Long gamma-ray bursts (GRBs) have been linked to extreme core-collapse supernovae from massive stars. Gravitational waves (GW) offer a probe of the physics behind long GRBs. We investigate models of long-lived ($\sim 10–1000s$ ) GW emission associated with the accretion disk of a collapsed star or with its protoneutron star remnant. Using data from LIGO’s fifth science run, and GRB triggers from the Swift experiment, we perform a search for unmodeled long-lived GW transients. Finding no evidence of GW emission, we place 90% confidence-level upper limits on the GW fluence at Earth from long GRBs for three waveforms inspired by a model of GWs from accretion disk instabilities. These limits range from $F<3.5\mathrm{ergs}{\mathrm{cm}}^{-2}$ to $F<1200\mathrm{ergs}{\mathrm{cm}}^{-2}$ , depending on the GRB and on the model, allowing us to probe optimistic scenarios of GW production out to distances as far as $\approx 33\mathrm{Mpc}$ . Advanced detectors are expected to achieve strain sensitivities $10\times$ better than initial LIGO, potentially allowing us to probe the engines of the nearest long GRBs.

Nearly a century after Einstein first predicted the existence of gravitational waves, a global network of Earth-based gravitational wave observatories^1,2,3,4 is seeking to directly detect this faint radiation using precision laser interferometry. Photon shot noise, due to the quantum nature of light, imposes a fundamental limit on the attometre-level sensitivity of the kilometre-scale Michelson interferometers deployed for this task. Here, we inject squeezed states to improve the performance of one of the detectors of the Laser Interferometer Gravitational-Wave Observatory (LIGO) beyond the quantum noise limit, most notably in the frequency region down to 150 Hz, critically important for several astrophysical sources, with no deterioration of performance observed at any frequency. With the injection of squeezed states, this LIGO detector demonstrated the best broadband sensitivity to gravitational waves ever achieved, with important implications for observing the gravitational-wave Universe with unprecedented sensitivity.

Magnetic resonance electrical impedance tomography (MREIT) is a new medical imaging modality visualizing static conductivity images of electrically conducting subjects. Recently, MREIT has rapidly progressed in its theory, algorithm, and experiment technique and now reached to the stage of in vivo animal experiments. In this paper, we present a software, named CoReHA 2.0 standing for the second version of conductivity reconstructor using harmonic algorithms, to facilitate in vivo MREIT reconstruction of conductivity image. This software offers various computational tools including preprocessing of MREIT data, identification of 2D geometry of the imaging domain and electrode positions, and reconstruction of cross-sectional scaled conductivity images from MREIT data. In particular, in the new version, we added several tools including ramp-preserving denoising, harmonic inpainting, and local harmonic algorithm to deal with data from in vivo experiments. The presented software will be useful to researchers in the field of MREIT for simulation, validation, and further technical development.

This paper proposes a robust real-time myocardial border tracking algorithm for echocardiography. Commonly, after an initial contour of LV border is traced at one or two frames from the entire cardiac cycle, LV contour tracking is performed over the remaining frames. Among a variety of tracking techniques, optical flow method is the most widely used for motion estimation of moving objects. However, when echocardiography data is heavily corrupted in some local regions, the errors bring the tracking point out of the endocardial border, resulting in distorted LV contours. This shape distortion often occurs in practice since the data acquisition is affected by ultrasound artifacts, outs, or shadowing phenomena of cardiac walls. The proposed method is designed to deal with this shape distortion problem by integrating local optical flow motion and global deformation into a variational framework. The proposed descent method controls the individual tracking points to follow the local motions of a specific speckle pattern, while their overall motions are confined to the global motion constraint being approximately an affine transform of the initial tracking points. Many real experiments show that the proposed method achieves better overall performance than conventional methods.

When the cohomology ring of a generalized Bott manifold with Q-coefficient is isomorphic to that of a product of complex projective spaces CP^<n_<i>> , the generalized Bott manifold is said to be Q-trivial. We find a necessary and sufficient condition for a generalized Bott manifold to be Q-trivial. In particular, every Q-trivial generalized Bott manifold is diffeomorphic to a Π_<n_<i> > 1> CP^<n_<i>> -bundle over a Q-trivial Bott manifold.

The notion of a toric origami manifold, which weakens the notion of a symplectic toric manifold, was introduced by A. Cannas da Silva, V. Guillemin and A.R. Pires. They showed that toric origami manifolds bijectively correspond to origami templates via moment maps, where an origami template is a collection of Delzant polytopes with some folding data. Like a fan is associated to a Delzant polytope, a multi-fan introduced by A. Hattori and M. Masuda can be associated to an oriented origami template. In this paper, we discuss their relationship and show that any simply connected compact smooth 4-manifold with a smooth action of T ² can be a toric origami manifold. We also characterize products of even dimensional spheres which can be toric origami manifolds.

There has been an increasing interest in analyzing social network services data. However, detecting social topics in the era of information explosion requires state-of-the-art analytics techniques. The geographic clustering analysis based on social topics across provinces, i.e., states, has rarely been studied. Using the Twitter data collected in the United States (US), we detected the social hot topic by using the ratio of word frequency. Also, we found geographic communities by correlating the time series for a set of topic words across US states. The result of the geographic clustering was visualized using the Google Fusion Table. In conclusion, the ratio of word frequency properly detects social topics or breaking news while suppressing daily tweeted small talks or emotional words such as lol, like, and love. We have also demonstrated that a clustering algorithm based on a social topic can be useful in classifying social communities.

Many High-Dynamic-Range (HDR) rendering techniques have been developed. Of these, the image color appearance model, iCAM, is a typical HDR image rendering algorithm. HDR rendering methods normally require a tone compression process and include many color space transformations from the RGB signal of an input image to the RGB signal of output devices for the realistic depiction of a captured image. The iCAM06, which is a refined iCAM, also contains a tone compression step and several color space conversions for HDR image reproduction. On the other hand, the tone compression and frequent color space changes in the iCAM06 cause color distortion, such as a hue shift and saturation reduction of the output image. To solve these problems, this paper proposes a separate color correction method that has no effect on the output luminance values by controlling only the saturation and hue of the color attributes. The color saturation of the output image was compensated for using the compensation gain and the hue shift was corrected using the rotation matrix. The separate color correction method reduces the existing color changes in iCAM06. The compensation gain and rotation matrix for the color correction were formulated based on the relationship between the input and output tristimulus values through the tone compression. The experimental results show that the revised iCAM06 with the proposed method has better performance than the default iCAM06.

We present a multi-channel sampling expansion for signals with selectively tiled band-region. From this we derive an oversampling expansion for any bandpass signal, and show that any finitely many missing samples from two-channel oversampling expansion can always be uniquely recovered. In addition, we find a sufficient condition under which some infinitely many missing samples can be recovered. Numerical stability of the recovery process is also discussed in terms of the oversampling rate and distribution of the missing samples.