Creating Noise-Corrupted Flaw Signals for Ultrasonic Nondestructive Evaluation

Noise-corrupted flaw signals with known contributions due to flaw scattering are needed to study flaw detection and characterization approaches. The inability to create these “known flaw” signals which are corrupted with acoustic noise (e.g., grain scattering noise) has presented a problem to the nondestructive evaluation (NDE) community for years. An approach is needed for creating noise-corrupted flaw signals which can be used as a basis for studying the impact of different flaw types, measurement system configurations, signal-to-noise ratios (SNRs), acoustic noise types, etc. on digital signal processing algorithms which are being developed

Toward Comprehensive Refugee Legislation in Hong Kong? Reflections on Reform of the 'Torture Screening' Procedures

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Wavelets and their application to digital signal processing in ultrsaonic NDE

As the use of digital based ultrasonic testing systems becomes more prevalent, there will be an increased emphasis on the development of digital signal processing techniques. In the past, various Fourier based digital signal processing approaches have been formulated and applied in the ultrasonic nondestructive evaluation (NDE) research community. In many cases, the inherent inability of Fourier methods to handle non-stationary signals has been exposed as the Fourier methods are applied to non-stationary ultrasonic signals. Our intent is to investigate the application of wavelet based signals processing techniques to a variety of problems in ultrasonic NDE. Wavelet methods have a number of potential advantage over Fourier methods including the inherent ability of wavelets to deal with non-stationary signals

Effect of Monomer Solubility on the Evolution of Copolymer Morphology during Polymerization-Induced Self-Assembly in Aqueous Solution

Polymerization-induced self-assembly (PISA) has become a widely used technique for the rational design of diblock copolymer nano-objects in concentrated aqueous solution. Depending on the specific PISA formulation, reversible addition–fragmentation chain transfer (RAFT) aqueous dispersion polymerization typically provides straightforward access to either spheres, worms, or vesicles. In contrast, RAFT aqueous emulsion polymerization formulations often lead to just kinetically-trapped spheres. This limitation is currently not understood, and only a few empirical exceptions have been reported in the literature. In the present work, the effect of monomer solubility on copolymer morphology is explored for an aqueous PISA formulation. Using 2-hydroxybutyl methacrylate (aqueous solubility = 20 g dm–3 at 70 °C) instead of benzyl methacrylate (0.40 g dm–3 at 70 °C) for the core-forming block allows access to an unusual “monkey nut” copolymer morphology over a relatively narrow range of target degrees of polymerization when using a poly(methacrylic acid) RAFT agent at pH 5. These new anisotropic nanoparticles have been characterized by transmission electron microscopy, dynamic light scattering, aqueous electrophoresis, shear-induced polarized light imaging (SIPLI), and small-angle X-ray scattering

Deep learning optimized single-pixel LiDAR

Interest in autonomous transport has led to a demand for 3D imaging technologies capable of resolving fine details at long range. Light detection and ranging (LiDAR) systems have become a key technology in this area, with depth information typically gained through time-of-flight photon-counting measurements of a scanned laser spot. Single-pixel imaging methods offer an alternative approach to spot-scanning, which allows a choice of sampling basis. In this work, we present a prototype LiDAR system, which compressively samples the scene using a deep learning optimized sampling basis and reconstruction algorithms. We demonstrate that this approach improves scene reconstruction quality compared to an orthogonal sampling method, with reflectivity and depth accuracy improvements of 57% and 16%, respectively, for one frame per second acquisition rates. This method may pave the way for improved scan-free LiDAR systems for driverless cars and for fully optimized sampling to decision-making pipelines

Reduced appropriate implantable cardioverter-defibrillator therapy after cardiac resynchronization therapy-induced left ventricular function recovery: a meta-analysis and systematic review

Aims For patients undergoing cardiac resynchronization therapy (CRT) with implantable cardioverter-defibrillator (ICD; CRT-D), the effect of an improvement in left ventricular ejection fraction (LVEF) on appropriate ICD therapy may have significant implications regarding management at the time of ICD generator replacement. Methods and results We conducted a meta-analysis to determine the effect of LVEF recovery following CRT on the incidence of appropriate ICD therapy. A search of multiple electronic databases identified 709 reports, of which 6 retrospective cohort studies were included (n = 1740). In patients with post-CRT LVEF ≥35% (study n = 4), the pooled estimated rate of ICD therapy (5.5/100 person-years) was significantly lower than patients with post-CRT LVEF <35% [incidence rate difference (IRD): −6.5/100 person-years, 95% confidence interval (95% CI): −8.8 to −4.2, P < 0.001]. Similarly, patients with post-CRT LVEF ≥45% (study n = 4) demonstrated lower estimated rates of ICD therapy (2.3/100 person-years) compared with patients without such recovery (IRD: −5.8/100 person-years, 95% CI: −7.6 to −4.0, P < 0.001). Restricting analysis to studies discounting ICD therapies during LVEF recovery (study n = 3), patients with LVEF recovery (≥35 or ≥45%) had significantly lower rates of ICD therapy compared with patients without such recovery (P for both <0.001). Patients with primary prevention indication for ICD, regardless of LVEF recovery definition, had very low rates of ICD therapy (0.4 to 0.8/100-person years). Conclusion Recovery of LVEF post-CRT is associated with significantly reduced appropriate ICD therapy. Patients with improvement of LVEF ≥45% and those with primary prevention indication for ICD appear to be at lowest ris

