9,823 research outputs found
Accessibility of Diverse Literature for Children in Libraries: A Literature Review
This literature review addresses the issues surrounding accessibility of culturally diverse children’s literature in libraries, including the importance of making diverse literature accessible, the availability of such titles on the market, library collection development of diverse books, and selection criteria among children. These issues, in sum, determine how many books are available to children, how they are made available, and if children will even choose to read them. The review shows that the data is unclear on many points regarding the benefits of diverse literature, though intuitive claims of the positive influence of such titles are not discounted. It also finds low representation of diversity in publishing and library collections. Finally, studies of how children select reading materials are presented, showing that there is not a straightforward correlation between having books available and children choosing them. Areas of further research are recommended to give librarians more insight into how to better optimize collection resources to best benefit all young readers
An interpretation and solution of ill-conditioned linear equations
Data insufficiency, poorly conditioned matrices and singularities in equations occur regularly in complex optimization, correlation, and interdisciplinary model studies. This work concerns itself with two methods of obtaining certain physically realistic solutions to ill-conditioned or singular algebraic systems of linear equations arising from such studies. Two efficient computational solution procedures that generally lead to locally unique solutions are presented when there is insufficient data to completely define the model, or a least-squares error formulation of this system results in an ill-conditioned system of equations. If it is assumed that a reasonable estimate of the uncertain data is available in both cases cited above, then we shall show how to obtain realistic solutions efficiently, in spite of the insufficiency of independent data. The proposed methods of solution are more efficient than singular-value decomposition for dealing with such systems, since they do not require solutions for all the non-zero eigenvalues of the coefficient matrix
An X-ray/optical study of the geometry and dynamics of MACS J0140.0-0555, a massive post-collision cluster merger
We investigate the physical properties, geometry and dynamics of the massive
cluster merger MACS J0140.0-0555 (z=0.451) using X-ray and optical diagnostics.
Featuring two galaxy overdensities separated by about 250 kpc in projection on
the sky, and a single peak in the X-ray surface brightness distribution located
between them, MACS J0140.0-0555 shows the tell-tale X-ray/optical morphology of
a binary, post-collision merger. Our spectral analysis of the X-ray emission,
as measured by our Chandra ACIS-I observation of the system, finds the
intra-cluster medium to be close to isothermal (~8.5 keV) with no clear signs
of cool cores or shock fronts. Spectroscopic follow-up of galaxies in the field
of MACS J0140.0-0555 yields a velocity dispersion of 875 (+70/-100) km/s
(n_z=66) and no significant evidence of bimodality or substructure along the
line of sight. In addition, the difference in radial velocity between the
brightest cluster galaxies of the two sub-clusters of 144+/-25 km/s is small
compared to typical collision velocities of several 1000 km/s. A strongly
lensed background galaxy at z=0.873 (which features variable X-ray emission
from an active nucleus) provides the main constraint on the mass distribution
of the system. We measure M(<75 kpc) = (5.6+/- 0.5)*10^13 M_sun for the
north-western cluster component and a much less certain estimate of
(1.5-3)*10^13 M_sun for the south-eastern subcluster. These values are in good
agreement with our X-ray mass estimates which yield a total mass of MACS
J0140.0-0555 of M(<r_500) ~ (6.8-9.1)*10^14 M_sun. ......Comment: 11 pages, 8 figures, and 2 tables. Accepted for publication in MNRA
Multiple Radial Cool Molecular Filaments in NGC 1275
We have extended our previous observation (Lim et al. 2008) of NGC1275
covering a central radius of ~10kpc to the entire main body of cool molecular
gas spanning ~14kpc east and west of center. We find no new features beyond the
region previously mapped, and show that all six spatially-resolved features on
both the eastern and western sides (three on each side) comprise radially
aligned filaments. Such radial filaments can be most naturally explained by a
model in which gas deposited "upstream" in localized regions experiencing an
X-ray cooling flow subsequently free falls along the gravitational potential of
PerA, as we previously showed can explain the observed kinematics of the two
longest filaments. All the detected filaments coincide with locally bright
Halpha features, and have a ratio in CO(2-1) to Halpha luminosity of ~1e-3; we
show that these filaments have lower star formation efficiencies than the
nearly constant value found for molecular gas in nearby normal spiral galaxies.
