Nondestructive Testing System to Assess Lack-Of-Bond in Brazed Generator Coils by Ultrasonic Retro-Reflection

Margetan et al. investigated the problem of assessing the integrity of diffusion bonds using reflected ultrasound at oblique incidence [1,2]. They presented a quasi-static distributed spring model to derive the ultrasonic reflectivity of an imperfectly-bonded interface as a function of frequency and angle of incidence. The results were then incorporated in a model for the corner reflection from a diffusion-bonded joint between two butting plates. Rose also studied the ultrasonic reflectivity of diffusion bonds and utilized it for quantitatively characterizing defective joints [3, 4]. Angel and Achenbach investigated the reflection of ultrasonic waves by an array of microcracks [5]

A Generalized Model of the Effects of Microstructure on Ultrasonic Backscattering and Flaw Detection

The influence of microstructure on ultrasonic inspection is well known. Familiar examples include the attenuation of ultrasound due to scattering from grain boundaries and the anisotropies in velocity that are associated with preferred grain orientation. Less commonly discussed are the creation of backscattered noise, which can mask flaw signals, and the modification of transducer radiation patterns, e.g. the modulation of the phase fronts in a beam, which can cause fluctuations in signals reflected from surfaces [1]. The latter influence the measurement of attenuation as well as the strength of signals reflected from flaws. The goal of this work is to develop a unified basis for understanding these phenomena, as can be used in the analysis of the performance of ultrasonic flaw detection systems. Of interest are correlations of noise in time as well as the variance of noise signals (about their mean of zero) and reflected signals (about a non-zero mean).</p

Relationships Between Ultrasonic Noise and Macrostructure of Titanium Alloys

The complex microstructure of two-phase titanium alloys can produce considerable ultrasonic backscattering noise. The noise introduces problems in detecting small flaws, such as hard-alpha inclusions, by forming a background which can mask the flaw signals. Therefore better understanding of grain noise is required to quantify and increase the detectability of the small flaws. As an aid to understanding the grain noise, an independent scattering model was constructed and studied during last two years by Margetan and Thompson. In that model for the backscattered noise generated by a tone burst, the grain noise is described by following equation (1) N(t)=FOM×M(t) where N(t) is the rms grain noise, FOM is a material characteristic parameter and M is a factor that depends on the detailed description of the experimental configuration as well as the ultrasonic attenuation. The argument, t, is the time delay at which the noise is observed and can be related to a spatial position within the material. Since the model gives an explicit functional form for M, it is possible to use Eq. (1) to infer the FOM from a measurement of N(t).1 Figure 1 presents the results of such a measurement in which the noise was observed, through each of three orthogonal sides of a set of four Ti-6246 specimens, whose history of heat treatment is summarized in Table 1.2 The FOM’s of each of specimens A1, A2 and B2 varied by an order of magnitude, depending on the side of the measurement. However, on specimen C1, which was annealed above the beta transus of 1775 °F, the noise was nearly isotropic. The purpose of this paper is to understand the origin of this anisotropy

Theory of Ultrasonic Backscatter From Multiphase Polycrystalline Solids

Ultrasound scatters from the microscopic single crystals that constitute polycrystalline solids. The scattering originates from crystallite-crystallite variations in the density and elastic constants. For single-phase materials, each crystallite has the same density and the same crystalline symmetry. Hence, in single-phase materials scattering arises from the variation in velocity, which in turn is due to the anisotropy of the elastic constants and the more or less random orientation of the crystallites [1,2]. The situation is considerably more complicated in multiphase alloys where the density, the crystal symmetry and the elastic constants vary from crystallite to crystallite

Novel sialic acid derivatives lock open the 150-loop of an influenza A virus group-1 sialidase

This work was supported by the Medical Research Council and the Scottish Funding Council.Influenza virus sialidase has an essential role in the virus’ life cycle. Two distinct groups of influenza A virus sialidases have been established, that differ in the flexibility of the ‘150-loop’, providing a more open active site in the apo form of the group-1 compared to group-2 enzymes. In this study we show, through a multidisciplinary approach, that novel sialic acid-based derivatives can exploit this structural difference and selectively inhibit the activity of group-1 sialidases. We also demonstrate that group-1 sialidases from drug-resistant mutant influenza viruses are sensitive to these designed compounds. Moreover, we have determined, by protein X-ray crystallography, that these inhibitors lock open the group-1 sialidase flexible 150-loop, in agreement with our molecular modelling prediction. This is the first direct proof that compounds may be developed to selectively target the pandemic A/H1N1, avian A/H5N1 and other group-1 sialidase-containing viruses, based on an open 150-loop conformation of the enzyme.Publisher PDFPeer reviewe

Influence of Columnar Microstructure on Ultrasonic Backscattering

Most structural materials are polycrystalline, that is, they are composed of numerous discrete grains, each having a regular, crystalline atomic structure. The elastic properties of the grains are anisotropic and their crystallographic axes are differently oriented. When an ultrasonic wave propagates through such a polycrystalline aggregate, it is scattered at the grain boundaries. The fraction of sound energy thus removed from the main beam is responsible for important phenomenons like attenuation and dispersion of the main beam, and background “noise” associated with a given ultrasonic inspection system. The amount of sound energy removed from the main beam depends on the size, shape, and orientation distributions of the grains. If the grains are equiaxed and randomly oriented, propagation direction of the ultrasonic wave has no effect upon the magnitude of the scattered energy. Such is not the case when an acoustic wave travels through materials like centrifugally cast stainless steel and austenitic stainless steel welds, which are used extensively in nuclear power plants. The microstructures of these stainless steels vary from randomly oriented, equiaxed grains to highly oriented, columnar grains.1,2 Since the backscattered signals tend to mask the signals from small and subtle defects, the estimation of probability of detection of such defects requires quantitative description of these signals. Consequently, an effort has been undertaken in this research to quantify the backscattered signals from microstructures with favored grain orientation and grain elongation

