Observations of one young and three middle-aged γ\gamma-ray pulsars with the Gran Telescopio Canarias

We used the 10.4m Gran Telescopio Canarias to search for the optical counterparts to four isolated $\gamma$-ray pulsars, all detected in the X-rays by either \xmm\ or \chan\ but not yet in the optical. Three of them are middle-aged pulsars -- PSR\, J1846+0919 (0.36 Myr), PSR\, J2055+2539 (1.2 Myr), PSR\, J2043+2740 (1.2 Myr) -- and one, PSR\, J1907+0602, is a young pulsar (19.5 kyr). For both PSR\, J1907+0602 and PSR\, J2055+2539 we found one object close to the pulsar position. However, in both cases such an object cannot be a viable candidate counterpart to the pulsar. For PSR\, J1907+0602, because it would imply an anomalously red spectrum for the pulsar and for PSR\, J2055+2539 because the pulsar would be unrealistically bright ($r'=20.34\pm0.04$) for the assumed distance and interstellar extinction. For PSR\, J1846+0919, we found no object sufficiently close to the expected position to claim a possible association, whereas for PSR\, J2043+2740 we confirm our previous findings that the object nearest to the pulsar position is an unrelated field star. We used our brightness limits ($g' \approx 27$), the first obtained with a large-aperture telescope for both PSR\, J1846+0919 and PSR\, J2055+2539, to constrain the optical emission properties of these pulsars and investigate the presence of spectral turnovers at low energies in their multi-wavelength spectra.Comment: 10 pages, 11 figures, accpted for publication in MNRA

Towards multiple 3D bone surface identification and reconstruction using few 2D X-ray images for intraoperative applications

This article discusses a possible method to use a small number, e.g. 5, of conventional 2D X-ray images to reconstruct multiple 3D bone surfaces intraoperatively. Each bone’s edge contours in X-ray images are automatically identified. Sparse 3D landmark points of each bone are automatically reconstructed by pairing the 2D X-ray images. The reconstructed landmark point distribution on a surface is approximately optimal covering main characteristics of the surface. A statistical shape model, dense point distribution model (DPDM), is then used to fit the reconstructed optimal landmarks vertices to reconstruct a full surface of each bone separately. The reconstructed surfaces can then be visualised and manipulated by surgeons or used by surgical robotic systems

A preliminary approach to intelligent x-ray imaging for baggage inspection at airports

Identifying explosives in baggage at airports relies on being able to characterize the materials that make up an X-ray image. If a suspicion is generated during the imaging process (step 1), the image data could be enhanced by adapting the scanning parameters (step 2). This paper addresses the first part of this problem and uses textural signatures to recognize and characterize materials and hence enabling system control. Directional Gabor-type filtering was applied to a series of different X-ray images. Images were processed in such a way as to simulate a line scanning geometry. Based on our experiments with images of industrial standards and our own samples it was found that different materials could be characterized in terms of the frequency range and orientation of the filters. It was also found that the signal strength generated by the filters could be used as an indicator of visibility and optimum imaging conditions predicted

Development of a Computer Vision-Based Three-Dimensional Reconstruction Method for Volume-Change Measurement of Unsaturated Soils during Triaxial Testing

Problems associated with unsaturated soils are ubiquitous in the U.S., where expansive and collapsible soils are some of the most widely distributed and costly geologic hazards. Solving these widespread geohazards requires a fundamental understanding of the constitutive behavior of unsaturated soils. In the past six decades, the suction-controlled triaxial test has been established as a standard approach to characterizing constitutive behavior for unsaturated soils. However, this type of test requires costly test equipment and time-consuming testing processes. To overcome these limitations, a photogrammetry-based method has been developed recently to measure the global and localized volume-changes of unsaturated soils during triaxial test. However, this method relies on software to detect coded targets, which often requires tedious manual correction of incorrectly coded target detection information. To address the limitation of the photogrammetry-based method, this study developed a photogrammetric computer vision-based approach for automatic target recognition and 3D reconstruction for volume-changes measurement of unsaturated soils in triaxial tests. Deep learning method was used to improve the accuracy and efficiency of coded target recognition. A photogrammetric computer vision method and ray tracing technique were then developed and validated to reconstruct the three-dimensional models of soil specimen

High Spatial Resolution Fast-Neutron Imaging Detectors for Pulsed Fast-Neutron Transmission Spectroscopy

Two generations of a novel detector for high-resolution transmission imaging and spectrometry of fast-neutrons are presented. These devices are based on a hydrogenous fiber scintillator screen and single- or multiple-gated intensified camera systems (ICCD). This detector is designed for energy-selective neutron radiography with nanosecond-pulsed broad-energy (1 - 10 MeV) neutron beams. Utilizing the Time-of-Flight (TOF) method, such a detector is capable of simultaneously capturing several images, each at a different neutron energy (TOF). In addition, a gamma-ray image can also be simultaneously registered, allowing combined neutron/gamma inspection of objects. This permits combining the sensitivity of the fast-neutron resonance method to low-Z elements with that of gamma radiography to high-Z materials.Comment: Also published in JINST: http://www.iop.org/EJ/abstract/1748-0221/4/05/P0501