7,317 research outputs found
Method of improving contact bonds in silicon integrated circuits
Fabrication method produces stable and reliable metallic systems for interconnections, contact pads, and bonded leads in silicon planar integrated circuits. The method is based on substrate isolation of the interconnection metal from the contact pad and bonded wire
A Search for Stars of Very Low Metal Abundance. V. Photoelectric UBV Photometry of Metal-Weak Candidates from the Northern HK Survey
We report photoelectric UBV data for 268 metal-poor candidates chosen from
the northern HK objective-prism/interference-filter survey of Beers and
colleagues. Over 40 % of the stars have been observed on more than one night,
and most have at least several sets of photometric measurements. Reddening
estimates, preliminary spectroscopic measurements of abundance, and type
classifications are reported.Comment: To Appear in the Astronomical Journal, October 200
Host-Parasite Co-evolution and Optimal Mutation Rates for Semi-conservative Quasispecies
In this paper, we extend a model of host-parasite co-evolution to incorporate
the semi-conservative nature of DNA replication for both the host and the
parasite. We find that the optimal mutation rate for the semi-conservative and
conservative hosts converge for realistic genome lengths, thus maintaining the
admirable agreement between theory and experiment found previously for the
conservative model and justifying the conservative approximation in some cases.
We demonstrate that, while the optimal mutation rate for a conservative and
semi-conservative parasite interacting with a given immune system is similar to
that of a conservative parasite, the properties away from this optimum differ
significantly. We suspect that this difference, coupled with the requirement
that a parasite optimize survival in a range of viable hosts, may help explain
why semi-conservative viruses are known to have significantly lower mutation
rates than their conservative counterparts
Rubidium in Metal-Deficient Disk and Halo Stars
We report the first extensive study of stellar Rb abundances. High-resolution
spectra have been used to determine, or set upper limits on, the abundances of
this heavy element and the associated elements Y, Zr, and Ba in 44 dwarfs and
giants with metallicities spanning the range -2.0 <[Fe/H] < 0.0. In
metal-deficient stars Rb is systematically overabundant relative to Fe; we find
an average [Rb/Fe] of +0.21 for the 32 stars with [Fe/H] < -0.5 and measured
Rb. This behavior contrasts with that of Y, Zr, and Ba, which, with the
exception of three new CH stars (HD 23439A and B and BD +5 3640), are
consistently slightly deficient relative to Fe in the same stars; excluding the
three CH stars, we find the stars with [Fe/H] < -0.5 have average [Y/Fe],
[Zr/Fe], and [Ba/Fe] of --0.19 (24 stars), --0.12 (28 stars), and --0.06 (29
stars), respectively. The different behavior of Rb on the one hand and Y, Zr,
and Ba on the other can be attributed in part to the fact that in the Sun and
in these stars Rb has a large r-process component while Y, Zr, and Ba are
mostly s-process elements with only small r-process components. In addition,
the Rb s-process abundance is dependent on the neutron density at the
s-processing site. Published observations of Rb in s-process enriched red
giants indicate a higher neutron density in the metal-poor giants. These
observations imply a higher s-process abundance for Rb in metal-poor stars. The
calculated combination of the Rb r-process abundance, as estimated for the
stellar Eu abundances, and the s-process abundance as estimated for red giants
accounts satisfactorily for the observed run of [Rb/Fe] with [Fe/H].Comment: 23 pages, 5 tables, 7 figure
On Multilingual Training of Neural Dependency Parsers
We show that a recently proposed neural dependency parser can be improved by
joint training on multiple languages from the same family. The parser is
implemented as a deep neural network whose only input is orthographic
representations of words. In order to successfully parse, the network has to
discover how linguistically relevant concepts can be inferred from word
spellings. We analyze the representations of characters and words that are
learned by the network to establish which properties of languages were
accounted for. In particular we show that the parser has approximately learned
to associate Latin characters with their Cyrillic counterparts and that it can
group Polish and Russian words that have a similar grammatical function.
Finally, we evaluate the parser on selected languages from the Universal
Dependencies dataset and show that it is competitive with other recently
proposed state-of-the art methods, while having a simple structure.Comment: preprint accepted into the TSD201
Avalanches in a Bose-Einstein condensate
Collisional avalanches are identified to be responsible for an 8-fold
increase of the initial loss rate of a large 87-Rb condensate. We show that the
collisional opacity of an ultra-cold gas exhibits a critical value. When
exceeded, losses due to inelastic collisions are substantially enhanced. Under
these circumstances, reaching the hydrodynamic regime in conventional BEC
experiments is highly questionable.Comment: 4 pages, 2 figures, 1 tabl
Open Access, Open Access, How Does Your Catalog Grow? With Selection, Access, and Usage All in a Virtual Row!
Much of the open access (OA) focus and discussion has been on journals (think Glossa), but the open access monograph has come fully into its own. University and scholarly publishers are providing high-quality books, often in areas that rely on long-form scholarship. However, open access monographs presented a challenge. How do they fit into the traditional models of selection, acquisition, cataloging, and tracking usage?
In the spring of 2016, Texas Woman’s University Libraries created a simple workflow to make open access monographs accessible through the libraries’ discovery layer using Google Sheets to track the workflow and EZproxy to track usage
Stochastic gain in population dynamics
We introduce an extension of the usual replicator dynamics to adaptive
learning rates. We show that a population with a dynamic learning rate can gain
an increased average payoff in transient phases and can also exploit external
noise, leading the system away from the Nash equilibrium, in a reasonance-like
fashion. The payoff versus noise curve resembles the signal to noise ratio
curve in stochastic resonance. Seen in this broad context, we introduce another
mechanism that exploits fluctuations in order to improve properties of the
system. Such a mechanism could be of particular interest in economic systems.Comment: accepted for publication in Phys. Rev. Let
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