofibrosarcoma protuberans, myofibroblastoma, and leiomyoblastoma, in addition to trichoblastoma and sebaceoma, can have a rippled-pattern

Quantum Circuit Distillation and Compression

Quantum coherence in a qubit is vulnerable to environmental noise. When long quantum calculation is run on a quantum processor without error correction, the noise often causes fatal errors and messes up the calculation. Here, we propose quantum-circuit distillation to generate quantum circuits that are short but have enough functions to produce an output almost identical to that of the original circuits. The distilled circuits are less sensitive to the noise and can complete calculation before the quantum coherence is broken in the qubits. We created a quantum-circuit distillator by building a reinforcement learning model, and applied it to the inverse quantum Fourier transform (IQFT) and Shor's quantum prime factorization. The obtained distilled circuit allows correct calculation on IBM-Quantum processors. By working with the quantum-circuit distillator, we also found a general rule to generate quantum circuits approximating the general $n$-qubit IQFTs. The quantum-circuit distillator offers a new approach to improve performance of noisy quantum processors.Comment: 11 pages, 8 figures, 1 tabl

Radial Bargmann representation for the Fock space of type B

Let $\nu_{\alpha,q}$ be the probability and orthogonality measure for the $q$-Meixner-Pollaczek orthogonal polynomials, which has appeared in \cite{BEH15} as the distribution of the $(\alpha,q)$-Gaussian process (the Gaussian process of type B) over the $(\alpha,q)$-Fock space (the Fock space of type B). The main purpose of this paper is to find the radial Bargmann representation of $\nu_{\alpha,q}$. Our main results cover not only the representation of $q$-Gaussian distribution by \cite{LM95}, but also of $q^2$-Gaussian and symmetric free Meixner distributions on $\mathbb R$. In addition, non-trivial commutation relations satisfied by $(\alpha,q)$-operators are presented.Comment: 13 pages, minor changes have been mad

A Three-Dimensional FRET Analysis to Construct an Atomic Model of the Actin–Tropomyosin–Troponin Core Domain Complex on a Muscle Thin Filament

It is essential to knowthe detailed structure of the thin filament to understand the regulation mechanism of striated muscle contraction. Fluorescence resonance energy transfer (FRET) was used to construct an atomic model of the actin–tropomyosin (Tm)–troponin (Tn) core domain complex. We generated single-cysteine mutants in the 167–195 region of Tm and in TnC, TnI, and the β-TnT 25-kDa fragment, and each was attached with an energy donor probe. An energy acceptor probe was located at actin Gln41, actin Cys374, or the actin nucleotide-binding site. From these donor–acceptor pairs, FRET efficiencies were determined with and without Ca2+. Using the atomic coordinates for F-actin, Tm, and the Tn core domain, we searched all possible arrangements for Tm or the Tn core domain on F-actin to calculate the FRET efficiency for each donor–acceptor pair in each arrangement. By minimizing the squared sum of deviations for the calculated FRET efficiencies from the observed FRET efficiencies, we determined the location of Tm segment 167– 195 and the Tn core domain on F-actin with andwithout Ca2+. The bulk of the Tn core domain is located near actin subdomains 3 and 4. The central helix of TnC is nearly perpendicular to the F-actin axis, directing the N-terminal domain of TnC toward the actin outer domain. The C-terminal region in the I–T arm forms a four-helix-bundle structure with the Tm 175–185 region. After Ca2+ release, the Tn core domainmoves toward the actin outer domain and closer to the center of the F-actin axis

Tuberous sclerosis complex tumor suppressor–mediated S6 kinase inhibition by phosphatidylinositide-3-OH kinase is mTOR independent

The evolution of mitogenic pathways has led to the parallel requirement for negative control mechanisms, which prevent aberrant growth and the development of cancer. Principally, such negative control mechanisms are represented by tumor suppressor genes, which normally act to constrain cell proliferation (Macleod, K. 2000. Curr. Opin. Genet. Dev. 10:81–93). Tuberous sclerosis complex (TSC) is an autosomal-dominant genetic disorder, characterized by mutations in either TSC1 or TSC2, whose gene products hamartin (TSC1) and tuberin (TSC2) constitute a putative tumor suppressor complex (TSC1-2; van Slegtenhorst, M., M. Nellist, B. Nagelkerken, J. Cheadle, R. Snell, A. van den Ouweland, A. Reuser, J. Sampson, D. Halley, and P. van der Sluijs. 1998. Hum. Mol. Genet. 7:1053–1057). Little is known with regard to the oncogenic target of TSC1-2, however recent genetic studies in Drosophila have shown that S6 kinase (S6K) is epistatically dominant to TSC1-2 (Tapon, N., N. Ito, B.J. Dickson, J.E. Treisman, and I.K. Hariharan. 2001. Cell. 105:345–355; Potter, C.J., H. Huang, and T. Xu. 2001. Cell. 105:357–368). Here we show that loss of TSC2 function in mammalian cells leads to constitutive S6K1 activation, whereas ectopic expression of TSC1-2 blocks this response. Although activation of wild-type S6K1 and cell proliferation in TSC2-deficient cells is dependent on the mammalian target of rapamycin (mTOR), by using an S6K1 variant (GST-ΔC-S6K1), which is uncoupled from mTOR signaling, we demonstrate that TSC1-2 does not inhibit S6K1 via mTOR. Instead, we show by using wortmannin and dominant interfering alleles of phosphatidylinositide-3-OH kinase (PI3K) that increased S6K1 activation is contingent upon the suppression of TSC2 function by PI3K in normal cells and is PI3K independent in TSC2-deficient cells