This paper proposed a deep learning method of sinogram correction for beam hardening reduction in CT for the first time. Conventional methods for beam hardening reduction are based on regularizations, and have the fundamental drawback of being not easily able to use manifold CT images, while a deep learning approach has the potential to do so.
Objective: Obstetricians mainly use ultrasound imaging for fetal biometric measurements. However, such measurements are cumbersome. Hence, there is urgent need for automatic biometric estimation. Automated analysis of ultrasound images is complicated owing to the patient-specific, operator-dependent, and machine-specific characteristics of such images. Approach: This paper proposes a method for the automatic fetal biometry estimation from 2D ultrasound data through several processes consisting of a specially designed convolutional neural network (CNN) and U-Net for each process.
Multiflagellated bacteria such as E. coli exploit the polymorphic transformations of helical flagella to explore their fluid environment. In these bacteria, a sequence of polymorphic helical forms appears consecutively as the cell “runs” and “tumbles.” During a run, the molecular motors that drive the twirling flagella spin counterclockwise, and the flagella form a normal flagellar bundle. Reversing one or more of these motors, from counterclockwise to clockwise, initiates a tumble by inducing shape transformations of the associated filaments, from normal to semicoiled and then to curly 1 forms. The next run begins when the motors switch back to counterclockwise rotations. This causes the flagella to revert from curly 1 back to normal forms. This paper investigates the dynamics of elastic flagella when one or two flagella undergo a full cycle of polymorphic transformations using a computational method in which the flagellar motors are tethered in space and connected via flexible hooks
We obtain Calderon？Zygmund type estimate for nonlinear elliptic equations of p-Laplacian type, under the condition that the associated nonlinearity is allowed to be merely measurable in one spatial variable, but has locally small mean oscillation in the remaining spatial variables. This is the minimal regularity requirement on the associated nonlinearity for Calderon？Zygmund type estimate, in the sense that if the associated nonlinearity is allowed to be merely measurable with respect to two independent spatial variables then Calderon？Zygmund type estimate fails in general.
We prove that the Hecke-Maass eigenforms for a compact arithmetic triangle group have a growing number of nodal domains as the eigenvalue tends to $ +\infty $. More generally the same is proved for eigenfunctions on negatively curved surfaces that are even or odd with respect to a geodesic symmetry and for which quantum unique ergodicity holds.
In this paper we introduce a new method to produce lower bounds for the Waring rank of symmetric tensors. We also introduce the notion of ecomputability and we use it to prove that Strassen’s conjecture holds in infinitely many new cases.
We study the essential surfaces in the exterior of a cable knot to compute the representativity and waist of most cable knots. Our computation answers Ozawa’s question  about the relationship between the representativity and the waist of a knot in the negative.
We present the first Advanced LIGO and Advanced Virgo search for ultracompact binary systems with component masses between 0.2 M⊙-1.0 M⊙ using data taken between September 12, 2015 and January 19, 2016.We find no viable gravitational wave candidates. Our null result constrains the coalescence rate of monochromatic (delta function) distributions of nonspinning (0.2 M⊙, 0.2 M⊙) ultracompact binaries to be less than 1.0 × 106 Gpc？3 yr？1 and the coalescence rate of a similar distribution of (1.0 M⊙, 1.0 M⊙) ultracompact binaries to be less than 1.9 × 104 Gpc？3 yr？1 (at 90% confidence). Neither black holes nor neutron stars are expected to form below ∼1 M⊙ through conventional stellar evolution, though it has been proposed that similarly low mass black holes could be formed primordially through density fluctuations in the early Universe and contribute to the dark matter density.
Since the first detection of gravitational-wave (GW), GW150914, September 14th 2015, the multimessenger astronomy added a new way of observing the Universe together with electromagnetic (EM) waves and neutrinos. After two years, GW together with its EM counterpart from binary neutron stars, GW170817 and GRB170817A, has been observed. The detection of GWs opened a new window of astronomy/astrophysics and will be an important messenger to understand the Universe. In this article, we briefly review the gravitational-wave and the astrophysical sources and introduce the basic principle of the laser interferometer as a gravitational-wave detector and its noise sources to understand how the gravitational-waves are detected in the laser interferometer. Finally, we summarize the search algorithms currently used in the gravitational-wave observatories and the detector characterization algorithms used to suppress noises and to monitor data quality in order to improve the reach of the astrophysica
On 17 August 2017, the LIGO and Virgo observatories made the first direct detection of gravitational waves from the coalescence of a neutron star binary system. The detection of this gravitational-wave signal, GW170817, offers a novel opportunity to directly probe the properties of matter at the extreme conditions found in the interior of these stars. The initial, minimal-assumption analysis of the LIGO and Virgo data placed constraints on the tidal effects of the coalescing bodies, which were then translated to constraints on neutron star radii.