Refractive index matched, nearly hard polymer colloids

Refractive index matched particles serve as essential model systems for colloid scientists, providing nearly hard spheres to explore structure and dynamics. The poly(methyl methacrylate) latexes typically used are often refractive index matched by dispersing them in binary solvent mixtures, but this can lead to undesirable changes, such as particle charging or swelling. To avoid these shortcomings, we have synthesized refractive index matched colloids using polymerization-induced self-assembly (PISA) rather than as polymer latexes. The crucial difference is that these diblock copolymer nanoparticles consist of a single core-forming polymer in a single non-ionizable solvent. The diblock copolymer chosen was poly(stearyl methacrylate)-poly(2,2,2trifluoroethyl methacrylate) (PSMA-PTFEMA), which self-assembles to form PTFEMA core spheres in n-alkanes. By monitoring scattered light intensity, n-tetradecane was found to be the optimal solvent for matching the refractive index of such nanoparticles. As expected for PISA syntheses, the diameter of the colloids can be controlled by varying the PTFEMA degree of polymerization. Concentrated dispersions were prepared, and the diffusion of the PSMA-PTFEMA nanoparticles as a function of volume fraction was measured. These diblock copolymer nanoparticles are a promising new system of transparent spheres for future colloidal studies

The Bolocam Galactic Plane Survey. VIII. A Mid-Infrared Kinematic Distance Discrimination Method

We present a new distance estimation method for dust-continuum-identified molecular cloud clumps. Recent (sub-)millimeter Galactic plane surveys have cataloged tens of thousands of these objects, but detailed study of their physical properties requires robust distance determinations. We derive Bayesian distance probability density functions (DPDFs) for 770 objects from the Bolocam Galactic Plane Survey in the longitude range 7.5 < l < 65. The DPDF formalism is based on kinematic distances, and uses external data sets to place prior distance probabilities to resolve the kinematic distance ambiguity (KDA) for objects in the inner Galaxy. We present priors related to the mid-infrared absorption of dust in dense molecular regions and the Galactic distribution of molecular gas. By assuming a numerical model of Galactic mid-infrared emission and simple radiative transfer, we match the morphology of millimeter thermal dust emission with mid-infrared absorption to compute a prior DPDF for distance discrimination. Selecting objects first from (sub-)millimeter source catalogs avoids a bias towards the darkest infrared dark clouds (IRDCs) and extends the range of heliocentric distance and contrast range probed by mid-infrared extinction. We derive well-constrained KDA resolutions for 618 molecular cloud clumps, with approximately 15% placed at or beyond the tangent distance. Objects sufficiently dark to be cataloged as IRDCs are generally placed at the near kinematic distance. Distance comparisons with Galactic Ring Survey KDA resolutions yield a 92% agreement, and a Galactic face-on view reveals sections of the Sagittarius and Scutum-Centaurus Arms. This KDA-resolution method for large catalogs of sources through the combination of (sub-)millimeter and mid-infrared observations of molecular cloud clumps is generally applicable to other dust-continuum Galactic plane surveys.Comment: Accepted for publication in ApJ; 29 pages, 16 figures. Data available prior to publication by contacting the author

Training future generations to deliver evidence‐based conservation and ecosystem management

1. To be effective, the next generation of conservation practitioners and managers need to be critical thinkers with a deep understanding of how to make evidence-based decisions and of the value of evidence synthesis. 2. If, as educators, we do not make these priorities a core part of what we teach, we are failing to prepare our students to make an effective contribution to conservation practice. 3. To help overcome this problem we have created open access online teaching materials in multiple languages that are stored in Applied Ecology Resources. So far, 117 educators from 23 countries have acknowledged the importance of this and are already teaching or about to teach skills in appraising or using evidence in conservation decision-making. This includes 145 undergraduate, postgraduate or professional development courses. 4. We call for wider teaching of the tools and skills that facilitate evidence-based conservation and also suggest that providing online teaching materials in multiple languages could be beneficial for improving global understanding of other subject areas