47,068 research outputs found
Lower bounds of characteristic scale of topological modification of the Newtonian gravitation
We analytically work out the long-term orbital perturbations induced by the
first term of the expansion of the perturbing potential arising from the local
modification of the Newton's inverse square law due to a topology R^2 x S^1
with a compactified dimension of radius R recently proposed by Floratos and
Leontaris. We neither restrict to any specific spatial direction for the
asymmetry axis nor to particular orbital configurations of the test particle.
Thus, our results are quite general. Non-vanishing long-term variations occur
for all the usual osculating Keplerian orbital elements, apart from the
semimajor axis which is left unaffected. By using recent improvements in the
determination of the orbital motion of Saturn from Cassini data, we
preliminarily inferred R >= 4-6 kau. As a complementary approach, the putative
topological effects should be explicitly modeled and solved-for with a modified
version of the ephemerides dynamical models with which the same data sets
should be reprocessed.Comment: Latex, 6 pages, no tables, 1 figure, 3 references. Accepted for
publication in International Journal of Modern Physics D (IJMPD
Separation of variables for a lattice integrable system and the inverse problem
We investigate the relation between the local variables of a discrete
integrable lattice system and the corresponding separation variables, derived
from the associated spectral curve. In particular, we have shown how the
inverse transformation from the separation variables to the discrete lattice
variables may be factorised as a sequence of canonical transformations,
following the procedure outlined by Kuznetsov.Comment: 14 pages. submitted for publicatio
Conversion from linear to circular polarization in FPGA
Context: Radio astronomical receivers are now expanding their frequency range
to cover large (octave) fractional bandwidths for sensitivity and spectral
flexibility, which makes the design of good analogue circular polarizers
challenging. Better polarization purity requires a flatter phase response over
increasingly wide bandwidth, which is most easily achieved with digital
techniques. They offer the ability to form circular polarization with perfect
polarization purity over arbitrarily wide fractional bandwidths, due to the
ease of introducing a perfect quadrature phase shift. Further, the rapid
improvements in field programmable gate arrays provide the high processing
power, low cost, portability and reconfigurability needed to make practical the
implementation of the formation of circular polarization digitally. Aims: Here
we explore the performance of a circular polarizer implemented with digital
techniques. Methods: We designed a digital circular polarizer in which the
intermediate frequency signals from a receiver with native linear polarizations
were sampled and converted to circular polarization. The frequency-dependent
instrumental phase difference and gain scaling factors were determined using an
injected noise signal and applied to the two linear polarizations to equalize
the transfer characteristics of the two polarization channels. This
equalization was performed in 512 frequency channels over a 512 MHz bandwidth.
Circular polarization was formed by quadrature phase shifting and summing the
equalized linear polarization signals. Results: We obtained polarization purity
of -25 dB corresponding to a D-term of 0.06 over the whole bandwidth.
Conclusions: This technique enables construction of broad-band radio astronomy
receivers with native linear polarization to form circular polarization for
VLBI.Comment: 11 pages 8 figure
Towards a grid-enabled simulation framework for nano-CMOS electronics
The electronics design industry is facing major challenges as transistors continue to decrease in size. The next generation of devices will be so small that the position of individual atoms will affect their behaviour. This will cause the transistors on a chip to have highly variable characteristics, which in turn will impact circuit and system design tools. The EPSRC project "Meeting the Design Challenges of Nano-CMOS Electronics" (Nana-CMOS) has been funded to explore this area. In this paper, we describe the distributed data-management and computing framework under development within Nano-CMOS. A key aspect of this framework is the need for robust and reliable security mechanisms that support distributed electronics design groups who wish to collaborate by sharing designs, simulations, workflows, datasets and computation resources. This paper presents the system design, and an early prototype of the project which has been useful in helping us to understand the benefits of such a grid infrastructure. In particular, we also present two typical use cases: user authentication, and execution of large-scale device simulations
The Hamiltonian Structures of the super KP hierarchy Associated with an Even Parity SuperLax Operator
We consider the even parity superLax operator for the supersymmetric KP
hierarchy of the form and obtain
the two Hamiltonian structures following the standard method of Gelfand and
Dikii. We observe that the first Hamiltonian structure is local and linear
whereas the second Hamiltonian structure is non-local and nonlinear among the
superfields appearing in the Lax operator. We discuss briefly on their
connections with the super algebra.Comment: 14 pages, Plain tex, IC/93/17
TBI Contusion Segmentation from MRI using Convolutional Neural Networks
Traumatic brain injury (TBI) is caused by a sudden trauma to the head that
may result in hematomas and contusions and can lead to stroke or chronic
disability. An accurate quantification of the lesion volumes and their
locations is essential to understand the pathophysiology of TBI and its
progression. In this paper, we propose a fully convolutional neural network
(CNN) model to segment contusions and lesions from brain magnetic resonance
(MR) images of patients with TBI. The CNN architecture proposed here was based
on a state of the art CNN architecture from Google, called Inception. Using a
3-layer Inception network, lesions are segmented from multi-contrast MR images.
When compared with two recent TBI lesion segmentation methods, one based on CNN
(called DeepMedic) and another based on random forests, the proposed algorithm
showed improved segmentation accuracy on images of 18 patients with mild to
severe TBI. Using a leave-one-out cross validation, the proposed model achieved
a median Dice of 0.75, which was significantly better (p<0.01) than the two
competing methods.Comment: https://ieeexplore.ieee.org/abstract/document/8363545/, IEEE 15th
International Symposium on Biomedical Imaging (ISBI 2018
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