On the other hand, some at least equally luminous Halpha features, including a
previously identified giant HII region, show no detectable cool molecular gas
with a corresponding ratio at least a factor of ~5 lower; in the giant HII
region, essentially all the pre-existing molecular gas may have been converted
to stars. We demonstrate that all the cool molecular filaments are
gravitationally bound, and without any means of support beyond thermal pressure
should collapse on timescales ~< 1e6yrs. By comparison, as we showed previously
the two longest filaments have much longer dynamical ages of ~1e7yrs. Tidal
shear may help delay their collapse, but more likely turbulent velocities of at
least a few tens km/s or magnetic fields with strengths of at least several
~10uG are required to support these filaments.Comment: 52 pages, 11 figures. Accepted to Ap
Neutrino Masses via the Zee Mechanism in 5D split fermions model
We study the Zee model in the framework of the split fermion model in
spacetime. Neutrino masses are generated through 1-loop
diagrams without the right-handed neutrinos introduced. By assuming an order
one anarchical complex 5D Yukawa couplings, all the effective 4D Yukawa
couplings are determined by the wave function overlap between the split
fermions and the bulk scalars in the fifth dimension. The predictability of the
Yukawa couplings is in sharp contrast to the original Zee model in 4D where the
Yukawa couplings are unknown free parameters. This setup exhibits a geometrical
alternative to the lepton flavor symmetry. By giving four explicit sets of the
split fermion locations, we demonstrate that it is possible to simultaneously
fit the lepton masses and neutrino oscillation data by just a handful free
parameters without much fine tuning. Moreover, we are able to make definite
predictions for the mixing angle , the absolute neutrino masses,
and the lepton flavor violation processes for each configuration.Comment: 16 pages, 2 figure
Neural Discrete Representation Learning
Learning useful representations without supervision remains a key challenge
in machine learning. In this paper, we propose a simple yet powerful generative
model that learns such discrete representations. Our model, the Vector
Quantised-Variational AutoEncoder (VQ-VAE), differs from VAEs in two key ways:
the encoder network outputs discrete, rather than continuous, codes; and the
prior is learnt rather than static. In order to learn a discrete latent
representation, we incorporate ideas from vector quantisation (VQ). Using the
VQ method allows the model to circumvent issues of "posterior collapse" --
where the latents are ignored when they are paired with a powerful
autoregressive decoder -- typically observed in the VAE framework. Pairing
these representations with an autoregressive prior, the model can generate high
quality images, videos, and speech as well as doing high quality speaker
conversion and unsupervised learning of phonemes, providing further evidence of
the utility of the learnt representations
Rare case of magnetic Ag ion: double perovskite CsKAgF
Normally or transition metals are in a low-spin state. Here using
first-principles calculations, we report on a rare case of a high-spin =1
magnetic state for the Ag ion in the double perovskite
CsKAgF. We also explored a possibility of a conventional low-spin
=0 ground state and find an associated tetragonal distortion to be 0.29
{\AA}. However, the lattice elastic energy cost and the Hund exchange loss
exceed the e crystal-field energy gain, thus making the low-spin
tetragonal structure less favorable than the high-spin cubic structure. We
conclude that the compact perovskite structure of CsKAgF is an
important factor in stabilizing the unusual high-spin ground state of
Ag.Comment: 6 pages, 6 figures, accepted for publication in PR
Orderly Spanning Trees with Applications
We introduce and study the {\em orderly spanning trees} of plane graphs. This
algorithmic tool generalizes {\em canonical orderings}, which exist only for
triconnected plane graphs. Although not every plane graph admits an orderly
spanning tree, we provide an algorithm to compute an {\em orderly pair} for any
connected planar graph , consisting of a plane graph of , and an
orderly spanning tree of . We also present several applications of orderly
spanning trees: (1) a new constructive proof for Schnyder's Realizer Theorem,
(2) the first area-optimal 2-visibility drawing of , and (3) the best known
encodings of with O(1)-time query support. All algorithms in this paper run
in linear time.Comment: 25 pages, 7 figures, A preliminary version appeared in Proceedings of
the 12th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA 2001),
Washington D.C., USA, January 7-9, 2001, pp. 506-51
A Machine Learning Artificial Neural Network Calibration of the Strong-Line Oxygen Abundance
The HII region oxygen abundance is a key observable for studying chemical
properties of galaxies. Deriving oxygen abundances using optical spectra often
relies on empirical strong-line calibrations calibrated to the direct method.
Existing calibrations usually adopt linear or polynomial functions to describe
the non-linear relationships between strong line ratios and Te oxygen
abundances. Here, I explore the possibility of using an artificial neural
network model to construct a non-linear strong-line calibration. Using about
950 literature HII region spectra with auroral line detections, I build
multi-layer perceptron models under the machine learning framework of training
and testing. I show that complex models, like the neural network, are preferred
at the current sample size and can better predict oxygen abundance than simple
linear models. I demonstrate that the new calibration can reproduce metallicity
gradients in nearby galaxies and the mass-metallicity relationship. Finally, I
discuss the prospects of developing new neural network calibrations using
forthcoming large samples of HII region and also the challenges faced.Comment: 12 pages, 15 figures. Accepted to MNRA
Radiation-induced magnetoresistance oscillations in two-dimensional electron systems under bichromatic irradiation
We analyze the magnetoresistance oscillations in high-mobility
two-dimensional electron systems induced by the combined driving of two
radiation fields of frequency and , based on the
balance-equation approach to magnetotransport for high-carrier-density systems
in Faraday geometry. It is shown that under bichromatic irradiation of
, most of the characterstic peak-valley pairs in the
curve of versus magnetic field in the case of monochromatic
irradiation of either or disappear, except the one around
or . oscillations
show up mainly as new peak-valley structures around other positions related to
multiple photon processes of mixing frequencies ,
, etc. Many minima of these resistance peak-valley pairs can
descend down to negative with enhancing radiation strength, indicating the
possible bichromaticzero-resistance states.Comment: 5 pages, 3 figures. Accepted for publication in Phys. Rev.
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