Effect of Texture on Ultrasonic Backscattering Coefficient in Pure Titanium Plate

Ultrasonic grain noise is one of the important factors which limit the detectability of small defects. The intensity of the grain noise may be represented by the ultrasonic backscattering coefficient which directly relates microstructure to the grain noise intensity. Various microstructures affect the backscattering coefficient, as reported in previous volumes of this series of proceedings1–3. In the present article, the effect of texture will be quantitatively discussed.</p

Prediction-Coherent LSTM-based Recurrent Neural Network for Safer Glucose Predictions in Diabetic People

In the context of time-series forecasting, we propose a LSTM-based recurrent neural network architecture and loss function that enhance the stability of the predictions. In particular, the loss function penalizes the model, not only on the prediction error (mean-squared error), but also on the predicted variation error. We apply this idea to the prediction of future glucose values in diabetes, which is a delicate task as unstable predictions can leave the patient in doubt and make him/her take the wrong action, threatening his/her life. The study is conducted on type 1 and type 2 diabetic people, with a focus on predictions made 30-minutes ahead of time. First, we confirm the superiority, in the context of glucose prediction, of the LSTM model by comparing it to other state-of-the-art models (Extreme Learning Machine, Gaussian Process regressor, Support Vector Regressor). Then, we show the importance of making stable predictions by smoothing the predictions made by the models, resulting in an overall improvement of the clinical acceptability of the models at the cost in a slight loss in prediction accuracy. Finally, we show that the proposed approach, outperforms all baseline results. More precisely, it trades a loss of 4.3\% in the prediction accuracy for an improvement of the clinical acceptability of 27.1\%. When compared to the moving average post-processing method, we show that the trade-off is more efficient with our approach

A prospective trial of tacrolimus (FK 506) in clinical heart transplantation: Intermediate-term results

Between January 1, 1989, and December 31, 1994, we have treated 122 primary heart recipients with FK 506 (group I) and 121 with cyclosporine (group II). Fifty patients in the cyclosporine (CyA) group received no lympholytic induction (CyA alone) and 71 others received lympholytic induction with either rabbit antithymocyte globulin or OKT3 (CyA+LI). The mean follow-up was longer in the FK 506 group than in the CyA groups (3.2 ± 1.3 vs 2.3 ± 1.8 years; p < 0.01). Patient survival did not differ on the basis of the type of immunosuppression used. At 3 months after transplantation, the freedom from rejection in the FK 506 group was higher than that of the CyA-alone group (47% vs 22%, p < 0.01) but similar to that of the CyA+LI group (47% vs 53%). The linearized rejection rate (episodes/100 patient-days) of the FK 506 group (0.09 episodes) was lower (p < 0.05) than that of the CyA-alone group (0.26) and the CyA+LI group (0.13). The requirement for pulsed steroids to treat rejection was less in common in the FK 506 group than in either CyA group. Eighteen patients in the CyA group had refractory rejections; all resolved with FK 506 rescue. Two patients in the FK 506 group had refractory rejection that resolved with total lymphoid irradiation (n = 1) and methotrexate therapy (n = 1). Patients receiving FK 506 had a lower risk of hypertension and required a lower dose of steroids. Although the mean serum creatinine concentration at 1 year was higher in the FK 506 group, this difference disappeared after 2 years. No patients required discontinuation of FK 506 because of its side effects. Our intermediate-term results indicate that FK 506 compares favorably with CyA as a primary immunosuppressant in heart transplantation

Patterns of analgesic use, pain and self-efficacy: a cross-sectional study of patients attending a hospital rheumatology clinic

Background: Many people attending rheumatology clinics use analgesics and non-steroidal anti-inflammatories for persistent musculoskeletal pain. Guidelines for pain management recommend regular and pre-emptive use of analgesics to reduce the impact of pain. Clinical experience indicates that analgesics are often not used in this way. Studies exploring use of analgesics in arthritis have historically measured adherence to such medication. Here we examine patterns of analgesic use and their relationships to pain, self-efficacy and demographic factors. Methods: Consecutive patients were approached in a hospital rheumatology out-patient clinic. Pattern of analgesic use was assessed by response to statements such as 'I always take my tablets every day.' Pain and self-efficacy (SE) were measured using the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) and Arthritis Self-Efficacy Scale (ASES). Influence of factors on pain level and regularity of analgesic use were investigated using linear regression. Differences in pain between those agreeing and disagreeing with statements regarding analgesic use were assessed using t-tests. Results: 218 patients (85% of attendees) completed the study. Six (2.8%) patients reported no current pain, 26 (12.3%) slight, 100 (47.4%) moderate, 62 (29.4%) severe and 17 (8.1%) extreme pain. In multiple linear regression self efficacy and regularity of analgesic use were significant (p < 0.01) with lower self efficacy and more regular use of analgesics associated with more pain. Low SE was associated with greater pain: 40 (41.7%) people with low SE reported severe pain versus 22 (18.3%) people with high SE, p < 0.001. Patients in greater pain were significantly more likely to take analgesics regularly; 13 (77%) of those in extreme pain reported always taking their analgesics every day, versus 9 (35%) in slight pain. Many patients, including 46% of those in severe pain, adjusted analgesic use to current pain level. In simple linear regression, pain was the only variable significantly associated with regularity of analgesic use: higher levels of pain corresponded to more regular analgesic use (p = 0.003). Conclusion: Our study confirms that there is a strong inverse relationship between self-efficacy and pain severity. Analgesics are often used irregularly by people with arthritis, including some reporting severe pain